CN111854753B - A Modeling Method for Indoor Space - Google Patents

Abstract

The present invention relates to a modeling method of indoor space, comprising: receiving position information of multiple integrated sensors from multiple integrated sensors; obtaining partition information of indoor space based on the grouping of multiple integrated sensors; and The position information of the above-mentioned multiple integrated sensors is used to obtain the size information of the partition. In the indoor space modeling method of the present application, the indoor space model can be established based on the detection results of one or more sensors in the sensor network. And through the built indoor space model, further perceive the indoor environment. After sensing the indoor environment, it can control the electrical appliances in the room and adjust the indoor environment.

Description

A Modeling Method for Indoor Space

technical field

The invention relates to the technical field of sensors, in particular to a modeling method of an indoor space.

Background technique

In this century, sensor technology, as one of the important pillars of modern information technology, has developed rapidly. Various sensors based on semiconductor materials, crystal materials, ceramic materials, organic composite materials, metal materials, polymer materials, superconducting materials, optical fiber materials and nanomaterials emerge in an endless stream, and gradually enter the family.

The so-called indoor space modeling refers to the establishment of indoor space model. In the prior art, the layout of the interior space is usually unchanged. For example, there are several rooms in a house and the size and orientation of each room are rarely adjusted. However, for the smart house of the future, the layout of the interior space can be easily changed. When the room layout does not change, the data center can store the externally input indoor space model. However, when the room layout is frequently changed, it becomes very inconvenient to input the interior space model from the outside every time. Therefore, there is an urgent need in this field for a unique space modeling method, which can automatically collect indoor space information according to changes in the indoor space structure or layout, so as to be able to adapt to future smart houses. .

Contents of the invention

Aiming at the technical problems existing in the prior art, the present application proposes a modeling method for indoor space, including: receiving position information of the multiple integrated sensors from multiple integrated sensors; grouping based on the multiple integrated sensors , obtaining partition information of the indoor space; and obtaining size information of the partition based on the position information of the plurality of integrated sensors.

The method as above, wherein the integrated sensor is configured to detect one or more environmental parameters of the indoor environment and/or one or more anthropometric parameters of people active in the room.

A method as above, wherein an environmental or human body parameter is jointly determined from multiple detections from one or more of the multiple integrated sensors.

The method as above, wherein the integrated sensor is configured to detect commands from a person active in the room.

The method as above, wherein the location information includes altitude.

The method as described above, wherein the position information includes horizontal relative position information.

The method as described above, further comprising: receiving grouping information of the plurality of integrated sensors from the plurality of integrated sensors.

The above method further includes: grouping the plurality of integrated sensors, and obtaining partition information of the indoor space based on the grouping information obtained after grouping.

The method as above, wherein the grouping of the plurality of integrated sensors is based at least in part on shape matching.

The method as above, wherein the grouping of the plurality of integrated sensors is based at least in part on zone partitioning.

The method as described above, wherein the area division is based on detection results of the plurality of integrated sensors.

The method as above, further comprising receiving location attribute information from the plurality of integrated sensors.

The method as described above, further comprising obtaining characteristic information of the partition of the indoor space based at least in part on the location attribute information of the plurality of integrated sensors.

The above method, wherein the location attribute information includes the radian of the location.

The above method, wherein the location attribute information includes the convexity and concaveness of the location.

The above method, wherein the location attribute information includes the functional area to which the location belongs.

The above method, wherein the location attribute information includes indoor facilities around the location.

According to another aspect of the present application, a system for indoor space modeling is proposed, including: a plurality of integrated sensors distributed in the indoor space; and a data center communicating with the plurality of integrated sensors; Wherein, the data center is configured to obtain partition information of the indoor space based on the grouping of the plurality of integrated sensors; and obtain size information of the partition based on the position information of the plurality of integrated sensors.

The system as above, wherein the location information includes altitude.

The system as above, wherein the position information includes horizontal relative position information.

The system as above, wherein the data center is configured to receive grouped information from the plurality of integrated sensors for the plurality of integrated sensors.

The above system, wherein the data center is configured to group the plurality of integrated sensors, and obtain partition information of the indoor space based on group information obtained after grouping.

The system as above, wherein the data center is configured to receive location attribute information from the plurality of integrated sensors.

The system as above, wherein the data center is configured to obtain characteristic information of the partition of the indoor space based at least in part on the location attribute information of the plurality of integrated sensors.

In the indoor space modeling method of the present application, the indoor space model can be established based on the detection results of one or more sensors in the sensor network. And through the built indoor space model, further perceive the indoor environment. After sensing the indoor environment, it can control the electrical appliances in the room and adjust the indoor environment.

Description of drawings

Below, preferred embodiment of the present invention will be described in further detail in conjunction with accompanying drawing, wherein:

Fig. 1 is a schematic structural diagram of an integrated sensor according to an embodiment of the present invention;

Fig. 2 is a structural schematic diagram of an integrated sensor according to another embodiment of the present invention;

3 is a schematic diagram of an integrated sensor housing according to another embodiment of the present invention;

Fig. 4 is a schematic structural diagram of an integrated sensor circuit according to an embodiment of the present invention;

Fig. 5 is a schematic diagram of an integrated sensor power supply structure according to an embodiment of the present invention;

Fig. 6 is a schematic structural diagram of an indoor living environment perception system according to an embodiment of the present invention;

7 is a flow chart of an integrated sensor detection method according to an embodiment of the present invention;

Fig. 8 is a schematic structural diagram of a sensor network according to an embodiment of the present invention;

FIG. 9A is a schematic diagram of a sensor network structure in a room according to an embodiment of the present application;

Fig. 9B is a schematic diagram of the positioning of integrated sensors according to an embodiment of the present invention;

Fig. 10 is a flowchart of an indoor space modeling method according to one embodiment of the present invention;

Fig. 11 is a method for sensing an indoor space environment according to an embodiment of the present invention;

Fig. 12 is a schematic diagram of an indoor model according to an embodiment of the present application;

13A and 13B are schematic diagrams of indoor environment changes according to an embodiment of the present application;

Fig. 14 is a flowchart of a method for adjusting an indoor environment according to an embodiment of the present invention;

Fig. 15 is a schematic structural diagram of an indoor space modeling element according to an embodiment of the present application;

FIG. 16 is a schematic diagram of an indoor space modeling process based on modeling elements according to an embodiment of the present invention;

17A-17D are schematic structural diagrams of an indoor facility according to an embodiment of the present application; and

Fig. 18 is a schematic flow chart of indoor space modeling based on indoor facilities according to an embodiment of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

In the following detailed description, reference is made to the accompanying drawings which are included in the specification and which illustrate specific embodiments of the application and which are included in this application. In the drawings, like reference numerals describe substantially similar components in different views. Various specific embodiments of the present application are described in sufficient detail below, so that those of ordinary skill in the art can implement the technical solutions of the present application. It should be understood that other embodiments may also be utilized or structural, logical or electrical changes may be made to the embodiments of the present application.

The invention proposes an integrated sensor for indoor living environment, and proposes a sensor network based on the integrated sensor. In some embodiments, the sensor network can also be a plurality of different sensors, and is not limited to integrated sensors. The following will take the integrated sensor as an example to illustrate the technical solution of the present application. As understood by those skilled in the art, the position of the integrated sensor may also include multiple sensors of different types.

In some embodiments of the present invention, the integrated sensor integrates multiple environmental sensors, including but not limited to: photosensitive sensors (vision), acoustic sensors (hearing), gas sensors (smell), chemical sensors (taste), pressure One or more of sensitive sensor (tactile), fluid sensor (tactile), thermal sensor (temperature), humidity sensor (humidity), magnetic sensor (magnetic field), etc. Environmental sensors detect one or more parameters of the indoor environment.

In some embodiments of the present invention, the integrated sensor integrates multiple human body sensors, including but not limited to: sound sensor, infrared sensor, ultrasonic sensor, laser sensor, gravity sensor, motion sensor, gesture sensor, temperature sensor, current sensor, One or more of voltage sensors, magnetic field sensors, displacement sensors, speed sensors, acceleration sensors, etc. Occupancy sensors are used to detect one or more parameters of a person active in a room.

In some embodiments, the environment sensor and the human body sensor may be the same sensor, such as an acoustic sensor. The sound sensor has the function of detecting sound. It can detect both the sound in the environment and the sound made by people. In some embodiments, the same sensor may have both functions of detecting environmental parameters and human parameters, such as a temperature sensor. The temperature sensor can not only detect the temperature of the indoor air, but also remotely detect the temperature of the human body. However, detecting air temperature and detecting human body temperature at a distance are two completely different functions.

In some embodiments, multiple results detected by the integrated sensor jointly characterize an environment or human body parameter. For example, the results of temperature detection and smoke detection in an integrated sensor together indicate a fire in a room. In some embodiments, the detection results of multiple integrated sensors jointly characterize an environment or human body parameter. For example, precise positioning can be achieved by setting multiple cameras in appropriate positions. For another example, the combination of the gravity detection result of the integrated sensor at a certain position and the infrared detection result of the integrated sensor at another position indicates that there is activity in a certain position in the room.

In some embodiments, environmental or human parameters include commands issued by objects or humans in the environment. For example, microwave detection results from an integrated sensor at one location can locate a person at one location, combined with instructions from a gesture sensor at another location, combined to indicate an active command issued by the person.

As a result, one or more integrated sensors can detect and provide multiple environmental or human parameters of the indoor living environment, which can replace the existing various types of sensors, and provide the basis for smart home data centers, such as computers or servers. The data service of the environment and human body is simple, convenient, easy to install and maintain, making smart home more convenient to realize.

Fig. 1 is a schematic structural diagram of an integrated sensor according to an embodiment of the present invention. As shown, integrated sensor 100 includes housing 102 , probe 104 , and circuit board 106 . In some embodiments, probe 104 and circuit board 106 are mounted on housing 102 . In some embodiments, housing 102 includes one or more support structures therein. Probe 104 and circuitry 106 are mounted to housing 102 by one or more support structures. Alternatively, housing 102, probe 104, and circuit board 106 are all mounted to one or more support structures such that housing 102, probe 104, and circuit board 106 are assembled.

As described in the background of the present invention, an important application of the integrated sensor of this embodiment is to detect indoor human settlements. In some embodiments, at least a portion of probe 104 is in direct contact with the room environment. For example, the probe 104 is part of the outer surface of the integrated sensor so that it is in direct contact with the room environment. In some embodiments, the probe 104 includes one or more channels in communication with the room environment, thereby indirectly contacting the room environment. Of course, probe 104 may be in contact with the room environment both directly and indirectly.

In some embodiments, probe 104 includes a plurality of sensors 11-14. The multiple sensors 11-14 are multiple environmental detectors and/or human body detectors, and are used to detect multiple environmental parameters and/or human body parameters. A plurality of sensors 11 - 14 are electrically connected to circuit 106 .

As shown, the plurality of sensors 11-14 are electrically connected to the circuit board 106 by a plurality of wires. In some embodiments, these lines are fixed lines disposed on the housing 102 or the supporting structure, such as conductive coating, conductive glue, or conductive layer, etc., instead of electrical wires.

In some embodiments, circuit board 106 includes a single printed circuit board and electronic components on multiple boards, such as processors and communication modules. The circuit board 106 receives the detection results from the sensors 11-14 through multiple electronic components on the board, processes the detection results from the sensors 11-14, and then forwards them to the home data center.

Different from the temperature or humidity detectors in the prior art, the integrated sensor of this embodiment is suitable for being installed in indoor facilities such as walls, floors or ceilings, so as to integrate with the indoor environment. This method has many advantages: on the one hand, it can simplify the appearance design of the integrated sensor, and there is no need to worry that the integrated sensor will affect the overall appearance of the room; on the other hand, it can also make the installation of the integrated sensor more convenient, and will not damage the walls and floors of the indoor room Or smallpox and other parts. More importantly, installing integrated sensors on indoor walls, floors, or ceilings can provide more space to integrate multiple sensors without worrying about space constraints, which is more conducive to the implementation of integrated sensors.

In some embodiments, brackets are included in the wall, floor or roof for mounting the integrated sensor. The bracket itself is part of the wall, floor or ceiling, and the integrated sensor is mounted on the bracket to be placed in the wall, floor or ceiling. In some embodiments, the walls, floors or ceilings are movable walls, floors or ceilings that are not rigidly connected to the original walls, floors and roofs of the room. The application number is 201910295819.8, and the application date is April 12, 2019. The name of the invention is a prefabricated building and an internal tension wall. It discloses an internal tension wall, which is not compatible with the original wall, floor and roof. An instance of a hardwired movable wall. This application is incorporated herein by reference in its entirety. The application number is 201910858472.3, and the application date is September 11, 2019. The name of the invention is a smallpox and a prefabricated building. It discloses a smallpox, which is a smallpox that is not hard-connected with the original wall, floor and roof. instance. This application is also incorporated herein by reference in its entirety. Sufficient space is included in the movable wall and ceiling of the above two examples to accommodate the integrated sensor of the present application. Therefore, as a preferred embodiment, the integrated sensor of the present application is used together with movable walls, floors or ceilings that are not hard-connected with the original walls, floors and roofs in the room. There are many ways in the prior art to realize the installation of the integrated sensor, not limited to the way of the bracket, which will not be repeated here.

In embodiments where the integrated sensor is placed on a wall, floor, or ceiling, the manner in which the integrated sensor contacts the indoor environment can be accomplished in a variety of ways. In the embodiment shown in FIG. 1 , the probe 104 becomes the surface or part of the integrated sensor 100 that is in direct contact with the environment. The sensors 11-14 detect indoor environment parameters or human body parameters through the surface of the probe 104 that is in direct contact with the environment. In the following two specific embodiments, other design schemes of integrating the sensor probe and the housing are shown. Certainly, the implementation manner of the integrated sensor of the present invention is not limited to this.

Fig. 2 is a schematic structural diagram of an integrated sensor according to another embodiment of the present invention. The integrated sensor 200 shown in FIG. 2 includes: a housing, a probe 204 and a circuit board (not shown); wherein, parts of the housing and the circuit board are similar to the corresponding parts of the embodiment described in FIG. 1 . Likewise, the integrated sensor of the embodiment shown in FIG. 2 may also include a support structure. Further, the wiring between the sensor and the circuit board can also be implemented in a manner similar to the embodiment described in FIG. 1 . I won't repeat them here.

As shown in FIG. 2 , the probe 204 of the integrated sensor 200 includes a channel 205 that communicates with the interior space 207 of the integrated sensor 200 . One or more sensors 21 - 24 are arranged in the channel 205 and the interior space 207 . Sensors 21 - 24 are in indirect contact with the room environment through channel 205 . These sensors include, but are not limited to, acoustic sensors, temperature sensors, humidity sensors, magnetic sensors, gas sensors, electromagnetic signal sensors, and the like. The channel 205 and the internal space 207 provide enough space to accommodate multiple sensors, so that the integrated sensor of the present application can have a smaller volume and a higher integration level.

In some embodiments, the probe 204 of the integrated sensor 200 includes a probe surface 209 in direct contact with the room environment. Channel 205 is provided through probe surface 209 . Included on the probe surface 209 are one or more sensors 25-28. The sensors 25-28 are in direct contact with the indoor environment. These sensors include, but are not limited to: optical sensors, pyroelectric sensors, infrared sensors, pressure sensors, and the like. The probe surface 209 provides a surface in direct contact with the indoor environment, which is conducive to obtaining accurate detection results.

Fig. 3 is a schematic diagram of an integrated sensor housing according to yet another embodiment of the present invention. The integrated sensor shown in FIG. 3 includes: a casing, a probe 304 and a circuit (not shown); wherein, the casing and the circuit are similar to those in the embodiment shown in FIG. 1 . Likewise, the integrated sensor of the embodiment shown in FIG. 3 may also include a support structure. Further, the circuit between the sensor and the circuit can also be implemented in a similar manner to the embodiment shown in FIG. 1 . I won't repeat them here.

As shown in FIG. 3 , the probe 304 of the integrated sensor 300 includes a plurality of channels 305 , wherein each channel 305 communicates with an internal space 307 of the integrated sensor 300 . One or more sensors 31 - 35 are arranged in the channel 305 and in the interior space 307 , which are indirectly in contact with the room environment via the channel 305 . These sensors include, but are not limited to, acoustic sensors, temperature sensors, humidity sensors, magnetic sensors, gas sensors, electromagnetic signal sensors, and the like. The channel 305 and the internal space 307 provide enough space to accommodate multiple sensors, so that the integrated sensor of the present application can have a smaller volume and a higher integration level.

In some embodiments, the probe 304 of the integrated sensor 300 includes a probe surface 309 in direct contact with the room environment. A plurality of channels 305 are provided through the probe surface 309 . One or more sensors 36-39 are included on the probe surface 309. The sensors 36-39 are in direct contact with the room environment. These sensors include, but are not limited to: optical sensors, pyroelectric sensors, infrared sensors, pressure sensors, and the like. The probe surface 309 provides a surface in direct contact with the indoor environment, which is conducive to obtaining accurate detection results.

In some embodiments, there may be a spacer between the integrated sensor and the indoor environment. These spacers include hollow or ventilated decorative panels, such as wood boards, cardboards, stone panels, glazed tiles, etc., or panels coated with wall paint, wallpaper, wall coverings, wall mud, wall stickers and other materials; hollow or ventilated Decorative objects, such as decorative paintings, photos, handicrafts, textiles, collectibles, flowers, etc.; or furniture or household appliances, etc. The presence of these spacers does not affect the direct or indirect contact between the integrated sensor and the indoor environment.

Fig. 4 is a schematic structural diagram of an integrated sensor circuit according to an embodiment of the present invention. As shown, the integrated sensor 400 includes a probe 401 and a circuit board. The probe 401 includes one or more analog sensors, one or more digital sensors and one or more switch sensors. The circuit board includes a processor 402 . In some embodiments, the processor 402 includes multiple ports corresponding to different sensors. For example, the processor 402 includes 8-channel I/O ports, of which 2 channels are analog quantities; 2 channels are digital quantities; and 2 channels are switch quantities. Each channel of the processor 402 corresponds to sensors of different types of detection results.

In some embodiments, in order to increase the number of sensors that can be accommodated by the integrated sensor and reduce the limitation of the processor channel on the number of sensors, field bus or non-field bus is used to realize the communication between the processor and multiple sensors.

Referring to FIG. 4 , the first analog sensors 41 and 42 of the probe 401 are electrically connected to the processor 402 through analog lines. The detection results of the analog sensors 41 and 42 are connected to the digital circuit through the analog-to-digital signal converter ADC, and then electrically connected to the processor 402 . The first digital sensors 43 and 44 of the probe 401 are electrically connected to the processor 402 through digital lines. The first switching value sensors 43 and 44 of the probe 401 are electrically connected to the processor 402 through a switching value line. In some embodiments, the digital and binary lines can be combined into one line. Such lines include but are not limited to: remote digital IO lines, such as: PROFIBUS, MODBUS, etc.; or field bus lines, such as: RS485, CAN, CC-LINK, D-Net, ASI, DP bus, etc.; or data bus lines, For example: PCI, PCIe, USB bus, etc. Since the real-time detection requirements of integrated sensors are not high, some high-delay non-field buses (such as data buses) can also be applied in the present invention.

In some embodiments, one or more signal conditioning circuits may be included between the sensor and the line, which are used to convert the detection signal from the sensor into a standard analog signal, digital signal, differential signal or switch signal to for subsequent signal processing.

In some embodiments, one or more controllers may be included in the analog quantity, digital quantity or switch quantity lines, which are used for signal processing and control of some sensors to reduce the workload of the processor 402, reduce costs, and improve system efficiency.

In some embodiments, some sensors can also be provided on the circuit board. For these sensors, all associated electronics can be integrated on the sensor-integrated circuit board. In other embodiments, for the sensor arranged outside the circuit board, except for the necessary wiring between the sensor and the circuit board, other electronic devices, including the signal conditioning circuit, the controller and the wiring between them are all arranged on the circuit board. board, thereby improving the integration of multiple sensors.

In this embodiment, the processor 402 can support different sensors through multiple interfaces of different types, and can also communicate with sensors of different types of measurement results through analog, digital and switch lines supporting multiple sensors, The integration of multiple sensors of various types can be realized; and the number of sensors is not limited by the number of ports of the processor 402 .

In some embodiments, in order to add or replace sensors conveniently, the integrated sensor 400 digital or switch lines may respectively include a plug-and-play interface, so as to facilitate adding or changing the functions of the integrated sensor 400 as required. For example, one or more plug-and-play interfaces are included in the digital or analog lines of the integrated sensor 400, including but not limited to PCIe, PCI, and USB interfaces. Sensors with digital or switch outputs can be connected to these plug-and-play interfaces. For sensors whose output result is analog, it can be converted into a digital signal by ADC, and then realize plug-and-play through the plug-and-play interface in the digital or analog line.

In some embodiments, integrated sensor 400 also includes a display module 404 in communication with processor 402 . The display module 404 is used to display the status of the integrated sensor. For example, the display module 404 may be a liquid crystal display, which displays working status or detection results. For another example, the display module 404 is a plurality of indicator lights, which reflect the working status of the integrated sensor 400 through states such as color, lighting, and flickering.

In some embodiments, integrated sensor 400 also includes memory 406 in communication with processor 402 . The memory is used to store data of the integrated sensor 400, including but not limited to: detection results of the integrated sensor, data of the integrated sensor itself (such as location, working status, etc.), and data during the working process of the integrated sensor.

In some embodiments, integrated sensor 400 also includes a communication module 408 . The communication module 408 is used for communicating with the outside (such as other integrated sensors or a home data center). In some embodiments, the communication module 408 may be a wireless module. The communication protocols adopted by the wireless module include but are not limited to: 5G, 2.5G, Wi-Fi, Zigbee, Lora, NB-IOT, Z-Ware, Bluetooth, etc.

In some embodiments, the communication module 408 may be a wired module. Wired modules are used for external (such as other integrated sensors or home data center) communication. The communication protocols used by the wired module include but are not limited to: remote digital IO lines, such as PROFIBUS, MODBUS, etc.; or field bus lines, such as: RS485, CAN, CC-LINK, D-Net, ASI, DP bus, etc.; or data Bus line, such as: PCI, PCIe, USB bus, etc. Especially for some embodiments where the integrated sensor is arranged on a movable wall or ceiling, a line for wired communication may be pre-set in the movable wall or ceiling, so as to support the integrated sensor to communicate in a wired manner.

In some embodiments, various integrated sensors can communicate with each other through their respective communication modules 408 to form a communication network, such as a mobile ad hoc (ad hoc) network.

Fig. 5 is a schematic diagram of an integrated sensor power supply structure according to an embodiment of the present invention. As shown in the figure, the integrated sensor also includes a battery 501 and a power management module 502 . Under the control of the power management module 502 , the battery 501 supplies power to each sensor, such as sensor 1 and sensor 2 . Similarly, the power management module 502 also controls the battery 501 to supply power to the processor 402 and also to supply power to the wireless module and memory.

Since the integrated sensor is placed in the wall, floor or ceiling, wiring the power supply line is an optional option. In some embodiments, the integrated sensor also includes a wireless charging module 504 connected to the battery 501 . Wireless charging for the battery 501 can be realized through the wireless charging module 504 . In some embodiments, the integrated sensor also includes a solar charging module 506 connected to the battery 501 . The solar charging module 506 can convert light energy into electrical energy to charge the battery 501 . In the embodiment of the movable wall, floor or ceiling, the movable wall, floor or ceiling already includes a power line, therefore, the integrated sensor can also be directly powered through the power line therein. In this embodiment, the battery 501, the wireless charging module 504 and the solar charging module 506 are all optional.

As shown by some embodiments of the present invention, integrated sensors have the following advantages:

1. Small size, light weight, low power consumption. The integrated sensor of the present invention realizes the integration of multiple sensors, and is an independent electronic system with complete functions, which can be implemented on a small single-chip integrated circuit board. While realizing multiple detection functions, it can also reduce the size, weight and power consumption.

2. Low cost. On the one hand, the integrated sensor of the present invention is convenient for mass production, so that the cost can be greatly reduced. On the other hand, multiple sensors can be arranged and managed centrally, and the cost of sensor installation and management is also greatly reduced.

3. High reliability. The integrated sensor of the invention integrates a plurality of electronic devices on a circuit board, greatly reduces connection points and soldering points, and the factory inspection ensures high reliability of the devices. Therefore, compared with multiple discrete sensors, the reliability of the circuit is greatly improved and the maintenance cost is reduced.

4. Good scalability. The integrated sensor of the present invention realizes integration and mutual communication of multiple sensors and communication with an external data center, facilitates the realization of different functions on this basis, and has excellent scalability.

Fig. 6 is a schematic structural diagram of an indoor living environment sensing system according to an embodiment of the present invention. As shown in the figure, the indoor living environment sensing system of this embodiment includes a plurality of integrated sensors, such as integrated sensors A-H, which are respectively arranged in the indoor environment. In some embodiments, multiple integrated sensors are respectively arranged in the walls, floors and ceilings. In particular, the walls, floors and ceilings are movable walls, floors and ceilings. Further, the indoor living environment perception system of this embodiment includes a home data center. Multiple integrated sensors communicate wirelessly with the home data center. A home data center can be a server, a dedicated computer, a computer, a notebook, or a mobile device such as a mobile phone or a pad.

On the one hand, the home data center is the center for storage, processing and mining of the detection results (data) of various integrated sensors, and it is also the command center for using these data to control the indoor living environment. On the other hand, the home data center is also the gateway of the home network. A home data center includes a gateway. The detection results (data) of all integrated sensors cannot be sent outside without going through the home data center. Therefore, the home data center is also the center of data protection.

In some embodiments, a home data center includes one or more processors, a first communication module, and a second communication module. The first wireless module is used for communicating with multiple integrated sensors, receiving one or multiple detection results from multiple integrated sensors; or sending control commands to multiple integrated sensors. The first communication module may be a data transceiver of communication protocols such as 5G, 2.5G, Wi-Fi, Zigbee, Lora, NB-IOT, Z-Ware, and Bluetooth. The second communication module is used to communicate with external networks in a wired or wireless manner, including but not limited to mobile Internet, Internet, and other networks capable of two-way communication.

In some embodiments, the home data center can communicate with body-worn sensors in a wired or wireless manner to obtain detection results from non-integrated sensors. In some embodiments, the home data center communicates with the home appliances in the house in a wired or wireless manner, so as to obtain detection results from non-integrated sensors.

In some embodiments, the home data center can process detection results from integrated sensors or non-integrated sensors, and based on this, use technologies such as big data and artificial intelligence to adjust one or more parameters of the indoor environment, thereby realizing Active indoor climate regulation.

FIG. 7 is a flowchart of an integrated sensor detection method according to an embodiment of the present invention. As shown in the figure, the integrated sensor detection method includes: at step 710, the home data center receives a detection result from a first sensor of the first integrated sensors. The first integrated sensor sends the detection result of the first sensor to the home data center through its wireless module.

In step 730, the detection result from the second sensor of the first integrated sensor and/or the detection result of the third sensor of the second integrated sensor is received at the home data center. The first integrated sensor sends the detection result of its second sensor to the home data center through its wireless module; or, the second integrated sensor sends the detection result of its third sensor to the home data center through its wireless module; or, the first Both the detection result of the second sensor of the integrated sensor and the detection result of the third sensor of the second integrated sensor are sent to the home data center.

In step 750, in the home data center, the detection results of the first sensor, the second sensor and/or the third sensor are comprehensively analyzed to obtain one or more indoor environment parameters or human body parameters. As understood by those skilled in the art, the present invention does not limit the type, quantity and detection time of integrated sensors and the sensors therein. By comprehensively analyzing these detection results, the desired indoor environment parameters or human body parameters can be obtained more accurately in the home data center. parameter.

In some embodiments, step 740 further includes receiving detection results from a fourth sensor worn on the body at the home data center. In an embodiment, the home data center comprehensively analyzes the detection results of the first sensor, the second sensor, the third sensor and/or the fourth sensor, and then obtains one or more indoor environment parameters or human body parameters. Through the detection results of the fourth sensor worn on the human body, one or more parameters of the human body can be known more accurately, so that desired indoor environment parameters or human body parameters can be obtained more accurately.

In some embodiments, at step 770, the home data center also controls one or more electrical appliances in the indoor environment according to the one or more indoor environment parameters or human body parameters from step 750, and adjusts one or more indoor environment parameters. By adjusting one or more indoor environment parameters, the indoor environment is adjusted to the situation suitable or desired by the user. Using the detection results of the integrated sensors, the method of this embodiment realizes active indoor living environment changes, thus becoming a direct application of active artificial intelligence.

Although this application takes the indoor living environment as an example to illustrate the technical solution of the integrated sensor of the present invention; however, those skilled in the art should understand that the application of the integrated sensor of the present invention is not limited to indoors, and can be applied to other independent spaces. Including but not limited to static outdoor space, mobile space (such as inside a car), etc.

Sensor Networks

According to an embodiment of the present invention, a plurality of integrated sensors constitute an integrated sensor network. The integrated sensor network together with the home data center becomes an integral part of the indoor environment perception system for human settlements. In the integrated sensor network, each integrated sensor can communicate with each other, or communicate with the sub-center of the integrated sensor network. In some embodiments, the home data center can serve as the central node of the sensor network. In an integrated sensor network, individual integrated sensors are also able to communicate with the home data center. In some embodiments, under the coordination of the sub-center of the integrated sensor network or the home data center, multiple integrated sensors can work together to achieve better control of the indoor living environment.

In another aspect, the present invention also provides a sensor network. An integrated sensor network as described above may be an example of a sensor network. A sensor network includes multiple sensors and data centers. Multiple sensors are placed at multiple positions in the room, which may be integrated sensors as described above, or other types of sensors. In the following description taking an integrated sensor as an example, those skilled in the art should understand that other types of sensors are also feasible. The data center communicates with a plurality of sensors in a wired or wireless manner, and detects the indoor environment based at least in part on a plurality of position information of the plurality of sensors. The data center can be a home data center or a branch center.

Fig. 8 is a schematic diagram of a sensor network structure according to an embodiment of the present invention. As shown in FIG. 8 , the indoor living environment includes multiple rooms, for example: room A, room B, and room C; where room A and room C communicate with room B respectively. Multiple integrated sensors A01-A05 are arranged in room A; multiple integrated sensors B01-B04 are arranged in room B; and multiple integrated sensors C01-C05 are arranged in room C. In one embodiment, individual integrated sensors can communicate with each other even if they are arranged in different rooms. For example, integrated sensor A01 can communicate directly with integrated sensor C05. In some embodiments, the sensor network shown in FIG. 8 may include a data center (not shown) capable of communicating with each integrated sensor in each room. In some embodiments, each room may include sub-centers, such as sub-center A, sub-center B, and sub-center C (not shown). The physical structure of the sub-center is similar to that of the data center, and it can be a device with computing power. A sub-center is not required. When the room is relatively large or the number of integrated sensors in the room is large, the setting of the sub-center can reduce the workload of the data center and is also conducive to responding to environmental changes more quickly. In some embodiments, various integrated sensors work together through a sub-center or a data center without direct communication.

In some embodiments, integrated sensors in a room may be installed in indoor facilities such as movable or immovable walls, floors or ceilings. Taking room A as an example, the integrated sensors can be installed at multiple positions on the walls around room A to form a sensor network for room A. In some embodiments, the integrated sensors can also be installed on the ceiling and/or floor of room A (not shown in the figure). In some embodiments, smart wearable devices (such as smart bracelets, smart watches, smart phones, etc.) in the room can also communicate with the data center.

In some embodiments, after forming a sensor network of one or more rooms, the data center can detect the indoor environment through multiple integrated sensors. Different from the prior art, the integration of multiple sensors at different locations improves the environment detection results in at least two aspects. On the one hand, detecting from multiple locations can obtain the distribution of the indoor environment, thereby improving the accuracy of detection. For example, in the prior art, there may be only one temperature and humidity detector in a room, and the temperature and humidity distribution in the room may be uneven, but the temperature and humidity sensor can only detect the temperature and humidity around it. Since there are multiple integrated sensors at different locations in the room, these integrated sensors can detect the temperature and humidity in their respective locations. The data center can obtain the distribution of temperature and humidity according to the temperature and humidity of each location, and more accurately reflect the temperature and humidity in the room. On the other hand, integrated sensors at multiple locations are able to detect multiple types of environmental parameters. Different types of environmental parameters obtained at different locations enable data centers to detect environmental parameters that cannot be detected by existing sensors.

In some embodiments, the integrated sensor can detect one or more environmental parameters of the indoor environment, and the data center can jointly determine based on the multiple detection results of one or more of the multiple integrated sensors in the sensor network and their location information an environment parameter. For example, the data center may determine the temperature distribution in the room according to the temperature in the room detected from multiple integrated sensors and the locations of the multiple integrated sensors.

In some embodiments, the integrated sensor can also detect one or more human body parameters of indoor active people, and the data center can detect multiple detection results of one or more of the multiple integrated sensors of the sensor network and its location information jointly determine a body parameter. For example, the data center can determine the movement route of the active people in the room according to the infrared information from the human body detected by multiple integrated sensors and the positions of the multiple integrated sensors.

In some embodiments, the data center may jointly determine a command issued by an indoor active person according to multiple detection results of one or more multiple integrated sensors of the sensor network. For example, a data center can determine that a person issued a voice command to adjust the temperature around them based on infrared information from a human body detected by one integrated sensor and voice information from an active person detected by another integrated sensor. Infrared information via integrated sensors is useful to determine the person issuing the command and its location. In some embodiments, the data center can adjust the indoor environment according to multiple detection results of one or more multiple integrated sensors of the sensor network and/or commands from indoor active people.

In some embodiments, when the integrated sensor communicates with the data center for the first time, it can send identity information and its location information to the data center. In some embodiments, the integrated sensor needs to be registered in the data center before it can join the data center's sensor network. When registering, the integrated sensor sends its identity information, such as ID; and its location information. In some embodiments, the identity information of the integrated sensor includes the room it is located in. For example, if the integrated sensor is in room A, room B, or room C, A in the sensor identity information A02 means room A, and 02 means the number is sensor No. 2. When the identity information of the integrated sensor includes room information, its location information may be location information in the room. In some embodiments, the identity information of the integrated sensor may also include integrated sensor location status information. For example: integrated sensors are movable or non-removable sensors. For removable integrated sensors, the letter X is included in the identification. For example X01, the movable sensor numbered 1.

In some embodiments, when the integrated sensor sends the detection result, its identity information and location information may be sent to the data center at the same time. Especially mobile sensors, which update their location by sending location information. For non-movable sensors, if the room facility where it is located is movable, it will re-register after changing the location or send the updated location information at the same time when sending the detection result next time.

In some embodiments, the location information of the integrated sensor includes altitude. That is to say, the position information of the integrated sensor is three-dimensional position information. However, the existing indoor positioning usually does not include height information. Three-dimensional position information is conducive to establishing a more accurate environment model. Further, in some embodiments, the location information includes horizontal relative location information. Altitude information and horizontal relative position information together define the position of the integrated sensor. Wherein, the horizontal relative position information is based on the relative position to the positioning point, and the positioning point is the position of the positioning sensor or a preset point of the room where the sensor is located. Indoor positioning often appears to be difficult, and precise positioning is difficult, but precise positioning is important for the present invention. In order to solve this problem and reduce the positioning cost, in this embodiment, the room is taken as a unit, and the horizontal relative position information is used to reduce the difficulty of positioning. The positioning point of the horizontal relative position is the preset point in the room, or the positioning integrated sensor on the preset point. In this way, the three-dimensional space positioning relative to the origin of the coordinates becomes the relative positioning of predetermined points in the room, so that auxiliary facilities such as walls of the room can be fully utilized to reduce the difficulty of relative positioning. And through the positional relationship between the predetermined point and the origin of the coordinates, the positions of all integrated sensors relative to the origin of the coordinates can be easily calculated.

Fig. 9A is a schematic diagram of a sensor network structure in a room according to an embodiment of the present application. As shown in the figure, the room 900 includes walls 910, 920 and 930 (only three are shown), a ceiling 940 and a floor 950; wherein the walls 910 and 930 are connected to the wall 920 respectively. Each wall is connected to the ceiling 940 and the floor 950 to form an indoor space. In some embodiments, the room 900 can also include a partition wall 960, which can be connected to the wall 910 and set between the ceiling 940 and the floor 950, and can be used to separate the indoor space, and can divide the indoor space into multiple partitions. space. In some embodiments, partition wall 960 is a movable partition wall.

In some embodiments, the connection between the wall 920 and the wall 930 includes a corner 970 , which is more protruding than the walls 920 and 930 . In some embodiments, the corner can also have other shapes, such as fan-shaped. In some embodiments, the walls are also not straight overall. For example: the wall has a certain curvature, concave and convex, etc.

In some embodiments, multiple integrated sensors are included in the room. The wall 910 may include integrated sensors 911-913, wherein the integrated sensor 911 is located at the junction of the wall 910 and the ceiling 940, the integrated sensor 912 is located at the junction of the wall 910 and the floor 950, and the integrated sensor 913 is located at the junction of the wall 910, the floor 950 and the partition. Junction of wall 960. The wall 920 may include an integrated sensor 921 located at the center of the wall 920 . The wall 930 includes integrated sensors 931 - 933 , the integrated sensor 931 is located at the junction of the wall 930 and the ceiling 940 , the integrated sensor 932 is located at the junction of the wall 930 and the floor 950 , and the integrated sensor 933 is located at the center of the wall 930 . The ceiling 940 includes an integrated sensor 941 located at the center of the ceiling 940 . The floor 950 includes an integrated sensor 951 located at the center of the floor 950 . The partition wall 960 includes integrated sensors 961-963, wherein the integrated sensor 961 is located at the junction of the partition wall 960 and the ceiling 940, the integrated sensor 962 is located between the partition wall 960 and the floor 950, and the integrated sensor 963 is set at the center of the partition wall 960. The corner 970 includes integrated sensors 971 and 972 , wherein the integrated sensor 971 is located at the junction of the corner 970 and the ceiling 940 , and the integrated sensor 972 is located at the junction of the corner 970 and the floor 950 .

In some other embodiments, the wall 910 , the wall 920 , the wall 930 , the ceiling 940 , the floor 950 or the partition wall 960 may further include integrated sensors in different numbers and in different positions. For example: the integrated sensor 911 can also be located on the ceiling, or divide the wall, ceiling, floor, or partition into multiple rectangles, and set an integrated sensor at the center of each rectangle, or place each corner and center of each rectangle separately. Set up an integrated sensor etc.

In some embodiments, the sensor network includes integrated sensors 911 - 913 , integrated sensors 921 , integrated sensors 931 - 933 , integrated sensors 941 , integrated sensors 951 , integrated sensors 961 - 963 , integrated sensors 971 and 972 within room 900 . These integrated sensors are all able to communicate with the data center. In some embodiments, the smart device 980 may be held or worn by the user. The smart device 980 is also capable of communicating with the data center.

Figure 9B is a schematic diagram of integrated sensor positioning according to one embodiment of the present invention. As shown in the figure, taking the positioning of the integrated sensor 933 as an example, the predetermined point is the center point A of the room floor. The integrated sensor 933 does not have a positioning function, but supports the input of the altitude and the horizontal relative position to the predetermined point A in the form of input. A typical operation is that the height and horizontal relative positions are performed by the worker setting up the integrated sensor 933 using a handheld laser rangefinder. Workers first measure the distance Z between the integrated sensor 933 and the ground with a laser rangefinder. At the predetermined point A, the distance X from the predetermined point A to the wall 930 is measured with a laser range finder, and the projection point B of the predetermined point A on the wall 930 is determined. Then project point B to place a light blocking device. Then, at the projection point of the integrated sensor 933 on the ground, the distance Y between this point and the projection point B of the predetermined point A is measured by using a laser range finder. The measured distances X, Y and Z are input to the integrated sensor 933, where X and Y are the horizontal relative distances of the integrated sensor 933 relative to the predetermined point A. Wherein, X and Y can be positive or negative numbers to indicate the direction relative to the predetermined point A. In other words, the predetermined point is similar to a coordinate origin in the room. The data center stores the location of the predetermined point A. The data center can calculate the position of the integrated sensor 933 from the X, Y and Z of the integrated sensor 933 and the position of the predetermined point A. In some cases, the shape of the room is irregular. At this time, two predetermined points can be arranged in the room. By measuring the distance between the projection point of the integrated sensor on the ground and two predetermined points as the horizontal relative position. In this mode, the position of the integrated sensor can also be precisely calculated. The error is at centimeter level or below. Likewise, other integrated sensors within room 900 may be positioned in a similar manner. This method is easy to operate, low in cost, and does not require more hardware support.

In some embodiments, an integrated sensor may include a locator. Positioning parts can use UWB, infrared, ultrasonic and other methods to achieve precise positioning. A positioning device (for example, a UWB base station or an infrared or ultrasonic emitting device) is included in the room, and the location thereof is a positioning point. The positioning device can communicate with the positioning part in the integrated sensor, so that the positioning of the integrated sensor can be realized more easily. However, the cost is relatively high. The accuracy of this positioning method is related to the technology used. In some cases, centimeter-level positioning in the room can be achieved through the positioning element.

An important application of the sensor network of the present invention is the precise detection and adjustment of the indoor environment. According to an embodiment of the present invention, an indoor space model can be established according to multiple detection results of one or more integrated sensors of the sensor network. Based on the indoor space model, the indoor environment can be further perceived. After sensing the indoor environment, the data center can control the electrical appliances in the room and adjust the indoor environment.

Interior Space Modeling

The so-called indoor space modeling refers to the establishment of indoor space model. In the prior art, the layout of the interior space is usually unchanged. For example, there are several rooms in a house and the size and orientation of each room are rarely adjusted. However, for the smart house of the future, the layout of the interior space can be easily changed. When the room layout does not change, the data center can store the externally input indoor space model. However, when the room layout is frequently changed, it becomes very inconvenient to input the interior space model from the outside every time. Therefore, if the layout of the room can be obtained automatically, or automatically updated when the layout of the room changes, so as to obtain the model of the interior space, it can be more suitable for smart houses in the future. This automatic method of obtaining and updating room layouts is known as interior space modeling. The sensor network based on the present invention can conveniently realize such indoor space modeling. The indoor layout information obtained through indoor space modeling may not be completely accurate, but it can already meet the requirements of use.

Fig. 10 is a flowchart of a method for modeling an indoor space according to an embodiment of the present invention. As shown in the figure, the space modeling method includes the following steps: In step 1010, location information of a plurality of integrated sensors is received from the plurality of integrated sensors. In this embodiment, spatial modeling is based on location information of multiple integrated sensors. As mentioned earlier, the data center can obtain the location of multiple integrated sensors in the sensor network arranged in the room. The indoor space information reflected by the positions of these integrated sensors is used to restore the indoor space layout as accurately as possible to realize indoor space modeling. As mentioned earlier, the integrated sensor can send its location information when it registers with the data center or when it sends the detection result. If the position of the integrated sensor changes, it needs to register with the data center as the master node of the sensor network again; or when sending the detection result, update its own position at the same time.

In some embodiments, the data center may also utilize other information to assist in spatial modeling. Such information includes, but is not limited to, the original house layout; the layout of the non-removable part of the house; additionally arranged positioning point information, etc. For example, a data center can store the original house layout. Although the layout of the house has changed, the original layout of the rooms can still be helpful. Combining location information from multiple integrated sensors makes it easier to derive new house layouts and model interior spaces. For example, in future houses, only the non-removable parts of the house are provided, and the layout such as the division of rooms is determined by the user himself. The data center can store the layout of the non-removable parts of the house. Combining location information from multiple integrated sensors makes it easier to derive new house layouts to model interior spaces. Of course, additional positioning points are possible in addition to the integrated sensors. The information of these anchor points is also beneficial to obtain the indoor space model.

At step 1020, based on the grouping of the plurality of integrated sensors, a partition of the indoor space is obtained. In some embodiments, the data center can group information from multiple integrated sensor receivers, enabling multiple integrated sensors to be grouped, so that zoning of the indoor space can be obtained. For example: All integrated sensors in the same room can be grouped together. In the embodiment shown in FIG. 8 , the data center divides all the integrated sensors into three groups A, B and C according to the ID of each integrated sensor. Movable integrated sensors can be grouped individually if the room includes them. For groups of non-removably integrated sensors, each group may correspond to a room. In some embodiments, further, groupings of integrated sensors may include subgroups, which may represent local facilities of a room (eg, walls, ceilings, floors, etc.) and the like. Some integrated sensors with the lowest heights belong to the ground subgroup; some integrated sensors with the highest heights belong to the ceiling subgroup; those with different heights but horizontal relative positions in a straight line represent a wall subgroup. That is, for further groupings of integrated sensors within the same grouping, information about in-room facilities can be obtained. This information is useful for modeling indoor spaces.

In some embodiments, if the room information cannot be obtained from the identity information of the integrated sensors, the data center can automatically group the integrated sensors according to the location characteristics of the integrated sensors, that is, automatically obtain the room layout of the house according to the location characteristics of the integrated sensors information. For example, data centers can enable grouping of integrated sensors based on shape matching. Usually, the shape of the room is regular. For example, a cuboid or a room composed of multiple cuboids is the most common. There are also some rooms that are irregular in shape. For example, a room composed of cuboids and curved surfaces. The data center stores these common room shapes, uses the common room shapes to match the positions of multiple integrated sensors, and selects the best matching scheme as the room layout.

In some embodiments, data centers may also group integrated sensors based on zoning. In some embodiments, area division may be performed based on a distance optimization scheme to a predetermined point. Specifically, a number of predetermined points are given in the area of the number of integrated sensors. The predetermined point setting scheme with the smallest cumulative result of the distance between the integrated sensor around these predetermined points and the predetermined point is the optimal solution. For this optimal solution, each predetermined point corresponds to a room, thereby identifying the layout of the room.

In some embodiments, the area division may be based on an object recognition algorithm to find different areas that may belong to the seemingly scattered multiple integrated sensor locations. Object recognition algorithms based on deep learning, including but not limited to, R-CNN, YOLO, or SSD. The existing integrated sensor arrangement and room layout can be used as a data set to train the target recognition algorithm model. The area division of multiple integrated sensors can be realized by using the trained object recognition algorithm model, so as to recognize the layout of the room.

In some embodiments, the region division may also be based on detection results of the plurality of integrated sensors. For integrated sensors in the same area, the detection results may be the same or similar. For example, temperature probes are included in integrated sensors; the temperature in the same room may vary. In this way, the temperature detection results of the integrated sensors can also be used to perform or assist in area division. For example, the integrated sensors with the same or similar detection results can be divided into a group to obtain the layout of the room.

Similarly, the original house layout or the layout of the non-removable parts of the house can also assist in determining the grouping of integrated sensors to obtain a new room layout.

As understood by those skilled in the art, the above area division methods can be used independently or in combination, so as to obtain a more accurate room layout. Of course, other area division methods in the prior art, independently or in combination with the above area division methods, can also be applied here.

Since the arrangement of integrated sensors is generally sparse, a relatively rough room layout can be obtained. In order to solve the problem that the integrated sensor is sparse and cannot accurately reflect the situation in the room, in some embodiments, the attribute information of the integrated sensor is added, so that the data center can obtain the local characteristics of the location of the integrated sensor. Integrated sensors include location attribute information, which can be part of the identity ID, or as a separate field. When registering to the data center or sending detection results, the data center obtains the location attribute information of the integrated sensor. The location attribute information reflects the characteristics of the indoor space near the integrated sensor. The location attribute information includes a type field or a type field and a quantity field. The type field can indicate that its location is convex, concave, arc surface, column and other features. The quantity field can represent the convex or concave distance, the radius of the arc surface, the radian of the column, etc. More accurate local features in the room can be obtained through the location attribute information. In some embodiments, the location attribute information may also include the functional area described in the location where the integrated sensor is located. For example: if the integrated sensor is located in a special place such as a bathroom or a kitchen, the location attribute information of the integrated sensor will indicate the type of functional area. In some embodiments, the location attribute information may also include the location of the integrated sensor or indoor facilities around it. For example: the vicinity of the integrated sensor location includes partition walls, windows, doors, etc., and the location attribute information will indicate the type and rough location of the indoor facility. All these information are beneficial to the establishment of the indoor space model.

In step 1030, based on the position information of the plurality of integrated sensors, the size information of each partition is obtained. After obtaining the partition information of the indoor space, that is, the indoor room layout, size information of each partition, such as the size of each room, can be further obtained. After obtaining the dimensions of the room, a model of the interior space was established. In this way, even if the indoor room layout changes, the new room layout can be easily obtained by using multiple integrated sensors arranged indoors, thereby realizing automatic updating. In some embodiments, such an automatic update capability is very useful for a future house where the room layout can change at any time according to the wishes of the user. Furthermore, by using indoor space modeling, the indoor environment can be adjusted more precisely, so as to achieve a more comfortable living experience.

In some embodiments, shape matching is first performed on the partitions. If the partition has already undergone shape matching, the previously adapted shape can be used. If the partition has not been subjected to shape matching, the shape of the partition is first determined through shape matching. After the shapes are matched, determine the dimensions of the matching shapes. This size is the size of the partition. If the location attribute information of the integrated sensor exists, the matching shape and size can be adjusted by using the location attribute information of the integrated sensor. In some embodiments, the size of a partition may be determined according to the location of the integrated sensors located at the edge of the partition within the same partition. Likewise, the original layout of the house or the layout of the non-removable parts of the house can also assist in determining the size of the partition. After determining the dimensions of the partitions, a model of the interior space was established.

Indoor space environment perception

The so-called indoor space perception refers to the accurate detection of one or more parameters of the indoor space environment. Existing indoor environment detection often uses the detection result of a sensor at a certain point to represent the environmental parameters of the entire space. However, such detection results are inaccurate, and cannot reflect the complex environmental changes of the entire space, and are not conducive to achieving more precise environmental control. In some embodiments of the present invention, based on the sensor network and with the help of space modeling, more accurate perception of the indoor space environment can be realized.

Fig. 11 is a method for sensing an indoor space environment according to an embodiment of the present invention. As shown in the figure, the method for sensing an indoor space environment includes the following steps: at step 1110, receiving a plurality of environmental parameters of the locations where the plurality of integrated sensors are located from a plurality of integrated sensors. As mentioned earlier, a sensor network in an indoor space is capable of sending detected environmental parameters to data center sensors from multiple locations in the indoor space. In the data center, the aggregation of these detection results can understand the environmental parameters of multiple locations in the indoor space.

At step 1120, indoor space modeling information is obtained using at least in part the location information of the plurality of integrated sensors. In some embodiments, the aforementioned method for modeling indoor space using an integrated sensor network can be applied here to obtain indoor space information. In some embodiments, other methods may also be used to obtain the indoor space model. The invention is not limited here. The locations of the plurality of integrated sensors are utilized at least in part to modify or validate the indoor space model to obtain indoor space information. For example, if the existing indoor space model cannot match the integrated sensor, which may affect the subsequent environment assignment, the indoor space model can be corrected according to the position of the integrated sensor.

In step 1130, indoor environment distribution information is obtained based at least in part on the plurality of environmental parameters of the plurality of integrated sensors and the indoor space modeling information. The indoor space information reflects the indoor space conditions, while the detection results of multiple integrated sensors reflect the environmental parameters of multiple discrete points in the indoor space. In this step, the environmental parameters of the entire indoor space are established by using the environmental parameters of these discrete points, so as to realize the perception of the environment.

In some embodiments, obtaining the indoor environment information may include the following steps: In step 1131, the indoor space is divided into multiple subspaces based on the indoor space information. There are many ways to divide the subspace. For example, fixed length, width and height; fixed volume, etc. At step 1132 , assign values to at least some of the subspaces' environmental parameters using the plurality of environmental parameters from the plurality of integrated sensors. If a certain subspace includes an integrated sensor or is adjacent to an integrated sensor, the data center uses the measurement value of the integrated sensor to assign values to the environmental parameters of the subspace. In this way, the environmental parameters of some subspaces are assigned; while the environmental parameters of some subspaces have not been assigned.

In step 1133, the data center assigns values to the remaining environmental parameters that have not been assigned to subspaces, so as to realize the environmental perception of the entire indoor space. There are various ways to assign values to these subspaces. In some embodiments, the environmental parameters of these subspaces are assigned values by interpolation. For example, if there are one or more subspaces between two assigned subspaces, the environment parameters of these spaced subspaces can be assigned values by interpolation.

In some embodiments, the field distribution of the environmental parameters of the indoor space may be estimated based on the assigned environmental parameters of the multiple subspaces; then, based on the field distribution of the indoor space, values may be assigned for some of the environmental parameters of the subspaces. Taking the temperature field as an example, if there is a heat source in the indoor space, a heat flow field will appear around the heat source. According to the temperature of the heat source, the air volume, and the size of the room, the shape of the heat flow field can be roughly estimated, thereby estimating the flow field distribution of the temperature. According to the estimated temperature flow field distribution and the assigned subspace temperature, the temperature of some subspaces can be assigned to make the temperature flow field distribution of the whole room consistent with the estimated temperature flow field distribution. In this way, the assignment of environmental parameters to some subspaces can be realized. Based on the estimated temperature flow field, the interpolation method or further field analysis method can be used to assign values to other subspaces, so as to obtain the temperature field of the entire indoor space. For another example, regarding the electromagnetic signal strength, according to the position of the signal source and the attenuation law of the electromagnetic signal in space, the distribution of the electromagnetic signal strength field can be roughly predicted. Combined with the detection results of the electromagnetic signal strength of multiple integrated sensors in the room, the assignment of the electromagnetic signal strength of some subspaces in the room can be realized. Based on the estimated electromagnetic signal intensity field, the interpolation method can be used to assign values to other subspaces, so as to obtain the electromagnetic intensity distribution of the entire indoor space.

In some embodiments, the data center can also assign values to the environmental parameters of at least part of the subspaces according to the location attribute information of the multiple integrated sensors. As mentioned earlier, integrated sensors may include location attribute information representing spatial characteristics of the integrated sensor or a location in its vicinity. For example, if the location of the integrated sensor is concave, then its environmental parameters may be relatively stable, and all subspaces of the concave area can be assigned the same value. For another example, if the integrated sensor is located near the water source of the bathroom, the humidity assignment in the surrounding subspace will increase accordingly.

Those skilled in the art should understand that the above methods can be used independently or in combination to more accurately assign values to the environment parameters of each subspace. Of course, there are other ways to assign values to environment parameters of subspaces that have not yet been assigned. These methods can be used independently or in combination with the above methods to more accurately perceive the environment of the indoor space.

In step 1140, the data center may estimate changes in the environmental parameters of each subspace, and update the environmental parameters of each subspace according to the estimated changes. These subspaces include both subspaces with integrated sensors or adjacent to integrated sensors, and subspaces that are not in direct contact with any integrated sensors.

In some embodiments, the data center estimates changes in environmental parameters of each subspace in the indoor space according to changes in the state of the facilities in the indoor space. For example, if a door or window in a room is opened to allow air exchange with the outside world, the data center can expect changes in temperature and humidity in the room. Based on the temperature and humidity outside and when doors and windows are open, the data center can predict changes in the temperature and humidity of the indoor space. According to the estimated results, the data center can reassign the temperature and humidity of multiple subspaces in the indoor space.

In some embodiments, the data center estimates changes in environmental parameters of other multiple subspaces in the indoor space according to changes in multiple environmental parameters from multiple integrated sensors after the state of the facilities in the indoor space changes. Although such an update will be slightly delayed in speed, it can ensure the accuracy of environmental change perception.

In some embodiments, the data center estimates changes in environmental parameters of each sub-space in the indoor space in response to the changing state of the outdoor environment. If there is a large change in the outdoor environment, such as a significant drop in temperature, a corresponding change in the indoor temperature can be expected without opening the doors or windows. Data centers can predict changes in temperature and humidity in indoor spaces. According to the estimated results, the data center can reassign the temperature and humidity of multiple subspaces in the indoor space.

Those skilled in the art should understand that the above methods can be used independently or in combination to update the environment parameter assignments of each subspace more accurately. Of course, there are other ways to assign values to update the environment parameters of each subspace. These methods can be used independently or in combination with the above methods to more accurately perceive the environmental changes of the indoor space.

The following will take a specific room as an example to further introduce the sensor network of this application, indoor space modeling, recognition of commands issued by users, and perception of the environment of the indoor space.

Fig. 12 is a schematic diagram of an indoor model according to an embodiment of the present application. As shown in the figure, a room 1200 includes walls 1210, 1220 and 1230, a ceiling 1240, a floor 1250, and a corner 1260. The layout thereof is similar to that of the embodiment shown in FIG. 9, so details will not be repeated here.

In some embodiments, wall 1210 includes integrated sensors 1211-1215, wall 1220 includes integrated sensors 1221-1225, wall 1230 includes integrated sensors 1231-1235, ceiling 1240 includes integrated sensors 1241-1245, floor 1250 includes integrated sensors 1251-1255 . Wherein, each integrated sensor is located at the center of each wall, ceiling or floor separating rectangle to form a sensor network of the room 1200, and each integrated sensor can detect one or more environmental parameters and/or one or more human body parameters in the room , and upload the test results to the data center.

The identity IDs of all the integrated sensors 1211-1255 have the same identity A, representing room A. Therefore, the room 1200 may be a result obtained after the data center models the indoor space of the house. Of course, the house may also include room B and room C as shown in Figure 8 . The data center obtains the position information of each integrated sensor, and thus obtains the dimension information of the room.

In some embodiments, the data center may regroup the integrated sensors in room A. For example: the integrated sensors 1211-1215 on the wall 1210 are a subgroup; all the integrated sensors on the wall 1220, the wall 1230, the ceiling 1240 and the floor 1250 are each a subgroup. In this way, the relevant information of the facilities in the room can be further obtained. In some embodiments, the data center may receive grouping information of the integrated sensor from the integrated sensor. In some embodiments, when the integrated sensor is installed, the group information of the integrated sensor can be preset (for example: the integrated sensor belongs to the wall 1210 or room A, etc.), through the preset group information of the integrated sensor, the integrated sensor can be Grouping, so that the partition information of the indoor space can be obtained. For example: divided into multiple rooms, or a room divided into different indoor facilities such as walls, ceilings, and floors.

In some embodiments, the data center may also obtain location attribute information of integrated sensors. For example: the location attribute information of the integrated sensors 1222 , 1223 , 1231 and 1234 all show that their locations protrude outward, and the data center can conclude that the room 1200 includes a corner 1260 located between the wall 1220 and the wall 1230 .

In some embodiments, the room includes a corner or the wall is an arc, and the position attribute information may include the arc of the position where the integrated sensor is located. In some embodiments, the location attribute information may also include the functional area described in the location where the integrated sensor is located. For example: integrated sensors are located in special places such as bathrooms and kitchens. Data centers can determine indoor partitions as special functional areas. In some embodiments, the location attribute information may also include indoor facilities around the location where the integrated sensor is located. For example, the vicinity of the integrated sensor location includes partition walls, windows, doors, etc., and the data center can determine the location of these facilities indoors.

Further, after the data center obtains the space model of the room 1200, it may further use the sensor network to sense the space environment in the room 1200. The data center divides the space of the room 1200 into multiple subspaces, so as to estimate the environment of other subspaces of the room by detecting environmental parameters of different subspaces according to multiple integrated sensors. As shown in the figure, the space of room 1000 is equally divided into 27 subspaces room01-room27. As understood by those skilled in the art, the above division is only exemplary, and the space of the room 1200 can also be divided into other numbers of subspaces.

The data center receives the environmental parameters of its location from each integrated sensor, and can obtain indoor environmental information based on the indoor space information obtained from the integrated sensor location information. In some embodiments, the indoor space information obtained according to the position information of the integrated sensor includes at least the size of the indoor space.

The data center uses the environmental parameters detected by the integrated sensor to assign values to the environmental parameters of at least part of the subspaces. For example: the subspaces that are in direct contact with the integrated sensor can be assigned values according to the detection results of the integrated sensor. As shown, subspaces close to walls, ceilings, or floors can be assigned values based on the detection results of the integrated sensors in contact with them.

In some embodiments, the environmental parameters in other subspaces that are not in contact with the integrated sensor can be determined according to the interpolation method. Taking the temperature field as an example, the integrated sensor in the eleventh subspace room11 detects a temperature of 10.0°C, and the integrated sensor in the seventeenth subspace room17 detects a temperature of 11.0°C, then the temperature in the fourteenth subspace room14 can be considered as is 10.5°C. Or, taking the humidity field as an example, the integrated sensor in the fifth subspace room5 detects a humidity of 50%, and the integrated sensor in the twenty-third subspace room23 detects a humidity of 48%, then it can be considered that the humidity in the fourteenth subspace room14 is The humidity is 49%.

In some embodiments, the data center can estimate the field distribution of the indoor space according to the subspaces whose environmental parameters are at least partially determined, and can determine the environmental parameters for the subspaces whose other environmental parameters are not determined through the flow field distribution of the indoor space.

In some implementations, the location attribute of the indoor space or the indoor space facility or its state may affect the flow field of the indoor space. For example: screens, corners, etc. may have an impact on the temperature field of the indoor space, or the state of indoor facilities such as doors and windows may also have an impact on the temperature field of the indoor space. In some embodiments, the data center receives location attribute information of the location of the integrated sensors from multiple integrated sensors, and determines environmental parameters for the environment of the affected subspace according to the location attribute information. The factors that affect the indoor environment will be introduced in detail below.

13A and 13B are schematic diagrams of indoor environment changes according to an embodiment of the present application. Through Figures 13A and 13B, we can not only understand the distribution of the flow field, but also understand the impact of indoor environment changes.

As shown, room 1300 includes walls 1310 , 1320 , and 1330 , ceiling 1340 , and floor 1350 . Its layout is the same as that of the above-mentioned embodiment, so it will not be repeated here. Wherein, the room 1300 also includes integrated sensors 1301-1308, which are arranged in every corner of the room 1300. For example: the corner where wall 1310 meets wall 1320 and ceiling 1340 , or the corner where wall 1320 meets wall 1330 and floor 1350 . The room 1300 may further include integrated sensors 1311, 1321, 1331, 1341, and 1351, which are disposed at the centers of the walls, ceiling, and floor, respectively. Among them, the integrated sensors 1301-1308, 1311, 1321, 1331, 1341, and 1351 together form the sensor network of the room 1300, and can detect the room 1300, and upload the detection results to the data center, so that the spatial model of the room 1300 can be established For determining the environmental parameters in the space, reference may be made to the embodiments in FIG. 9 , FIG. 10 and FIG. 11 , and details are not repeated here.

In some embodiments, the data center can determine the environmental parameters of the indoor space or some subspaces according to the location attribute information of the integrated sensor. In some embodiments, the walls, ceiling or floor of the room 1300 include special shapes, which may affect the environment of some subspaces in the room 1300 . In some embodiments, the room 1300 includes a special area, which may affect the environmental parameters of some subspaces. For example, if the room 1300 includes a bathroom, the humidity in some of the subspaces may be relatively high; or if the room 1300 includes a kitchen, then the electromagnetic intensity in some of the subspaces may be relatively high. In some embodiments, the room 1300 includes some indoor facilities, which may affect the environment in some subspaces. For example: doors and windows may affect the temperature in some subspaces.

In some embodiments, the wall 1310 may include a door 1313 , and the wall 1330 may include a window 1332 , wherein the door 1313 and the window 1332 may affect the environment in the room 1300 . Wherein, the data center may estimate the space of the room 1300 or the environmental parameters of each subspace according to the state changes of the door 1313 and/or the window 1332 . For example: the door 1313 and the window 1332 change from the closed state to the open state, and the data center can lower or raise a certain value (such as: 2 ℃, 3 ℃, 5℃, etc.).

In some embodiments, when the state of the door 1313 and/or the window 1332 changes, the data center can also estimate environmental parameters of other subspaces of the indoor space according to changes in multiple environmental parameters of multiple integrated sensors. For example, if the integrated sensor detects that the temperature of the subspace near the window 1332 is 25°C, and the temperature of the subspace near the door 1313 is 20°C, then it can be predicted that the temperature of other subspaces between the window 1332 and the door 1313 is 22.5°C.

In some embodiments, the data center may also estimate the environmental parameters or changes of the environmental parameters of the indoor space or each subspace according to the outdoor environment or the change state of the outdoor environment. In some embodiments, the outdoors are in different seasons, which will affect the indoor environment (such as temperature, humidity, etc.). For example, if it is hot outside in summer and cold outside in winter, it will have a greater impact on the temperature in the room; or if there is more rain in summer and drier in winter, it will have a greater impact on the humidity in the room. In some embodiments, the outdoor environment also has an impact on the indoor environment at different times of the day. For example: the temperature is lower in the morning and evening, and the temperature is higher at noon, which will have a greater impact on the indoor temperature. In some embodiments, large changes in the outdoor environment will have an impact on the indoor environment. For example: sudden precipitation will have a great impact on the indoor humidity. In some embodiments, the data center can also receive the local weather forecast of the room 1300, and the outdoor environment can be determined through the weather forecast. In some embodiments, the exterior of room 1300 may also include integrated sensors for detecting the environment outside.

Adjustment of the indoor environment

The so-called adjustment of the indoor environment refers to adjusting the indoor environment by starting the indoor electrical appliances. The regulation of indoor environment includes passive regulation and active regulation. Passive adjustment is the usual way: when the indoor environment changes or the user's instructions are received, the indoor electrical appliances are activated to adjust the indoor environment. Active adjustment is a unique adjustment method: actively change the indoor environment according to the possible change trend of the indoor environment or the situation of the user, so as to make the living environment more friendly and more comfortable to live in.

Fig. 14 is a flowchart of a method for adjusting an indoor environment according to an embodiment of the present invention. As shown in the figure, the method for adjusting the indoor environment in this embodiment includes the following steps: at step 1410, receiving multiple environmental parameters of the locations where the multiple integrated sensors are located from multiple integrated sensors. As mentioned earlier, a sensor network in an indoor space is capable of sending detected environmental parameters to data center sensors from multiple locations in the indoor space. In the data center, the aggregation of these detection results can understand the environmental parameters of multiple locations in the indoor space.

At step 1420, indoor environment information is obtained based at least in part on the plurality of environmental parameters of the plurality of integrated sensors and the indoor space information. As mentioned above, through the sensor network, the perception of the indoor space environment can be realized, so as to obtain more accurate indoor environment information. Those skilled in the art should understand that the present invention is not limited to the methods for spatial environment perception described above. Other ways of obtaining accurate spatial environment information can also be applied here.

In step 1430, the environment adjusting device is activated to adjust the indoor environment to obtain the desired indoor environment. In the indoor space, one or more environmental conditioning devices are arranged. For different environmental parameters, different environmental adjustment devices can be used. These environmental conditioning devices include but are not limited to: air conditioners, fans, electric heaters, heaters, humidifiers, signal amplifiers and other electrical appliances or facilities of different types and quantities. By starting these electrical appliances or facilities, the adjustment of indoor environment parameters can be realized. In some embodiments, the quantity and distribution of the indoor environment regulating devices are arranged so that the data center can understand its influence on the changes of the environment parameters of each subspace, so as to realize the precise adjustment of the environment. Taking temperature as an example, the room includes multiple air conditioners or air conditioner outlets and heaters distributed on each wall, so that precise adjustment of the temperature of each subspace can be achieved.

For passive adjustment, compared with the prior art, the method of the present invention can perform more accurate environmental adjustment. For example, the comfortable temperature of the indoor environment is 21±2°C. In order to ensure the comfort of living, the temperature of all occupant-related subspaces is set at 21±2°C, and the data center maintains the temperature of these subspaces. Through the perception of the indoor space environment, the data center found that the temperature of the subspace near the door and window in the indoor space was 23°C, while the temperature of the subspace of the bed located far away from the door and window in the indoor space reached 25°C. The data center activates the air conditioner near the bed or the air outlet of the air conditioner to reduce the temperature in the subspace of the bed and control the temperature around the bed within a comfortable range for the human body. From such an example, it can be seen that through spatial environment perception, more refined environmental parameters of the spatial environment can be obtained, so that more refined environmental parameter adjustment can be realized.

For another example, the data center receives commands from multiple people in the room through integrated sensors, and can adjust the environmental parameters of the subspaces in which multiple people live according to these commands, so that multiple people in the room can enjoy a comfortable environment. indoor environment. For example, there are two men and women indoors: A and B, where A likes the temperature to be lower; and B likes the temperature to be higher. When both A and B are in the same room, A and B may issue different commands. A's command is to lower the temperature to 16°C; and B's command is to increase the temperature to 25°C. In the prior art, such an order cannot be executed. In the case of the present invention, if there is a certain interval between A and B and they are in different subspaces; then, the data center can meet such requirements by finely adjusting the temperature of the respective subspaces of A and B. The data center can reduce the temperature of the subspace where A is located through the air conditioner; and increase the temperature of the subspace where B is located through the heater. In this way, both A and B can enjoy their own comfortable environment, thereby improving the comfort of the entire indoor living environment.

A characteristic of the indoor environment adjustment of the present invention is active adjustment, that is, the environment can be actively adjusted without changing the environment or receiving an order from the user, thereby further improving living comfort. A few examples are given below to further illustrate.

In some embodiments, the data center may estimate changes in environmental parameters of each subspace in the indoor space according to state changes of indoor facilities, and actively adjust the indoor environment according to the estimated changes in environmental parameters of each subspace. For example, if a door or window in a room switches from closed to open, the temperature in the room may not change immediately. After the data center detects the state change of the door or window of the indoor facility, it can predict whether the indoor temperature will rise or fall according to the outdoor temperature and wind speed. Further, the data center can activate the environment regulating device to adjust the temperature of each subspace, so as to maintain the indoor environment within a comfortable range. In other words, while opening the door or window for ventilation, the indoor temperature does not change.

In some embodiments, the indoor facility that has undergone a state change may be an environmental conditioning device. When the environment adjustment device is activated, the data center can estimate the environmental parameters of each sub-space in the room. For example: take Figure 13 as an example, the initial temperature of each subspace in the room is 20°C, and the air conditioner at wall 1310 is turned on for cooling. The data center estimates that the temperature of the subspace near wall 1310 can be 15°C based on the power of the air conditioner and the wind direction. °C, the temperature of the subspace near the wall 1330 may be 18 °C, and the temperature of the subspace in between may be 16 °C. Further, the data center can automatically activate the heating device of the subspace at 1310, and increase the temperature of the subspace at 1310, so as to keep the temperature of each subspace at a comfortable environment.

If there are one or more people in the room, the data center can actively adjust the environmental parameters of the subspace around people according to whether there are people, their identities and activities, etc., making the living environment more humane.

In some embodiments, multiple integrated sensors within room 1300 may detect one or more persons moving within the room. The data center can understand the current activities of people in the room, and understand the number and location of people. The data center can actively adjust the illuminance of each subspace that people can see, so that the human eye can comfortably see the indoor situation clearly.

In some embodiments, multiple integrated sensors in the room 1300 can detect one or more human body parameters of indoor activities, and the data center can adjust the environment of the subspace around the indoor active people according to the detection results. Taking temperature as an example, if the data center finds that one of the many people who are active indoors has a high body temperature (whether it is due to exercise or eating hot food), the data center can turn on the air conditioner to reduce the temperature of the subspace where the person with elevated body temperature is located. temperature, making it feel comfortable; while keeping the temperature of the subspace around other people constant.

The data center can identify the identity of a person, and actively adjust the environment of the subspace around the indoor active person according to the identity. For example, if the integrated sensor detects that user A is near the walls 1310 and 1320, the data center can adjust the environment of the surrounding subspace according to the habit of user A, and adjust the temperature to the range that user A is used to.

In some embodiments, integrated sensors identify the activities of indoor active people, and the data center can actively adjust the environmental parameters of the subspace near the indoor active people according to the identification results. For example, when it is recognized that someone is sleeping in the room (for example, lying on the bed and inactive for more than a predetermined time), the temperature of the surrounding subspace is appropriately increased. For another example, when it is recognized that someone is moving indoors (for example: running, fitness, etc.), the oxygen content in the surrounding subspace is appropriately increased.

Another feature of the present invention is that, through the precise adjustment of the indoor environment, energy saving and environmental protection can be realized without reducing the comfort of the living environment, so that it is more in line with the future development direction of the home.

In some embodiments, the data center turns on or turns off the environmental parameter adjustment device in response to the detection result of one or more people active in the room. For example, when the data center recognizes that there are one or more people in the room, the signal amplifiers in the surrounding subspaces are activated, so that one or more people can enjoy wireless signals. If there is no one in the room or for a subspace with no people around, the data center will turn off the signal amplifier to save energy. The same can be said for temperature. When the data center recognizes that the people in the room are in a sleeping state, in addition to appropriately increasing the temperature of the subspace around the person to ensure the comfort of the living environment, the data center can turn off the ambient temperature adjustment devices such as air conditioners or heaters for the rest of the subspaces. Thereby saving energy. The invention can realize the fine adjustment of the indoor environment, thereby saving energy to the greatest extent and realizing green home furnishing.

In some embodiments, even when adjusting the indoor environment, before the data center activates the environmental adjustment device, according to the desired indoor environment, the multiple environmental adjustment devices that need to be activated for adjusting the environment of each subspace in the room and their corresponding Power is estimated.

In some embodiments, the data center can start the environment adjustment device in a way that estimates the total energy consumed by the multiple environment adjustment devices that need to be activated to adjust the indoor environment is the least, so as to help save energy. For example: when the location where user A is located needs to cool down, either the cooling device on the wall 1310 or the cooling device on the wall 1320 can be used, or both can be used at the same time. After comparing the energy consumption, the data center chooses to control the cooling device of the wall 1310 to cool down the subspace around it, and does not activate the cooling device of the wall 1320 . In this way, the temperature at the location where the user A is located can be lowered to the required temperature range with the minimum energy consumption.

In some embodiments, comfort is also a consideration. The data center can also estimate that multiple environmental adjustment devices need to be activated to adjust the indoor environment, and start the environmental adjustment devices in the fastest way to adjust the adjustment speed, so as to improve user experience. For example: when the location of user B needs to be heated, the heating device near the wall 1330 and the ground 1350 is controlled to heat the subspace around it at the same time, so as to raise the temperature of the location of B to the desired temperature as quickly as possible. temperature range.

In the above part of this paper, the technical solutions of the present invention are described in the form of multiple embodiments by integrating sensors, sensor networks, indoor space modeling, indoor space environment perception and indoor space environment adjustment. Those skilled in the art should understand that there are many possible changes in the technical solution of the present invention, and these changes are still within the scope of the present invention.

The technical solutions of the present invention are further described below through two variations of the technical solutions of the present invention.

Space Modeling Using Modeling Elements Instead of Integrated Sensors

In this embodiment, the indoor space modeling element has a positioning function, but may not include a sensor or have a detection function. Multiple sensors can be positioned relative to multiple modeled elements for less cost and more flexibility.

Fig. 15 is a schematic structural diagram of an indoor space modeling element according to an embodiment of the present application. As shown in the figure, the indoor space modeling component 1500 includes a processor 1510 , a positioning component 1520 and a communication module 1530 ; wherein, the processor 1510 is electrically connected to the positioning component 1520 and the communication module 1530 . The positioning component 1520 is used to determine the position of the modeling component. In some embodiments, the positioning component can realize indoor spatial positioning through UWB, Wi-Fi, RFID, infrared, or ultrasonic waves. In some embodiments, the communication module 1530 is used to communicate with the home data center or the data center of the room sub-center.

In some embodiments, the modeling component 1500 may further include a memory 1540 , which is electrically connected to the processor 1510 and may be used to store data of the modeling component 1500 . In some embodiments, the memory 1540 and the processor may be integrated on the same chip.

In some embodiments, the modeling component can also include an input display device 1560, which is connected to the processor and can be used to input information to the processor and display related information. For example: identity information and/or location information of modeled elements may be input to the processor. In some embodiments, the input display device may be a touch display screen.

Fig. 16 is a schematic diagram of an indoor space modeling process based on modeling elements according to an embodiment of the present invention. As shown in the figure, at step 1610, the data center acquires location information of each modeling element from a plurality of modeling elements. As mentioned before, the positioning components of the modeling components can realize the positioning of the indoor space. The data center can obtain the location of the modeling element by receiving the spatial positioning information of its positioning element from the modeling element.

To facilitate positioning, in some embodiments, the location information of the modeling element includes height and/or horizontal relative location information. In some embodiments, the horizontal relative position may be relative to an anchor point within the room. Determining height is sometimes difficult for spatial orientation. By arranging the modeling components at one or more fixed heights and only using the positioning components to obtain horizontal relative position information, the spatial positioning can be simplified and the result is more accurate. In some embodiments, the positioning method relative to the positioning point in the room used by the integrated sensor in the foregoing embodiments may also be applied here, which will not be repeated here.

In step 1620, the data center can obtain partition information of the indoor space according to the grouping of multiple modeling elements. In some embodiments, the data center may receive grouping information for a plurality of modeling elements from the modeling element. The grouping of modeling components can be realized by using these grouping information, and then the division of indoor space can be obtained. Similar to the integrated sensor embodiments, in some embodiments multiple modeling element groupings may be matched by shape. For example: Group multiple modeling components that form a rectangular shape into a group. In some embodiments, grouping of modeled elements may be achieved by a clustering algorithm.

In step 1630, the data center obtains size information of indoor space partitions according to the position information of multiple modeling components obtained from multiple modeling components, and forms an indoor space model. In some embodiments, the data center may also receive location attribute information from multiple modeling elements, so as to obtain feature information of indoor space partitions. In some embodiments, the location attribute information includes but not limited to: the radian of the location of the modeling element, the convexity of the location of the modeling element, the functional area to which the location of the modeling element belongs, and the indoor facilities around the location of the modeling element .

At step 1640, a plurality of locations of a plurality of sensors in the room are calibrated in the room space model. For spatial environment perception and spatial environment control, it is necessary to know the position of the sensor in the spatial model, excluding positioning elements.

In some embodiments, the multiple sensors also include a positioning element, for example, realizing indoor space positioning through UWB, Wi-Fi, RFID, infrared rays, or ultrasonic waves. In this step, position calibration of the sensor can be realized according to the positions received from multiple sensors.

In some embodiments, multiple sensors do not include positioning elements to reduce cost. Multiple sensors use their positions relative to the modeling elements to achieve positional calibration in the spatial model. In some embodiments, the relative positions of the sensors and modeling elements are fixed. For example, a simple rule is to place a sensor at the midpoint between two modeled elements, and to name each sensor to indicate that it is between those two modeled elements. For example, sensor A12 represents the sensor at the midpoint between modeling elements No. 1 and No. 2 in room A. B67 is the sensor at the midpoint between modeling elements 6 and 7 in room B. In this way, the data center can know the position of the sensor relative to the modeling element according to the name of the sensor, so that its position can be marked on the space model.

In some more complex examples, the multiple sensors include RFID tags. A number of modeling elements also include RFID tags. The cost of RFID tags is low, which is conducive to large-scale use and promotion. There are multiple RFID scanners arranged indoors. By scanning the sensor, the return time and signal strength of the RFID tags at different locations can be obtained. By performing calibration with the return time and signal strength of the RFID of multiple modeling components, it is possible to know the positions of multiple sensors relative to the modeling component. This technology has a range of several meters to tens of meters, which can meet the needs of indoor positioning. The information of centimeter-level positioning accuracy can be obtained within a few milliseconds through the RFID scanner, and the transmission range is large and the cost is low. This method is also applicable to infrared, Wi-Fi, ultrasonic and other methods.

Therefore, by calibrating the positions of multiple sensors on the indoor space model, the combination of the sensor network and the space model can be realized, so that the subsequent indoor environment perception and indoor environment control can be realized, and the indoor environment can be detected more precisely, and Change the indoor environment to provide a better living environment.

In some embodiments, the modeling element may also have a detection function. In this way, modeling elements can also become sensors. However, this type of sensor of the modeling element will be quite special, and it can realize indoor positioning through its own positioning element without the help of other sensors. Although another type of sensor also has a positioning element, it cannot complete positioning by itself and must rely on other sensors to achieve positioning.

Spatial modeling with indoor facilities

In this embodiment, indoor facilities, such as walls, kicks, floors or ceilings, have positioning functions, and also include multiple sensors, which have detection functions; thus sensor networks and space modeling can be directly realized, which is suitable for industrial production and low cost. lower.

Figure 17A-Figure 17D is a schematic structural view of an indoor facility according to an embodiment of the present application; wherein the indoor facility shown in Figure 17A is a movable wall; the indoor facility shown in Figure 17B is a kick; the indoor facility shown in Figure 17C is the floor; and the indoor facility shown in FIG. 17D is the ceiling. As shown in the figure, these facilities all include a processor 1710 , a positioning component 1720 and a communication module 1730 ; wherein, the processor 1710 is electrically connected to the positioning component 1720 and the communication module 1730 . The positioning component 1720 is used to determine the position of the modeling component. In some embodiments, the positioning component can realize indoor space positioning through UWB, Wi-Fi, RFID, infrared rays, or ultrasonic waves. In some embodiments, the communication module 1730 is used to communicate with the home data center or the data center of the room sub-center.

Fig. 18 is a schematic flow chart of indoor space modeling based on indoor facilities according to an embodiment of the present invention. As shown in the figure, at step 1810, the data center acquires location information of each indoor facility from a plurality of indoor facilities. As mentioned above, one or more positioning elements of a plurality of indoor facilities enable indoor spatial positioning. The data center can obtain the location of the indoor facility by receiving the spatial positioning information of its positioning components from the indoor facility.

To facilitate positioning, in some embodiments, the location information of the indoor facility includes altitude and/or horizontal relative location information. In some embodiments, the horizontal relative position may be relative to an anchor point within the room. Determining height is sometimes difficult for spatial orientation. By arranging indoor facilities at one or more fixed heights and only using positioning elements to obtain horizontal relative position information, spatial positioning can be simplified and the result is more accurate. Due to the small number of positioning components used in indoor facilities, there are high requirements for positioning accuracy. In some embodiments, the positioning element is a high-precision positioning technology such as UWB, infrared, and ultrasonic, providing centimeter-level or higher positioning accuracy.

In step 1820, the data center may obtain partition information of the indoor space according to the location information of the multiple indoor facilities obtained from the multiple indoor facilities. In some embodiments, some indoor facilities are used to divide the indoor space, and the indoor space can be divided into multiple areas directly according to the size and position of the indoor facilities, such as the length or position of the wall or skirting. Each indoor facility is therefore used to divide each zone. Some other indoor settings, such as floors, ceilings and other facilities, are also divided into their own rooms.

In step 1830, the data center obtains size information of indoor space partitions to form an indoor space model. In some embodiments, the data center receives location attribute information according to a plurality of indoor facilities, so as to obtain feature information of indoor space partitions. In some embodiments, the location attribute information includes, but is not limited to: the radian of the location of the indoor facility, the convexity of the location of the indoor facility, the functional area to which the location of the indoor facility belongs, and the indoor facilities around the location of the indoor facility.

At step 1840, a plurality of locations of a plurality of sensors in the room are calibrated in the room space model. For spatial environment perception and spatial environment control, it is necessary to know the position of the sensor in the spatial model, excluding positioning elements.

In some embodiments, multiple sensors do not include positioning elements to reduce cost. Multiple sensors are installed in the indoor facility, and their positions relative to the positioning elements of the indoor facility are fixed, so the position calibration in the space model can be directly realized. For example, the naming of each sensor indicates its position relative to the positioning element of the indoor installation. For example, sensor A12 means sensor number 12 in wall A of the indoor facility. The data center stores a table of the exact location of each sensor in each indoor facility. The data center can understand through the query table that the No. 12 sensor is the sensor located at the upper right 45° of the positioning element in the wall A with a distance of 40cm. Thus, the data center can calibrate the position of the A12 sensor in the indoor space model. For another example, B67 represents the No. 67 sensor in the floor B installed indoors. The data center finds out by looking up the table that the position of sensor No. 67 is at the origin of the positioning element on floor B, and the coordinates are (150, -300) centimeters. Thus, the data center can calibrate the position of the B67 sensor in the indoor space model. In this way, according to the name of the sensor, the data center can know its position relative to the positioning element of the indoor facility, so that its position can be marked on the space model. In this embodiment, the sensor does not need to add any additional positioning elements, and has low cost and good expandability. In some embodiments, the positioning element of the indoor facility may also have a detection function. In this way, the positioning element can also become a sensor and be part of a sensor network.

Therefore, by calibrating the positions of multiple sensors on the indoor space model, the combination of the sensor network and the space model can be realized, so that the subsequent indoor environment perception and indoor environment control can be realized, and the indoor environment can be detected more precisely, and Change the indoor environment to provide a better living environment.

The above-described embodiments are only for illustrating the present invention, rather than limiting the present invention. Those of ordinary skill in the relevant technical field can also make various changes and modifications without departing from the scope of the present invention. Therefore, all Equivalent technical solutions should also belong to the scope of the disclosure of the present invention.

Claims (23)

1. A modeling method for indoor space, comprising: receiving location information from a plurality of integrated sensors for the plurality of integrated sensors; Obtaining zoning information of the indoor space based on the grouping of the plurality of integrated sensors; and Obtaining size information of the partition based on the position information of the plurality of integrated sensors; Wherein, the probe of the integrated sensor includes a channel, and the channel communicates with the inner space of the integrated sensor, and one or more sensors are arranged in the channel and the inner space; the probe includes a probe surface that is in direct contact with the room , including one or more sensors on the surface of the probe, the sensors on the surface of the probe are in direct contact with the indoor environment; Wherein the integrated sensor is configured to detect one or more environmental parameters of the indoor environment and/or one or more anthropometric parameters of people active in the room. 2. The method of claim 1, wherein an environmental or human body parameter is collectively determined from a plurality of detections from one or more of a plurality of integrated sensors. 3. The method of claim 1, wherein the integrated sensor is configured to detect commands from a person active in the room. 4. The method of claim 1, wherein the location information includes altitude. 5. The method of claim 1, wherein the location information includes horizontal relative location information. 6. The method of claim 1, further comprising receiving grouping information for the plurality of integrated sensors from the plurality of integrated sensors. 7. The method according to claim 1, further comprising: grouping the plurality of integrated sensors, and obtaining partition information of the indoor space based on the grouping information obtained after grouping. 8. The method of claim 7, wherein the grouping of the plurality of integrated sensors is based at least in part on shape matching. 9. The method of claim 7, wherein the grouping of the plurality of integrated sensors is based at least in part on zoning. 10. The method of claim 7, wherein the zone division is based on detection results of the plurality of integrated sensors. 11. The method of claim 1, further comprising receiving location attribute information from the plurality of integrated sensors. 12. The method of claim 11, further comprising obtaining characteristic information of the partition of the indoor space based at least in part on the location attribute information of the plurality of integrated sensors. 13. The method according to claim 11, wherein the location attribute information includes an arc of the location. 14. The method according to claim 11, wherein the location attribute information includes the convexity and concaveness of the location. 15. The method according to claim 11, wherein the location attribute information includes the functional area to which the location belongs. 16. The method of claim 11, wherein the location attribute information includes indoor facilities around the location. 17. A system for modeling an interior space, comprising: a plurality of integrated sensors distributed throughout the interior space; and a data center in communication with the plurality of integrated sensors; Wherein, the data center is configured to obtain partition information of the indoor space based on the grouping of the plurality of integrated sensors; and obtain size information of the partition based on the location information of the plurality of integrated sensors; Wherein, the probe of the integrated sensor includes a channel, and the channel communicates with the inner space of the integrated sensor, and one or more sensors are arranged in the channel and the inner space; the probe includes a probe surface that is in direct contact with the room , including one or more sensors on the surface of the probe, the sensors on the surface of the probe are in direct contact with the indoor environment; Wherein the integrated sensor is configured to detect one or more environmental parameters of the indoor environment and/or one or more anthropometric parameters of people active in the room. 18. The system of claim 17, wherein the location information includes altitude. 19. The system of claim 17, wherein the location information includes horizontal relative location information. 20. The system of claim 17, wherein the data center is configured to receive group information from the plurality of integrated sensors for the plurality of integrated sensors. 21. The system of claim 17, wherein the data center is configured to group the plurality of integrated sensors, and obtain zoning information of the indoor space based on the grouped information obtained after grouping. 22. The system of claim 17, wherein the data center is configured to receive location attribute information from the plurality of integrated sensors. 23. The system of claim 22, wherein the data center is configured to obtain characteristic information of the partition of the indoor space based at least in part on the location attribute information of the plurality of integrated sensors.

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