CN112581728B - Cloud-based low-power early warning method and system for wireless terminal of Internet of things - Google Patents
Cloud-based low-power early warning method and system for wireless terminal of Internet of things Download PDFInfo
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- CN112581728B CN112581728B CN202011433592.8A CN202011433592A CN112581728B CN 112581728 B CN112581728 B CN 112581728B CN 202011433592 A CN202011433592 A CN 202011433592A CN 112581728 B CN112581728 B CN 112581728B
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
- G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract
The invention discloses a cloud-based low-power early warning method for a wireless terminal of an Internet of things, which comprises the following steps: after the electric quantity data of the wireless terminal are changed, reporting the real-time electric quantity to a cloud platform as a data source of a big data computing platform; the big data computing platform collects data of the cloud platform, a low electric quantity threshold value and an electric quantity deviation value are preset, computing is carried out according to the currently reported real-time electric quantity, and whether pushing early warning is needed or not is judged; the calculation method comprises the following steps: and comparing the acquired data with a low-power threshold value and a maximum deviation value, and calculating and judging whether to carry out early warning pushing or not. The invention also discloses a cloud-based low-power early warning system for the wireless terminal of the Internet of things. The invention solves the problem that the normal operation of the equipment is influenced by insufficient electric quantity caused by untimely battery replacement after the intelligent terminal equipment with the battery runs for a long time.
Description
Technical Field
The invention belongs to the field of Internet of things, and particularly relates to a cloud-based low-power early warning method and system for an Internet of things wireless terminal.
Background
Along with the popularization of the internet of things smart home, smart devices have begun to permeate into common homes, smart devices on the market at present mainly comprise wired devices and wireless devices, wherein the wired devices can be powered by a power connection mode, the wireless devices are powered by batteries, how long the wireless devices can operate is based on the battery capacity of the devices, and after the devices operate for a long time, if a user does not know or forgets to replace the batteries, the problem that the devices cannot operate due to the fact that the electric quantity of the batteries is exhausted exists, and particularly, the devices in security and protection can have great potential safety hazards; how to inform the user of the accurate information of the too low electric quantity of the equipment in time becomes a problem that smart home manufacturers need to solve urgently.
Disclosure of Invention
Aiming at the technical problem, the invention discloses a cloud-based low-power early warning method and system for a wireless terminal of the Internet of things.
In order to achieve the purpose, the invention adopts the technical scheme that:
a cloud-based low-power early warning method for a wireless terminal of an Internet of things comprises the following steps:
after the electric quantity data of the wireless terminal is changed, reporting the real-time electric quantity to a cloud platform as an original data source of a big data computing platform;
the big data computing platform receives original data sent by the cloud platform, performs data cleaning, and stores sampled electric quantity data;
a low electric quantity threshold value and an electric quantity deviation value are preset in the big data computing platform, and the big data computing platform carries out computation according to the currently reported electric quantity data and judges whether push early warning is needed or not;
the calculation method comprises the following steps: comparing the data acquired this time with a low-power threshold, and replacing the stored data acquired last time with the data value acquired this time if the data acquired this time is larger than the low-power threshold; otherwise, calculating the difference value between the data acquired last time and the data acquired this time;
if the difference between the data acquired this time and the data acquired last time is smaller than the maximum deviation value, replacing the data acquired last time with the data acquired this time; otherwise, calculating the average electric quantity of the wireless terminal;
inquiring the latest N sampling values of the wireless terminal, removing a maximum value and a minimum value, then calculating the average value of N-2 data, and if the average value is larger than a low-power threshold, replacing the data acquired last time with the data acquired this time; otherwise, early warning pushing is carried out.
Further, the wireless terminal reports the electric quantity, and when the wireless terminal monitors that the voltage electric quantity of the wireless terminal changes, the sampled electric quantity data are sent to the intelligent gateway through an internet of things protocol.
Further, the data cleansing includes: filtering data, wherein the original data comprises response data of a command issued by a cloud platform and data actively reported by a wireless terminal, and filtering the response data in the original data; and data classification, wherein the wireless terminal actively reports data including heartbeat data, equipment state data, alarm data and electric quantity sampling data, and classifies the electric quantity sampling data in the actively reported data.
Furthermore, after the big data computing platform stores the electric quantity sampling data, the data model is adjusted according to the electric quantity sampling data, and if the electric quantity sampling data is larger than the maximum electric quantity of the data model, the maximum electric quantity value and the reporting time of the wireless terminal are updated; and if the sampling electric quantity is smaller than the minimum electric quantity of the data model, updating the minimum electric quantity value and the reporting time of the wireless terminal.
Further, when the electric quantity sampling data is smaller than a low electric quantity threshold value, calculating the maximum operation time length predicted by the wireless terminal according to the maximum electric quantity value and the time interval recorded by the minimum electric quantity value of the data model, meanwhile, calculating the actual operation time length of the equipment according to the electric quantity time reported for the first time after the wireless terminal is electrified and the interval of the current time of the system, and if the actual operation time length is longer than the maximum operation time length, carrying out early warning and pushing.
Further, in order to avoid that the user frequently receives early warning within an effective range of a period of time, the early warning pushing module needs to perform verification after receiving the early warning information, and if a pushing record exists within the effective range of the time, the information is not pushed, and the process is ended; and if the record is not pushed within the effective time, carrying out early warning pushing and recording a pushing log.
Further, when the early warning needs to be pushed, the big data computing platform returns the early warning information to the cloud platform, and the early warning information is pushed to the mobile terminal device of the user through the early warning pushing module of the cloud platform.
The invention also discloses a cloud-based low-power early warning system for the wireless terminal of the Internet of things, which comprises the wireless terminal, an intelligent gateway, a cloud platform, a big data computing platform and mobile terminal equipment; the cloud platform and the wireless terminal are bridged through an intelligent gateway, so that real-time data communication is realized; the cloud platform is in communication connection with the mobile terminal device, so that safety authentication, data encryption and decryption and early warning pushing are realized; and is in bidirectional communication connection with a big data computing platform;
after monitoring that the voltage and the electric quantity of the wireless terminal change, the wireless terminal sends original data to the intelligent gateway through an Internet of things protocol;
the intelligent gateway receives data sent by the wireless terminal, translates and analyzes the data, and reports the data through a communication protocol agreed with the cloud platform;
the cloud platform receives data sent by the intelligent gateway, analyzes and translates the data, acquires original data and sends the original data to the big data computing platform;
the big data computing platform comprises a data acquisition module, a data cleaning module, a data modeling module, an algorithm module and a database; the data acquisition module receives original data sent by the cloud platform; the data cleaning module is used for filtering and classifying the original data and then storing the electric quantity sampling data into a database; the data modeling module adjusts the data model through the cleaned sampling data; and the algorithm module calculates according to the current electric quantity sampling data, the stored historical data and the data model, and judges whether the early warning needs to be pushed or not.
Further, data filtering is carried out, wherein the original data comprises response data of an instruction issued by the cloud platform and data actively reported by the wireless terminal, and response data in the original data are filtered out; data classification, wherein the wireless terminal actively reports data including heartbeat data, equipment state data, alarm data and electric quantity sampling data, and classifies the electric quantity sampling data in the actively reported data; the data modeling module adjusts the data model: if the electric quantity sampling data is larger than the maximum electric quantity of the data model, updating the maximum electric quantity value and the reporting time of the wireless terminal; and if the sampling electric quantity is smaller than the minimum electric quantity of the data model, updating the minimum electric quantity value and the reporting time of the wireless terminal.
Further, when the early warning needs to be pushed, the big data computing platform returns the early warning information to the cloud platform, and the early warning information is pushed to the mobile terminal device of the user through an early warning pushing module of the cloud platform.
Furthermore, the early warning pushing module needs to perform verification after receiving the early warning information, and if a pushing record exists in the effective time range, the information is not pushed, and the process is ended; and if the record is not pushed within the effective time, carrying out early warning pushing and recording a pushing log.
The invention has the following beneficial effects: the invention solves the problem that the normal operation of the equipment cannot be influenced if the battery is not replaced in time and the electric quantity is insufficient after the intelligent terminal equipment with the battery runs for a long time.
Drawings
Fig. 1 is a service communication flow chart of a cloud-based internet of things wireless terminal low-power early warning system in an embodiment of the invention.
FIG. 2 is a block diagram of a big data computing platform and a processing flow diagram according to an embodiment of the present invention.
Fig. 3 is a flow chart of pushing of the cloud-based internet of things wireless terminal low-power early warning system according to the embodiment of the invention.
Fig. 4 is a flow chart of data acquisition of a wireless terminal according to a low power warning method in an embodiment of the present invention.
Fig. 5 is a flowchart of a push warning algorithm of a low power warning method according to an embodiment of the present invention.
Detailed Description
In order to facilitate understanding of those skilled in the art, the present invention will be further described with reference to the following embodiments and accompanying drawings.
The embodiment is the intelligent terminal device based on battery power supply, when the electric quantity reaches the low electric quantity alarm threshold value after the device operates for a period of time, real-time sample data collected through the cloud platform big data system are analyzed, modeled and predicted, alarm information is pushed to a user through the cloud platform in time, the user can be guaranteed to receive early warning information in the first time, the battery is replaced, and normal operation of the device is guaranteed.
As shown in the traffic communication flow diagram of fig. 1, the wireless terminal device: the device can operate without wiring and adopting battery power supply in the field of Internet of things;
the intelligent gateway: the central control device in the field of intelligent home is used for bridging data real-time communication between a cloud platform and terminal equipment, and comprises protocol translation, data acquisition and service processing;
a cloud platform: the intelligent gateway and the mobile terminal are responsible for equipment access and communication, including security authentication, data encryption and decryption, task scheduling, early warning pushing and the like; meanwhile, the sampled data are sent to a big data platform for calculation and analysis;
big data computing platform: performing data cleaning, storage, modeling and data analysis through the data reported by the terminal equipment, and judging whether early warning is needed or not according to an analysis result;
a mobile terminal: the device capable of receiving the early warning information pushed by the cloud platform comprises a smart phone, a smart sound box and the like;
as shown in fig. 2, 202, the big data computing platform comprises a data acquisition module, a data cleaning module, a data modeling module and an algorithm module;
the data acquisition module acquires 201 sampling data reported by the wireless terminal;
the data cleaning module filters and classifies the acquired data;
the data modeling module continuously adjusts the data model through the archived data;
the algorithm module analyzes and calculates historical data of the equipment according to the currently reported real-time electric quantity to obtain whether a data conclusion needs to be pushed for early warning;
203. the database system is used for storing the generated service data and the sampling data;
204. the early warning pushing module is a data output module of the system and pushes early warning information to mobile terminal equipment of a user.
As shown in the flowcharts of fig. 3 and 4, when the wireless terminal monitors that the electric quantity changes, the wireless terminal reports the electric quantity sampling value; the cloud platform receives the sampling value, the big data computing platform analyzes the data and judges whether pushing early warning is needed or not, and if not, the process is ended; if the early warning information is needed, the early warning information is forwarded to an early warning pushing module; in order to avoid that the user frequently receives early warning within an effective range of a period of time, the early warning pushing module needs to verify after receiving early warning information, and if a pushing record exists within the effective range of the time, the information is not pushed, and the process is ended; if the record is not pushed within the effective time, early warning pushing is carried out, and a pushing log is recorded; and the mobile terminal equipment receives the early warning information, and the process is finished.
The data acquisition process comprises the following steps: 301, the terminal device reports electric quantity, and when the device monitors that the voltage electric quantity of the device changes, the sampled electric quantity data is sent to the intelligent gateway through an internet of things protocol;
the method comprises the following steps that 302, an intelligent gateway processes data, the intelligent gateway receives the data sent by equipment, translates and analyzes the data, and reports the data through a communication protocol agreed with a cloud platform after the data are obtained;
303, carrying out service processing on the cloud platform, wherein the cloud platform receives data sent by the intelligent gateway, translates and analyzes the data to obtain original data, and then stores the original data in a database;
304 database system for storing the raw data of the device, which can be relational or non-relational database;
the big data computing platform comprises the following processing flows: 201, after the electric quantity data of the terminal device changes, reporting to a cloud platform as a data source input module of a big data computing platform;
when the sampled electric quantity is smaller than the low electric quantity threshold value, calculating the maximum expected running time of the equipment according to the maximum electric quantity value and the time interval recorded by the minimum electric quantity value of the equipment data model, meanwhile, calculating the actual running time of the equipment according to the electric quantity time reported for the first time after the equipment is powered on and the current time interval of the system, and if the actual running time is longer than the maximum running time, carrying out early warning pushing.
More specifically, the algorithm module judges that the flow is shown in fig. 5. The intelligent terminal device reports the sampled electric quantity data; the algorithm module receives the sampling electric quantity reported by the equipment and compares the sampling electric quantity with a low electric quantity threshold value preset by the platform, if the current sampling electric quantity is larger than the low electric quantity threshold value, the last sampling value is replaced by the current sampling value, and the current sampling is finished; if the sampling electric quantity is smaller than the low electric quantity threshold value, calculating the difference value between the last sampling value and the current sampling; if the difference between the sampling and the last sampling is smaller than the maximum deviation value, replacing the last sampling value with the sampling value, and finishing the sampling; if the difference between the current sampling and the last sampling is larger than or equal to the maximum deviation value, calculating the average electric quantity of the equipment; inquiring the latest N sampling values of the equipment from a database according to the equipment code, removing a maximum value and a minimum value, then calculating the average value of N-2 data, if the average value is greater than a low-power threshold value, replacing the sampling value of the last time with the sampling value of this time, and finishing the sampling of this time; and if the average value is less than or equal to the low power threshold, carrying out early warning pushing.
Through this system, report to the cloud platform after intelligent terminal monitors that the electric quantity changes, the cloud platform records electric quantity data and through big data analysis, in time inform the user to change the equipment battery, avoid leading to the unable normal operating's of equipment problem because the electric quantity is not enough.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical solution according to the technical idea of the present invention falls within the protection scope of the present invention.
Claims (10)
1. A cloud-based low-power early warning method for a wireless terminal of an Internet of things is characterized by comprising the following steps:
after the electric quantity data of the wireless terminal is changed, reporting the real-time electric quantity to a cloud platform as an original data source of a big data computing platform;
the big data computing platform receives original data sent by the cloud platform, performs data cleaning, and stores electric quantity sampling data;
a low electric quantity threshold value and an electric quantity maximum deviation value are preset on the big data computing platform, and the big data computing platform carries out computation according to the currently reported electric quantity sampling data and judges whether push early warning is needed or not;
the judging method comprises the following steps: comparing the current electric quantity sampling data with a low electric quantity threshold value, and replacing the stored last electric quantity sampling data with the current electric quantity sampling data if the current electric quantity sampling data is larger than the low electric quantity threshold value; otherwise, calculating the difference value between the last electric quantity sampling data and the current electric quantity sampling data;
if the calculated difference value is smaller than the maximum electric quantity deviation value, replacing the existing maximum electric quantity deviation value with the calculated difference value; otherwise, calculating the average electric quantity of the wireless terminal;
inquiring the latest N sampling values of the wireless terminal, removing a maximum value and a minimum value, then calculating the average value of N-2 data, and if the average value is greater than a low-electric-quantity threshold value, replacing the last electric-quantity sampling data with the current electric-quantity sampling data; otherwise, early warning pushing is carried out.
2. The cloud-based low-power early warning method for the wireless terminal of the internet of things of the claim 1, wherein the method comprises the following steps: the wireless terminal reports the electric quantity, and when the wireless terminal monitors that the voltage electric quantity of the wireless terminal changes, the sampled electric quantity data are sent to the intelligent gateway through the Internet of things protocol.
3. The cloud-based internet of things wireless terminal low-power early warning method according to claim 1, wherein the data cleaning comprises: filtering data, wherein the original data comprises response data of a command issued by a cloud platform and actively reported data of a wireless terminal, and filtering the response data in the original data; and data classification, wherein the wireless terminal actively reports data including heartbeat data, equipment state data, alarm data and electric quantity sampling data, and classifies the electric quantity sampling data in the actively reported data.
4. The cloud-based internet of things wireless terminal low-power early warning method according to claim 1, wherein: after the big data computing platform stores the electric quantity sampling data, the data model is adjusted according to the electric quantity sampling data, and if the electric quantity sampling data is larger than the maximum electric quantity of the data model, the maximum electric quantity value and the reporting time of the wireless terminal are updated; and if the sampling electric quantity is smaller than the minimum electric quantity of the data model, updating the minimum electric quantity value and the reporting time of the wireless terminal.
5. The cloud-based Internet of things wireless terminal low-power early warning method according to claim 4, characterized in that: when the electric quantity sampling data is smaller than the low electric quantity threshold value, calculating the maximum operation time length of the wireless terminal according to the maximum electric quantity value and the time interval recorded by the minimum electric quantity value of the data model, meanwhile, calculating the actual operation time length of the equipment according to the electric quantity time reported for the first time after the wireless terminal is powered on and the current time interval of the system, and if the actual operation time length is larger than the maximum operation time length, carrying out early warning and pushing.
6. The cloud-based low-power early warning method for the wireless terminal of the internet of things of the claim 1, wherein the method comprises the following steps: the early warning pushing module checks the received electric quantity early warning information, and if a pushing record exists in an effective time range, the electric quantity early warning information is not pushed; and if the pushing record does not exist in the effective time, carrying out electric quantity early warning information and recording a pushing log.
7. The cloud-based internet of things wireless terminal low-power early warning method according to claim 1, wherein: when the early warning needs to be pushed, the big data computing platform returns the early warning information to the cloud platform, and the early warning information is pushed to the mobile terminal equipment of the user through an early warning pushing module of the cloud platform.
8. The utility model provides a low electric quantity early warning system of thing networking wireless terminal based on cloud which characterized in that: the system comprises a wireless terminal, an intelligent gateway, a cloud platform, a big data computing platform and mobile terminal equipment; the cloud platform and the wireless terminal are bridged through an intelligent gateway, so that real-time data communication is realized; the cloud platform is in communication connection with the mobile terminal device, so that safety authentication, data encryption and decryption and early warning pushing are realized; and is in bidirectional communication connection with a big data computing platform;
after monitoring that the voltage and the electric quantity of the wireless terminal change, the wireless terminal sends original data to the intelligent gateway through an Internet of things protocol; the intelligent gateway receives data sent by the wireless terminal, translates and analyzes the data, and reports the data through a communication protocol agreed with the cloud platform; the cloud platform receives data sent by the intelligent gateway, analyzes and translates the data, acquires original data and sends the original data to the big data computing platform;
the big data computing platform comprises a data acquisition module, a data cleaning module, a data modeling module, an algorithm module and a database; the data acquisition module receives original data sent by the cloud platform; the data cleaning module is used for filtering and classifying the original data and then storing the electric quantity sampling data into a database; the data modeling module adjusts the data model through the archived data; the algorithm module calculates according to the current electric quantity sampling data, the stored historical data and the data model, and judges whether early warning needs to be pushed or not, wherein the judgment method adopts the low-electric-quantity early warning method of the cloud-based wireless terminal of the Internet of things as claimed in any one of claims 1 to 7.
9. The cloud-based internet of things wireless terminal low-battery early warning system as claimed in claim 8, wherein: when the early warning needs to be pushed, the big data computing platform returns the early warning information to the cloud platform, and the early warning information is pushed to the mobile terminal equipment of the user through an early warning pushing module of the cloud platform.
10. The cloud-based internet of things wireless terminal low-battery early warning system according to claim 9, wherein: the early warning pushing module needs to be checked after receiving the early warning information, and if a pushing record exists in the effective time range, the information is not pushed, and the process is ended; and if the record is not pushed within the effective time, carrying out early warning pushing and recording a pushing log.
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