CN114158166B - Control method and device of lighting equipment - Google Patents

Abstract

The invention discloses a control method and device for lighting equipment, and relates to the technical field of control. The method includes: firstly, acquiring network data of users in the lighting area of the lighting device. Then, according to the network data of the user, the user type of the user is determined. Finally, when the number of target users in the lighting area of the lighting device is greater than the first number threshold, the state of the lighting device is adjusted according to the state parameter of the lighting device corresponding to the user type of the target user. Wherein, the network data includes one or more of time period, age, gender, occupation, user location and traffic information. The target user is a user of the same user type. The state parameter of the lighting device includes a brightness parameter of the lighting device and a switching parameter of the lighting device.

Description

A control method and device for lighting equipment

technical field

The present invention relates to the technical field of control, in particular to a method and device for controlling lighting equipment.

Background technique

As an essential public infrastructure in urban construction, lighting equipment directly reflects the image of the city and the level of urban modernization. Lighting equipment not only illuminates the city, reduces urban night traffic accidents, and protects the safety of citizens, but also plays a very important role in beautifying the city.

At present, the switch of the lighting equipment is usually controlled according to the period, that is, the lighting equipment is turned on during a fixed period of time every day, and the lighting equipment is turned off during the rest of the period. In this control mode, during the turn-on period of the lighting device, even if there is no user within the lighting range of the lighting device, the lighting device will still be turned on until the end of the turn-on period. Therefore, controlling the lighting equipment using the existing lighting equipment control method will lead to low lighting efficiency of the lighting equipment, which will easily cause waste of resources.

Contents of the invention

The invention provides a control method and device for lighting equipment, which are used to solve the problem of low lighting efficiency of the existing lighting equipment.

To achieve the above object, the present invention adopts the following technical solutions:

In a first aspect, the present invention provides a method for controlling lighting equipment, the method comprising:

First, network data of users within the lighting area of the lighting device are acquired. Then, according to the network data of the user, the user type of the user is determined. Finally, when the number of target users in the lighting area of the lighting device is greater than the first number threshold, the state of the lighting device is adjusted according to the state parameter of the lighting device corresponding to the user type of the target user. Wherein, the network data includes one or more of time period, age, gender, occupation, user location and traffic information. The target user is a user of the same user type. The state parameter of the lighting device includes a brightness parameter of the lighting device and a switching parameter of the lighting device.

It can be seen that the present invention adjusts the state of the lighting device according to the state parameter of the lighting device corresponding to the user type of the target user when the number of target users in the lighting area of the lighting device is greater than the first number threshold. Therefore, the present invention does not turn on the lighting device when there is no user in the lighting area, thereby improving the lighting efficiency of the lighting device. In addition, the present invention adopts different lighting luminances for different user types, further improving the lighting efficiency of the lighting equipment.

In a second aspect, the present invention provides a control device for lighting equipment, which includes: a first acquisition unit, a first determination unit, and a control unit. The first acquisition unit is configured to acquire network data of users in the lighting area of the lighting device, where the network data includes one or more of time period, age, gender, occupation, user location and traffic information. The first determining unit is configured to determine the user type of the user according to the network data of the user. The control unit is configured to adjust the state of the lighting device according to the state parameter of the lighting device corresponding to the user type of the target user when the number of target users in the lighting area of the lighting device is greater than the first number threshold, and the target users are the same For a user of the user type, the state parameters of the lighting device include a brightness parameter of the lighting device and an on/off parameter of the lighting device.

In a third aspect, the present invention provides a computer-readable storage medium storing one or more programs, one or more programs include instructions, and when the instructions are executed by the control device of the lighting device, the control device of the lighting device executes the following steps: A control method for lighting equipment described in one aspect.

In a fourth aspect, the present invention provides a computer program product containing instructions. When the instructions are run on the control device of the lighting device, the control device of the lighting device executes the control method of the lighting device as described in the first aspect.

In a fifth aspect, the present invention provides a lighting device control device, including: a processor and a memory, the memory is used to store programs, and the processor invokes the programs stored in the memory to execute the lighting device control method as described in the first aspect .

For the specific description of the second aspect to the fifth aspect and its various implementations in the present invention, you can refer to the detailed description in the first aspect and its various implementations; and, the second to the fifth aspect and its various implementations For the beneficial effects of the manner, reference may be made to the first aspect and the analysis of beneficial effects in various implementation manners thereof, and details are not repeated here.

These and other aspects of the invention will be more clearly understood in the following description.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those skilled in the art, other drawings can also be obtained based on these drawings without creative effort.

FIG. 1 is a schematic diagram of a lighting system provided by an embodiment of the present invention;

FIG. 2 is a first structural schematic diagram of a control device for lighting equipment provided by an embodiment of the present invention;

FIG. 3 is a first schematic flow diagram of a method for controlling lighting equipment provided by an embodiment of the present invention;

FIG. 4 is a second schematic flow diagram of a method for controlling lighting equipment provided by an embodiment of the present invention;

FIG. 5 is a schematic flow diagram III of a control method for lighting equipment provided by an embodiment of the present invention;

Fig. 6 is a second structural schematic diagram of a control device for lighting equipment provided by an embodiment of the present invention.

Detailed ways

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. 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.

The term "and/or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and/or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations.

The terms "first" and "second" in the description and drawings of the present invention are used to distinguish different objects, or to distinguish different processes for the same object, rather than to describe a specific sequence of objects.

In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other unlisted steps or units, or may optionally also include Other steps or elements inherent to the process, method, product or apparatus are included.

It should be noted that, in the description of the embodiments of the present invention, words such as "exemplary" or "for example" are used as examples, illustrations or illustrations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present invention shall not be construed as being more preferred or more advantageous than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete manner.

In the description of the present invention, unless otherwise specified, the meaning of "plurality" refers to two or more than two.

In the following, terms involved in the embodiments of the present invention are explained to facilitate readers' understanding.

Multi-access edge computing (multi-access edge computing, MEC) or multi-access edge cloud (multi-access edge cloud, MEC) is on the edge of the network close to the source of people, things or data, integrating network, computing, storage, An open platform that applies core capabilities and provides nearby edge computing services to meet the key needs of industry digitalization in terms of agile connection, real-time business, data optimization, security and privacy protection. Edge computing or edge cloud technology has become one of the important technologies supported by the 5th generation mobile networks (5G), and the 3rd generation partnership project (3GPP) has made it clear that the 5G core network Support edge computing write standard 23.501. Artificial intelligence technology is combined with edge computing or edge cloud technology to construct intelligent edge computing or intelligence.

The support degree indicates the frequency of related things appearing in a data set at the same time. A high degree of support for related things indicates that the related things are high-frequency related things in the data set. The support degree can be obtained according to the relational expression "support degree=(number of associated things/sum of the number of mined things)".

Confidence indicates the degree of credibility of related things, and the higher the degree of confidence of related things, the higher the degree of credibility of related things. The confidence degree can be obtained according to the relational expression "confidence degree=(number of related things/number of one of the mined related things)".

Cosine similarity measures the similarity between two vectors by measuring the cosine of the angle between them. The cosine of an angle of 0 degrees is 1, and the cosine of any other angle is no greater than 1; and its minimum value is -1. Thus the cosine of the angle between two vectors determines whether the two vectors are generally pointing in the same direction. When two vectors have the same direction, the value of cosine similarity is 1; when the angle between two vectors is 90°, the value of cosine similarity is 0; when two vectors point in completely opposite directions, the value of cosine similarity is -1. This result is independent of the length of the vector, only the direction in which the vector points. Cosine similarity is usually used in positive spaces, so it is given a value between -1 and 1. In the case of information retrieval, since the frequency of a word cannot be negative, the cosine similarity of the two documents ranges from 0 to 1. Also, the angle between the frequency vectors of two words cannot be larger than 90°. The most common application of cosine similarity is to calculate text similarity. The two texts are based on their words, and two vectors are established, and the cosine value of the two vectors is calculated, and the similarity of the two texts in the statistical method can be known. Practice has proved that this is a very effective method.

Normalization is a way of simplifying calculations, that is, transforming a dimensioned expression into a dimensionless expression and becoming a scalar. This method is often used in various calculations. The normalized value can be obtained according to the relationship "normalized value=(value to be normalized-minimum value of the feature column)/(maximum value of the feature column-minimum value of the feature column)".

Information entropy is a measure of system order, the more chaotic the system, the greater the information entropy. If the value of a random variable X is X={x1,x2,...,xn}, and each probability obtained is {p1,p2,...,pn}, then the entropy is defined as:

信息增益越大，区分样本的能力就越强，越具有代表性。IG(S/T)这个代表在特征属性T的条件下样本的信息增益。S是全部样本集合，value(T)是属性T所有取值的集合，v是T的其中一个属性值，sv是S中属性T的值为v的样例集合，|sv|为sv中所含样例数。如果我们的结果只有是用户类型A和非用户类型A，那么属性T指的是用户类型A，S指的是包含用户类型A和非用户类型A，v指的是用户信息的一个字段k，sv指的是用户类型A的具有字段K的样例集合。Information gain is the difference between the information before and after the attribute selection division of the decision tree. The formula for calculating information gain is:

The greater the information gain, the stronger the ability to distinguish samples and the more representative they are. IG(S/T) This represents the information gain of the sample under the condition of the feature attribute T. S is the set of all samples, value(T) is the set of all values of the attribute T, v is one of the attribute values of T, sv is the set of samples whose value of the attribute T in S is v, and |sv| is all values in sv Contains the number of samples. If our result is only user type A and non-user type A, then attribute T refers to user type A, S refers to user type A and non-user type A, v refers to a field k of user information, sv refers to the sample set of user type A with field K.

An embodiment of the present invention provides a method for controlling a lighting device, which is suitable for a lighting system. FIG. 1 shows a structure of the lighting system. As shown in FIG. 1 , the lighting system may include: one or more lighting device control devices 100 , one or more lighting devices, one or more business data acquisition devices, and one or more network data acquisition devices. Fig. 1 illustrates a lighting system including a lighting device control device 100, a lighting device, a business data acquisition device, and a network data acquisition device. Each device in the lighting system can be connected through a wireless network or a wired network.

The lighting device control device 100 is used to implement the following lighting device control method. The control device 100 for lighting equipment can also be called an artificial intelligence module. The control device 100 (artificial intelligence module) of lighting equipment can be deployed in the edge computing architecture. Deployment forms include but are not limited to virtual machines, containers, and microservices.

The business data acquiring device is used for acquiring business data. The service data acquiring device may include one or more cameras and/or one or more sensors. The service data acquisition device can also be called a service data module.

The network data acquiring device is used for acquiring network data. The network data acquisition device may be an edge node. The network data acquisition device can be connected to the 5G core network. The network data acquisition device may also be called a network data module.

Lighting equipment includes but is not limited to various lamps with switch and brightness adjustment functions.

An embodiment of the present invention provides a method for controlling a lighting device, and the method for controlling the lighting device can be executed by the control device 100 for the lighting device. Fig. 2 shows a hardware structure of the control device 100 of the lighting equipment. As shown in FIG. 2 , the control device 100 for lighting equipment may include at least one processor 101 , a communication line 102 , a memory 103 and a communication interface 104 .

Specifically, the processor 101 is configured to execute computer-executable instructions stored in the memory 103, so as to implement steps or actions of the terminal.

Processor 101 may be a chip. For example, it can be a field programmable gate array (fieldprogrammable gate array, FPGA), it can be an application specific integrated circuit (ASIC), it can also be a system chip (system on chip, SoC), it can also be a central processing unit ( central processor unit (CPU), can also be a network processor (network processor, NP), can also be a digital signal processing circuit (digital signal processor, DSP), can also be a microcontroller (microcont roller unit, MCU), or It can be a programmable controller (programmable logic device, PLD) or other integrated chips.

The communication line 102 is used to transmit information between the processor 101 and the memory 103 .

The memory 103 is used for storing and executing computer-executable instructions, and the execution is controlled by the processor 101 .

The memory 103 may exist independently, and is connected to the processor through the communication line 102 . Memory 103 may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. Among them, the non-volatile memory can be read-only memory (read-only memory, ROM), programmable read-only memory (programmableROM, PROM), erasable programmable read-only memory (erasable PROM, EPROM), electrically programmable Erase programmable read-only memory (ele ctrically EPROM, EEPROM) or flash memory. Volatile memory can be random access memory (RAM), which acts as external cache memory. By way of illustration and not limitation, many forms of RAM are available such as static random access memory (static RAM, SRAM), dynamic random access memory (dynamic RAM, DRAM), synchronous dynamic random access memory (synchronous DRAM, SDRAM) ), double data rate synchronous dynamic random access memory (double data rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (enhanced SDRAM, ESDRAM). It should be noted that the memory of the systems and devices described herein is intended to include, but not be limited to, these and any other suitable types of memory.

The communication interface 104 is used for communicating with other devices or a communication network. Wherein, the communication network may be Ethernet, a radio access network (radio access network, RAN), or a wireless local area network (wireless local area networks, WLAN), etc.

The method for controlling a lighting device provided by an embodiment of the present invention will be described below in conjunction with the lighting system shown in FIG. 1 and the control device 100 for a lighting device shown in FIG. 2 .

As shown in Fig. 3, the control method for lighting equipment provided by the embodiment of the present invention includes:

S301. The control device 100 of the lighting equipment acquires network data of users in the lighting area of the lighting equipment.

Specifically, the control device 100 of the lighting equipment acquires network data of users in the lighting area from the network data acquiring device at regular intervals.

Wherein, the network data includes one or more of time period, age, gender, occupation, user location and traffic information. For example, user A's network data includes time period and age, and user B's network data includes age, occupation, and user location. The network data may also include other parameters, for example, lighting device switching time, lighting device brightness status, lighting device switching complaints, lighting device brightness complaints, and the like. The application program used by the user can be determined according to the traffic information of the user.

S302. The control apparatus 100 of the lighting equipment determines the user type of the user according to the network data of the user.

Specifically, the control device 100 of the lighting equipment parses the network data of the user to obtain the feature field of the user.

Exemplarily, as shown in Table 1, the control device 100 for lighting equipment parses the network data of user A, and obtains the feature field of user A (19, male, A1 lighting equipment, fitness, 18:00-20:00, level 1 ,short).

Also exemplary, as shown in Table 1, the lighting device control device 100 parses the network data of user B, and obtains the feature field of user B (60, female, A2 lighting device, music, 18:00-20:00, 1 level, dark).

Table 1

The control device 100 of the lighting device determines the user type of the user according to the characteristic field of the user.

Specifically, the control device 100 of the lighting equipment uses the feature field with the largest information gain among the feature fields of the user as a root node, the remaining feature fields as non-leaf nodes, and user types as leaf nodes to construct a decision tree. Then the user type of the user is obtained through the decision tree. Among them, using the feature field with the largest information gain as the root node can reduce the level of the decision tree, reduce computational complexity, and improve computational efficiency.

S303. The control device 100 of the lighting device adjusts the state of the lighting device according to the state parameter of the lighting device corresponding to the user type of the target user when the number of target users in the lighting area of the lighting device is greater than the first number threshold.

Wherein, the target users are users of the same user type, and the state parameters of the lighting equipment include brightness parameters of the lighting equipment and switch parameters of the lighting equipment.

Optionally, the control device 100 of the lighting device adjusts the state of the lighting device according to preset state parameters of the lighting device when the number of target users in the lighting area of the lighting device is greater than a second number threshold.

Wherein, the second quantity threshold is greater than the first quantity threshold. The preset state parameters of the lighting equipment can be manually formulated by experts.

Optionally, the control apparatus 100 of the lighting device generates label information when the number of target users in the lighting area of the lighting device is greater than a third number threshold.

Wherein, the marking information is used to mark the number of times that the number of target users in the lighting area of the lighting device exceeds the third threshold. When the number of times in the marked information reaches a certain number, lighting equipment needs to be added or removed. If the number of target users in the lighting area of the lighting equipment is greater than the third number threshold, it means that there are many people gathered in the lighting area of the lighting equipment, and the large number of people gathered in the lighting area of the lighting equipment may be that the location planning of the lighting equipment construction is unreasonable caused by. Therefore it is necessary to add lighting devices to divert the crowd.

Exemplarily, as shown in Table 2, when the number of users of user type A in the lighting area of the K1 lighting device is greater than the first threshold, the control device 100 of the lighting device, according to the state of the lighting device corresponding to the user type A, parameter to adjust the state of the lighting device K1.

Table 2

For another example, as shown in Table 2, when the number of users of user type B in the lighting area of the K2 lighting device is greater than the first number threshold, the control device 100 of the lighting device, according to the lighting device corresponding to the user type B, The status parameters of the lighting device K2 are adjusted. The control device 100 of the lighting device adjusts the state of the lighting device according to the preset state parameter of the lighting device when the number of users of user type B in the lighting area of the K2 lighting device is at the second threshold value. The control device 100 of the lighting equipment suggests adding lighting equipment when the number of users of user type B in the lighting area of the K2 lighting equipment is greater than the third number threshold and reaches a preset number.

Referring to FIG. 3 , as shown in FIG. 4 , the lighting device control method provided by the embodiment of the present invention may further include:

S304. The control apparatus 100 of the lighting equipment acquires network data and service data of multiple users.

Wherein, the service data includes one or more of time period, user location, status of lighting equipment, and number of users.

S305. The lighting device control apparatus 100 determines multiple user types according to network data and multiple service data of multiple users.

Specifically, S305 may include:

The control device 100 of the lighting equipment analyzes the network data and the service data of multiple users to obtain multiple feature fields.

The control device 100 of the lighting system determines a plurality of association rules.

Wherein, the association rule includes multiple different fields.

The control device 100 of the lighting system determines the support and confidence of the association rules.

The control device 100 of the lighting system determines a target association rule.

Wherein, the target association rule is an association rule whose support degree is greater than a first threshold and whose confidence degree is greater than a second threshold. The target association rule may also be an association rule whose support degree is greater than or equal to the first threshold and whose confidence degree is greater than or equal to the second threshold. If the support degree of the association rule is greater than the first threshold and the confidence degree is greater than the second threshold, it means that the association rule has a higher frequency of occurrence and a higher degree of credibility.

The control device 100 of the lighting device determines the user characteristics, behavior track and spatio-temporal characteristics of each of the multiple users according to the target association rule.

Wherein, the user characteristics include one or more of age and occupation. Behavior traces include time periods and user behaviors, that is, what users are doing in each period. Spatio-temporal features include time period and user location, that is, where the user is in each time period.

The control device 100 of the lighting device determines user information of each user among the plurality of users according to the user characteristics, behavior track and spatio-temporal characteristics of each user among the plurality of users.

The control device 100 of the lighting equipment converts the user information of each of the plurality of users into a vector.

Specifically, the control apparatus 100 of the lighting equipment converts the user information of each of the multiple users into a vector by normalizing and de-dimensionalizing the user information of each of the multiple users.

The control device 100 of the lighting device determines the cosine similarity between the vectors of every two users among the plurality of users.

The control device 100 of the lighting device determines multiple user types, users of the same user type are similar users, and the cosine similarity between vectors of similar users is greater than a third threshold.

Exemplarily, user type A includes user A, user B, and user C. Then user A, user B, and user C are similar users to each other. That is to say, the cosine similarity between vectors of user A and user B, the cosine similarity between vectors of user B and user C, and the cosine similarity between vectors of user A and user C are all greater than the third threshold.

S306. The control apparatus 100 of the lighting device determines a feature field corresponding to each user type among the multiple user types.

The functions of S304 to S306 are to establish the corresponding relationship between feature fields and user types. The control device 100 of the lighting equipment can determine the user type of the user according to the characteristic field of the user (the characteristic field in the user's network data).

Referring to FIG. 4, as shown in FIG. 5, the method for controlling lighting equipment provided by the embodiment of the present invention may further include:

S307. The control apparatus 100 of the lighting equipment determines a lighting association rule.

Wherein, the lighting association rule is an association rule related to the state of the lighting device in the target association rules. That is, the association rules related to the brightness state of the lighting device, the switching state of the lighting device or the position of the lighting device in the target association rules. For example, {Lighting Fixture A, 60-65, 20:00-21:00, retired}.

S308. The lighting device control apparatus 100 determines the state parameter of the lighting device corresponding to each user type among the multiple user types according to the feature field and the lighting association rule corresponding to each user type among the multiple user types.

Wherein, the determined corresponding relationship between the user type and the state parameter of the lighting device may be optimized, so that the corresponding relationship between the user type and the state parameter of the lighting device is more reasonable. Optimization methods include but are not limited to expert optimization, complaint optimization, etc. The expert priority refers to adjusting the state parameters of the lighting equipment according to the expert's suggestion. Complaint optimization refers to adjusting the status parameters of lighting equipment according to the opinions in the complaint work order. The corresponding relationship between the user type and the state parameter of the lighting device can be stored in the database. The database that stores the correspondence between user types and state parameters of lighting equipment may be called a knowledge base of lighting usage requirements. In addition, when the number of target users of the lighting device exceeds the third number threshold for many times, it is necessary to modify the corresponding relationship in the knowledge base of lighting usage requirements, or to remove or add a lighting device to meet user needs.

The function of S307 to S308 is to establish the corresponding relationship between the user type and the state parameter of the lighting device. The control device 100 of the lighting equipment can obtain the corresponding state parameters of the lighting equipment according to the user type. For example, the state parameter of the lighting device corresponding to the square dance user type. The status parameters of the lighting equipment corresponding to users of the night running type.

In the embodiment of the present invention, random forest, gradient boosting decision tree (gradient boosting decision tree, GBDT), classification and regression tree (classification and regression tree, CART) and other similar algorithms can be used to solve classification (determine user type according to characteristics, determine lighting according to user type) The status parameter of the device) problem.

In the embodiment of the present invention, similar algorithms such as correlation analysis algorithm (apriori), frequent pattern growth algorithm (frequent pattern growth, FP-growth), fast update algorithm (fast update, FUP) can be used to do rule mining (according to network data or business data, get feature field).

In the embodiment of the present invention, the database structured query language (structured query language, SQL) for storing business data and network data is constructed, and it can also be constructed with a relational or non-relational database such as a non-structured query language (not only structured query language, NoSQL). .

The foregoing mainly introduces the solutions provided by the embodiments of the present invention from the perspective of methods. In order to realize the above functions, it includes corresponding hardware structures and/or software modules for performing various functions. Those skilled in the art should easily realize that the present invention can be realized in the form of hardware or a combination of hardware and computer software in combination with the units and algorithm steps of each example described in the embodiments disclosed herein. Whether a certain function is executed by hardware or computer software drives hardware depends on the specific application and design constraints of the technical solution. Skilled artisans may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present invention.

The embodiment of the present invention can divide the functional modules of the control device 100 of the lighting equipment according to the above method example, for example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one processing module . The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software function modules. It should be noted that the division of modules in the embodiment of the present invention is schematic, and is only a logical function division, and there may be another division manner in actual implementation.

An embodiment of the present invention provides a lighting device control device 100, which is used to execute the above-mentioned lighting device control method. As shown in FIG. 6, the lighting device control device 100 includes: a first acquisition unit 601, a first determination unit 602 and control unit 603.

The first obtaining unit 601 is configured to obtain network data of users in the lighting area of the lighting device, and the network data includes one or more of time period, age, gender, occupation, user location and traffic information. For example, referring to FIG. 3 , the first acquiring unit 601 may be configured to perform S301.

The first determining unit 602 is configured to determine the user type of the user according to the network data of the user. For example, referring to FIG. 3 , the first determining unit 602 may be configured to execute S302.

The first determining unit 602 is specifically configured to:

Analyze the user's network data to obtain the user's feature field.

According to the feature field of the user, the user type of the user is determined.

The control unit 603 is configured to adjust the state of the lighting device according to the state parameter of the lighting device corresponding to the user type of the target user when the number of target users in the lighting area of the lighting device is greater than the first number threshold, and the target user is For users of the same user type, the state parameters of the lighting equipment include brightness parameters of the lighting equipment and switching parameters of the lighting equipment. For example, referring to FIG. 3 , the control unit 603 may be configured to execute S303.

As shown in FIG. 6 , the control apparatus 100 for lighting equipment may further include: a second acquiring unit 604 , a second determining unit 605 and a third determining unit 606 .

The second acquiring unit 604 is configured to acquire network data and business data of multiple users, where the business data includes one or more of time period, user location, status of lighting equipment, and number of users. For example, referring to FIG. 4 , the second acquiring unit 604 may be configured to execute S304.

The second determining unit 605 is configured to determine multiple user types according to network data and multiple service data of multiple users. For example, referring to FIG. 4 , the second determining unit 605 may be configured to perform S305.

The second determining unit 605 is specifically configured to:

Analyze the network data and business data of multiple users to obtain multiple feature fields.

A plurality of association rules are determined, and the association rules include a plurality of different fields.

Determine the support and confidence of association rules.

A target association rule is determined, where the target association rule is an association rule with a support degree greater than a first threshold and a confidence degree greater than a second threshold.

According to the target association rules, the user characteristics, behavior trajectory and spatiotemporal characteristics of each user among multiple users are determined. User characteristics include one or more of age and occupation, behavior trajectory includes time period and user behavior, and spatiotemporal characteristics include time period and user location.

The user information of each user among the plurality of users is determined according to the user characteristics, behavior track and spatio-temporal characteristics of each user among the plurality of users.

Convert user information for each of the multiple users into a vector.

Determine the cosine similarity between the vectors for every two of the users.

Multiple user types are determined, users of the same user type are similar users, and the cosine similarity between vectors of similar users is greater than a third threshold.

The third determining unit 606 is configured to determine a feature field corresponding to each user type among the multiple user types. For example, referring to FIG. 4 , the third determining unit 606 may be configured to perform S306.

As shown in FIG. 6 , the control apparatus 100 for lighting equipment may further include: a fourth determination unit 607 and a fifth determination unit 608 .

The fourth determination unit 607 is configured to determine a lighting association rule, where the lighting association rule is an association rule related to the state of the lighting device in the target association rules. For example, referring to FIG. 5 , the fourth determining unit 607 may be configured to perform S307.

The fifth determining unit 608 is configured to determine the state parameter of the lighting device corresponding to each user type in the plurality of user types according to the feature field and the lighting association rule corresponding to each user type in the plurality of user types. For example, referring to FIG. 5 , the fifth determining unit 608 may be configured to perform S308.

Specifically, as shown in FIG. 2 and FIG. 6 . The first acquisition unit 601, the first determination unit 602, the control unit 603, the second acquisition unit 604, the second determination unit 605, the third determination unit 606, the fourth determination unit 607 and the fifth determination unit 608 in FIG. 6, The program in the memory 103 is invoked by the processor 101 in FIG. 2 via the communication line 102 to execute the above-mentioned control method of the lighting device.

It should be understood that in various embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the order of execution, and the execution order of each process should be determined by its functions and internal logic, rather than by the embodiment of the present invention. The implementation process constitutes any limitation.

Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present invention.

Those skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated. to another system, or some features may be ignored, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

A unit described as a separate component may or may not be physically separated, and a component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.

The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention shall be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims (8)

1. A control method for lighting equipment, comprising: Obtain network data of users in the lighting area of the lighting equipment, where the network data includes one or more of time period, age, gender, occupation, user location and traffic information; determining the user type of the user according to the network data of the user; When the number of target users in the lighting area of the lighting device is greater than a first number threshold, adjust the state of the lighting device according to the state parameter of the lighting device corresponding to the user type of the target user, and the target The users are users of the same user type, and the state parameters of the lighting equipment include brightness parameters of the lighting equipment and switch parameters of the lighting equipment; The control method also includes: Obtain network data and business data of multiple users, where the business data includes one or more of time period, user location, status of lighting equipment, and number of users; determining multiple user types according to the network data of the multiple users and the multiple service data, determining a characteristic field corresponding to each user type in the plurality of user types; The determining multiple user types according to the network data of the multiple users and the multiple service data includes: Analyzing the network data of the multiple users and the multiple service data to obtain multiple feature fields; determining a plurality of association rules, the association rules comprising a plurality of different fields; Determining the support and confidence of association rules; determining a target association rule, where the target association rule is an association rule with a support degree greater than a first threshold and a confidence degree greater than a second threshold; According to the target association rule, determine the user characteristics, behavior track and spatio-temporal characteristics of each user in the plurality of users, the user characteristics include one or more of age and occupation, and the behavior track includes time period and user Behavior, the spatio-temporal features include time period and user location; determining user information of each user among the plurality of users according to user characteristics, behavior traces, and spatiotemporal characteristics of each user among the plurality of users; converting the user information of each user among the multiple users into a vector; determine the cosine similarity between the vectors of every two users among the plurality of users; Multiple user types are determined, users of the same user type are similar users, and the cosine similarity between vectors of similar users is greater than a third threshold. 2. The control method according to claim 1, wherein the determining the user type of the user according to the network data of the user comprises: Analyzing the network data of the user to obtain the feature field of the user; The user type of the user is determined according to the feature field of the user. 3. The control method according to claim 1, wherein the control method further comprises: determining a lighting association rule, where the lighting association rule is an association rule related to the state of lighting equipment in the target association rules; According to the feature field corresponding to each user type in the plurality of user types and the lighting association rule, determine the state parameter of the lighting device corresponding to each user type in the plurality of user types. 4. A control device for lighting equipment, comprising: a first acquisition unit, a first determination unit and a control unit; The first acquisition unit is configured to acquire network data of users in the lighting area of the lighting device, where the network data includes one or more of time period, age, gender, occupation, user location and traffic information; The first determining unit is configured to determine the user type of the user according to the network data of the user; The control unit is configured to adjust the lighting according to the state parameter of the lighting device corresponding to the user type of the target user when the number of target users in the lighting area of the lighting device is greater than a first number threshold The state of the device, the target user is a user of the same user type, and the state parameters of the lighting device include brightness parameters of the lighting device and switch parameters of the lighting device; The control device further includes: a second acquiring unit, a second determining unit, and a third determining unit; The second acquiring unit is configured to acquire network data and business data of multiple users, where the business data includes one or more of time period, user location, status of lighting equipment, and number of users; The second determining unit is configured to determine multiple user types according to the network data of the multiple users and the multiple service data; The third determining unit is configured to determine a characteristic field corresponding to each user type among the plurality of user types; The second determining unit is specifically used for: Analyzing the network data of the multiple users and the multiple service data to obtain multiple feature fields; determining a plurality of association rules, the association rules comprising a plurality of different fields; Determining the support and confidence of association rules; determining a target association rule, where the target association rule is an association rule with a support degree greater than a first threshold and a confidence degree greater than a second threshold; According to the target association rule, determine the user characteristics, behavior track and spatio-temporal characteristics of each user in the plurality of users, the user characteristics include one or more of age and occupation, and the behavior track includes time period and user Behavior, the spatio-temporal features include time period and user location; determining user information of each user among the plurality of users according to user characteristics, behavior traces, and spatiotemporal characteristics of each user among the plurality of users; converting the user information of each user among the multiple users into a vector; determine the cosine similarity between the vectors of every two users among the plurality of users; Multiple user types are determined, users of the same user type are similar users, and the cosine similarity between vectors of similar users is greater than a third threshold. 5. The control device according to claim 4, wherein the first determining unit is specifically configured to: Analyzing the network data of the user to obtain the feature field of the user; The user type of the user is determined according to the feature field of the user. 6. The control device according to claim 4, characterized in that, the control device further comprises: a fourth determining unit and a fifth determining unit; The fourth determination unit is configured to determine a lighting association rule, where the lighting association rule is an association rule related to the state of lighting equipment in the target association rules; The fifth determining unit is configured to determine the state of the lighting device corresponding to each user type in the plurality of user types according to the feature field corresponding to each user type in the plurality of user types and the lighting association rule parameter. 7. A control device for lighting equipment, characterized in that the control device for lighting equipment comprises: one or more processors, and a memory; The memory is coupled to the one or more processors; the memory is used to store computer program code, the computer program code includes instructions, and when the one or more processors execute the instructions, the lighting The control device of the equipment executes the control method of the lighting equipment according to any one of claims 1-3. 8. A computer-readable storage medium, comprising instructions, characterized in that, when the instructions are run on the control device of the lighting device, the control device of the lighting device is made to execute any one of claims 1-3. The control method of the lighting equipment.

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