CN110401975A - A kind of method, apparatus and electronic equipment of the transmission power adjusting internet of things equipment - Google Patents
A kind of method, apparatus and electronic equipment of the transmission power adjusting internet of things equipment Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/06—TPC algorithms
- H04W52/14—Separate analysis of uplink or downlink
- H04W52/146—Uplink power control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
- H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
- H04W52/245—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account received signal strength
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
- H04W52/26—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service]
- H04W52/267—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service] taking into account the information rate
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Abstract
The present embodiments relate to internet of things field, disclose a kind of method of transmission power for adjusting internet of things equipment, device and electronic equipment, this method is by detecting and judging whether the signal quality for the wireless signal that internet of things equipment is emitted is lower than preset threshold, the environmental data of internet of things equipment local environment is acquired when being lower than preset threshold, and the optimum transmission power of internet of things equipment is calculated according to the environmental data, finally the optimum transmission power is sent to the internet of things equipment, so that internet of things equipment emits signal with optimum transmission power, the method of the transmission power of adjustment internet of things equipment provided in an embodiment of the present invention solves the problems, such as that traditional debugging scheme is cumbersome because of manpower debugging bring, provide a kind of intelligent regulator method.
Description
Technical Field
The embodiment of the invention relates to the technical field of Internet of things, in particular to a method and a device for adjusting the transmitting power of Internet of things equipment and electronic equipment.
Background
With the updating and iteration of the internet technology, the internet of things can realize the interconnection of everything in the future. Based on such development trend, more and more companies are currently on the market to research the ad-hoc network physical devices, i.e., the internet of things devices, or provide a specific internet of things scheme based on the original physical devices of the companies. As time goes by, the internet of things equipment exposed in the actual working environment for a long time is affected by weather and distance between the master equipment and the slave equipment in the actual working environment, and signal attenuation or network signal quality reduction may occur.
In the process of implementing the invention, the inventor finds that the following problems exist in the related art: the traditional equipment debugging scheme usually debugs wireless transmission parameters of equipment artificially, for example, adjusts transmission power and transmission frequency, observes network signal quality of the equipment, selects and adjusts the wireless transmission parameters with the best network signal quality, and realizes debugging of the equipment of the internet of things.
Disclosure of Invention
The embodiment of the invention mainly solves the technical problem of providing a method and a device for adjusting the transmitting power of Internet of things equipment and electronic equipment, and can solve the problem that manual operation is needed in the existing equipment debugging scheme.
In order to solve the above technical problem, in a first aspect, an embodiment of the present invention adopts a technical solution that: the method for adjusting the transmitting power of the Internet of things equipment comprises the following steps:
acquiring the signal quality of a wireless signal transmitted by the Internet of things equipment;
judging whether the signal quality is lower than a preset threshold value or not;
if so, acquiring environment data of the environment where the Internet of things equipment is located;
calculating the optimal transmitting power of the Internet of things equipment according to the environment data;
sending the optimal transmitting power to the Internet of things equipment so that the Internet of things equipment transmits signals at the optimal transmitting power;
wherein the environmental data includes at least one of transmission distance, temperature, humidity, wind speed, and lightning level.
Wherein, according to the environment data, calculating the optimal transmitting power of the internet of things equipment, further comprises:
inputting the environment data into a preset machine learning model;
and receiving the optimal transmitting power calculated by the preset machine learning model according to the environment data.
Wherein the method further comprises:
acquiring training samples, wherein the training samples comprise environmental data, transmission power and signal quality;
and inputting the training samples into a training model, and training the training model to obtain the preset machine learning model.
Wherein the training model is an extreme gradient lifting model.
In order to solve the above technical problem, in a second aspect, another technical solution adopted in the embodiment of the present invention is: the utility model provides a device of transmission power of adjustment thing networking equipment, includes:
the first acquisition module is used for acquiring the signal quality of a wireless signal transmitted by the Internet of things equipment;
the judging module is used for judging whether the signal quality is lower than a preset threshold value or not;
the second acquisition module is used for acquiring environmental data of the environment where the Internet of things equipment is located when the signal quality is lower than a preset threshold value, wherein the environmental data comprises at least one of transmission distance, temperature, humidity, wind speed and lightning level;
the computing module is used for computing the optimal transmitting power of the Internet of things equipment according to the environment data;
and the sending module is used for sending the optimal transmitting power to the Internet of things equipment so that the Internet of things equipment can transmit signals at the optimal transmitting power.
Wherein the calculation module is specifically configured to: inputting the environment data into a preset machine learning model; and receiving the optimal transmitting power calculated by the preset machine learning model according to the environment data.
Wherein the apparatus further comprises:
a third obtaining module, configured to obtain a training sample, where the training sample includes environment data, transmission power, and signal quality;
and the training module is used for inputting the training samples into a training model, training the training model and obtaining the preset machine learning model.
Wherein the training model is an extreme gradient lifting model.
In order to solve the foregoing technical problem, in a third aspect, an embodiment of the present invention further provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect as described above.
In order to solve the above technical problem, in a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the method according to the first aspect.
In order to solve the above technical problem, in a fifth aspect, the present invention further provides a computer program product, which includes a computer program stored on a computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, cause the computer to execute the method according to the first aspect.
The embodiment of the invention has the beneficial effects that: different from the situation of the prior art, the embodiment of the invention provides a method and a device for adjusting the transmission power of internet of things equipment and electronic equipment, the method comprises the steps of detecting and judging whether the signal quality of a wireless signal transmitted by the internet of things equipment is lower than a preset threshold value, acquiring environmental data of the environment where the internet of things equipment is located when the signal quality is lower than the preset threshold value, calculating the optimal transmission power of the internet of things equipment according to the environmental data, and finally sending the optimal transmission power to the internet of things equipment so that the internet of things equipment transmits the signal with the optimal transmission power.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below. It is obvious that the drawings described below are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
Fig. 1 is a schematic diagram of an exemplary system structure of an embodiment of a method for adjusting transmission power of an internet of things device according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for adjusting transmission power of an internet of things device according to an embodiment of the present invention;
FIG. 3 is a sub-flow diagram of step 140 of the method of FIG. 2;
fig. 4 is a flowchart of another method for adjusting the transmission power of the internet of things device according to the embodiment of the present invention;
fig. 5 is a schematic structural diagram of an apparatus for adjusting transmission power of an internet of things device according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of another apparatus for adjusting transmission power of an internet of things device according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that, if not conflicted, the various features of the embodiments of the invention may be combined with each other within the scope of protection of the invention. Additionally, while functional block divisions are performed in apparatus schematics, with logical sequences shown in flowcharts, in some cases, steps shown or described may be performed in sequences other than block divisions in apparatus or flowcharts.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Please refer to fig. 1, which is a schematic diagram of an exemplary system structure of an embodiment of a method for adjusting transmission power of an internet of things device according to the present invention. As shown in fig. 1, the system architecture 100 includes: internet of things devices 10a and 10b, a host internet of things device 20, and a cloud platform 30. The internet of things sub-devices 10a and 10b are connected with the host internet of things device 20, and the host internet of things device 20 is connected with the cloud platform 30. The connections may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The internet of things sub-devices 10a and 10b are sub-physical devices subordinate to the host internet of things device 20. The internet of things sub-devices 10a and 10b can detect the quality of network signals between the host internet of things device 20 and upload the related data of the quality of the network signals to the host internet of things device 20. The internet of things sub-devices 10a and 10b can also detect environment data of respective environments, and upload the environment data to the host internet of things device 20. The network signal may be a wireless signal, and the internet of things sub-devices 10a and 10b can detect the signal quality of the wireless signal with the host internet of things device 20.
In addition, the internet of things sub-devices 10a and 10b also have respective device numbers, that is, device IDs, and when the internet of things sub-devices 10a and 10b upload data to the host internet of things device 20, the respective uploaded data are marked by the device IDs on the internet of things sub-devices 10a and 10 b. It should be noted that, in an actual application environment, there are not necessarily two sub-physical devices subordinate to the host internet of things device 20, that is, the internet of things sub-devices 10a and 10b, and there may be one or more than two sub-physical devices.
The host internet of things device 20 is a host device of the internet of things sub-devices 10a and 10b, and is used for collecting, forwarding and sorting data uploaded by the internet of things sub-devices 10a and 10 b. Specifically, in the embodiment of the present invention, an MQTT (Message queue Telemetry Transport) client is further disposed in the host internet of things device 20, and the host internet of things device 20 can perform data interaction with the cloud platform 30 through the MQTT client.
In addition, a power adjusting transmitter (not shown) is further disposed inside or outside the host internet of things device 20, and after the power adjusting transmitter acquires new transmission power data, the transmission power of the host internet of things device 20 is adjusted to adjust the signal quality of the network signal output by the host internet of things device 20, so as to adjust the network connection speed and the data transmission amount between the host internet of things device and the internet of things sub-devices 10a and 10 b. The network connection speed and the data transmission quantity comprise the data uploading rate and the data downloading rate.
The cloud platform 30 can be in communication connection with the host internet of things device 20, the cloud platform 30 can acquire data uploaded by the host internet of things device 20, and the cloud platform 30 can also send a control command to the power adjusting transmitter of the host internet of things device 20 to adjust the transmitting power of the host internet of things device 20. The cloud platform 30 is provided therein with a cloud database, an MQTT server (not shown), and a processor (not shown).
The cloud database stores a machine learning model, and the processor of the cloud platform 30 can process the data uploaded by the host internet of things device 20 to obtain an input parameter. The processor of the cloud platform 30 may also call the machine learning model, substitute the input parameters into the machine learning model to perform data processing, so as to obtain an optimal transmission power, and then send the optimal transmission power to the power adjustment transmitter, so as to adjust the transmission power of the host internet of things device 20. The processor may be a cloud computing platform that enables data processing within the cloud platform 30.
The cloud platform 30 communicates with the host internet of things device 20 through the MQTT server. The cloud platform 30 establishes an MQTT communication protocol, i.e., a message queue telemetry transmission communication protocol, with the MQTT client in the host internet of things device 20 through the MQTT server, and data transmission between the cloud platform 30 and the host internet of things device 20 is realized through the protocol.
It should be understood that the numbers of the internet of things devices 10a and 10b, the host internet of things device 20, and the cloud platform 30 in fig. 1 are merely illustrative. There may be any number of internet of things devices 10a and 10b, host internet of things device 20, and cloud platform 30, as desired for the implementation.
Specifically, the embodiments of the present invention will be further explained below with reference to the drawings.
An embodiment of the present invention provides a method for adjusting the transmission power of an internet of things device, which can be executed by the system structure 100, please refer to fig. 2, which shows a flowchart of a method for adjusting the transmission power of an internet of things device applied by the system structure 100, and the method includes, but is not limited to, the following steps:
step 110: and acquiring the signal quality of the wireless signal transmitted by the Internet of things equipment.
In the embodiment of the present invention, the acquiring of the signal quality of the wireless signal transmitted by the internet of things device specifically includes acquiring the signal quality of the wireless signal transmitted by the host internet of things device through a signal strength collector or a sensor arranged on the sub device of the internet of things device, and uploading the acquired signal strength data to the host internet of things device. Taking fig. 1 as an example, the internet of things sub-devices are the internet of things sub-devices 10a and 10b, and the host internet of things device is the host internet of things device 20.
It can be understood that, when setting up the internet of things system, the transmission power of the host internet of things device 20 needs to be enough to cover all the child internet of things devices and provide a stable network signal. In practical application, the method is not limited to only two pieces of sub-Internet of things equipment. Therefore, the internet of things sub-devices 10a and 10b periodically collect the wireless signals when being connected with the host internet of things device 20, acquire and monitor the signal quality of the wireless signals of the host internet of things device 20, and upload the collected data to the host internet of things device 20.
For example, when the host internet of things device 20 is a base station and the internet of things sub-devices, that is, the internet of things sub-devices 10a and 10b are mobile terminals, the mobile terminals detect the network speed and upload the network speed data to the currently connected base station. It can be understood that, when the number of mobile terminals connected to the base station reaches a certain base number, the radiation range of the base station can cover the area range of the distance of the farthest terminal currently connected to the base station. And the number of the base stations can be more than one, when a plurality of base stations exist, the radiation ranges of at least two of the base stations can also intersect, and the mobile terminal located in the radiation range where the intersection exists can be selectively connected with one of the base stations through a network.
Step 120: and judging whether the signal quality is lower than a preset threshold value or not. If yes, go to step 130; if not, return to step 110.
The internet of things sub-devices 10a and 10b collect the signal quality of the wireless signal transmitted by the host internet of things device 20 and upload the signal quality to the host internet of things device 20, and then the host internet of things device 20 judges whether the uploaded signal quality is lower than a preset threshold value. If yes, further detecting the environmental data; if not, the signal quality acquired by the Internet of things sub-equipment is continuously acquired after a preset time interval. The preset time interval refers to the frequency at which the signal quality is collected and uploaded by the internet of things sub-devices 10a and 10b, and can be set according to the attenuation speed of the network signal.
In the embodiment of the present invention, the preset threshold refers to the minimum signal quality required by the internet of things subset which is farthest from the host internet of things device within the coverage area of the host internet of things device, the preset threshold needs to be preset according to the number of the internet of things subsets and the signal quality of the wireless signal required by the internet of things subset, and the preset threshold can be obtained through experiments and research before the host internet of things device and the corresponding internet of things subset are set.
Step 130: and acquiring environment data of the environment where the Internet of things equipment is located.
And when the signal quality uploaded by the IOT sub-equipment is determined to be lower than a preset threshold value, acquiring environmental data of the environment where the host IOT equipment is located. The host internet of things equipment is provided with various sensors to acquire various environmental data of the environment. The environmental data includes, but is not limited to, at least one of transmission distance, temperature, humidity, wind speed, and lightning level. The transmission distance refers to the transmission distance between the host internet of things device and the internet of things sub-device.
Further, in order to improve the accuracy of debugging, the environmental data of all internet of things sub-devices corresponding to the host internet of things device can be acquired, and accordingly, the internet of things sub-devices are required to be provided with sensors for acquiring the environmental data so as to acquire and upload the environmental data. And the internet of things sub-device is required to be provided with a device capable of performing information interaction with the host internet of things device and a corresponding communication protocol so as to acquire a control instruction for acquiring environmental data from the host internet of things device.
Step 140: and calculating the optimal transmitting power of the Internet of things equipment according to the environment data.
In the embodiment of the present invention, taking fig. 1 as an example, after the environmental data of the host internet of things device 20 is obtained, the optimal transmission power of the host internet of things device 20 is calculated according to the machine learning model pre-stored in the cloud database. The machine learning model can be obtained in advance through a machine learning training sample set. Specifically, a deep learning algorithm or a relevant algorithm for machine learning such as an XGBoost algorithm (extreme gradient boost model) may be used and obtained through iterative training.
Step 150: and sending the optimal transmitting power to the Internet of things equipment so that the Internet of things equipment transmits signals at the optimal transmitting power.
After the optimal transmitting power is obtained, the optimal transmitting power is sent to a power adjusting transmitter so as to adjust that the host Internet of things equipment can transmit signals with the optimal transmitting power, and the power debugging of the host Internet of things equipment is realized, so that the Internet of things sub-equipment connected with the host Internet of things equipment can obtain the optimal network signal quality.
The embodiment of the invention provides a method for adjusting the transmitting power of equipment of the Internet of things, which comprises the steps of detecting and judging whether the signal quality of a signal transmitted by the equipment of the Internet of things is lower than a preset threshold value, acquiring environmental data of the environment where the equipment of the Internet of things is located when the signal quality of the signal is lower than the preset threshold value, calculating the optimal transmitting power of the equipment of the Internet of things according to the environmental data, and finally sending the optimal transmitting power to the equipment of the Internet of things so that the equipment of the Internet of things transmits the signal at the optimal transmitting power.
In some embodiments, please refer to fig. 3, which shows a sub-flow of step 140 in the method of fig. 2, wherein step 140 specifically includes the following steps:
step 141: and inputting the environment data into a preset machine learning model.
Step 142: and receiving the optimal transmitting power calculated by the preset machine learning model according to the environment data.
In the embodiment of the invention, after the environmental data of the host internet of things device is acquired, the environmental data is input into a preset power transmitting neural network so as to calculate the optimal transmitting power and send the optimal transmitting power to the power adjusting transmitter, so that the power adjustment of the host internet of things device is realized. The preset machine learning model is a machine learning model which is based on a machine learning algorithm, can be continuously updated in an iterative manner and can obtain the optimal transmitting power according to the calculation of environmental parameters.
Taking the system structure shown in fig. 1 as an example, after obtaining the environmental data, the host internet of things device 20 uploads the environmental data to the MQTT client in the cloud platform 30, and the MQTT client reads the machine learning model stored in the cloud database, sends the environmental data and the power adjustment module to the processor of the cloud platform 30, and substitutes the environmental data into the machine learning model to calculate, so as to obtain the optimal transmitting power. And finally, the MQTT client sends the calculated final transmitting power to the power adjusting transmitter so as to adjust the transmitting power of the host Internet of things equipment 20.
Further, the processor inputs the calculated optimal transmitting power and the corresponding environmental parameters thereof into a machine learning model, and puts the optimal transmitting power and the corresponding environmental parameters thereof into machine learning as samples, so as to realize training of the machine learning model. The cloud platform 30 obtains the corresponding optimal transmission power by continuously obtaining new environmental data and calculating, and puts the environmental data and the corresponding optimal transmission power into the machine learning model for continuous iterative training, so as to obtain the optimal machine learning model.
In some embodiments, please refer to fig. 4, which shows another embodiment of a method for adjusting the transmission power of an internet of things device, where the embodiment is different from the above embodiment in that: the method for adjusting the transmitting power of the Internet of things equipment further comprises the following steps:
step 160: training samples are obtained, wherein the training samples comprise environmental data, transmission power and signal quality.
Step 170: and inputting the training samples into a training model, and training the training model to obtain the preset machine learning model.
The training model is an extreme gradient lifting model. Firstly, acquiring a training sample, preprocessing the training sample, specifically, firstly, acquiring algorithm characteristic parameters of physical equipment from the Internet, selecting the transmitting power with the optimal network signal quality and the corresponding algorithm characteristic parameters as the training sample, and forming a plurality of data records. In the embodiment of the present invention, the algorithm characteristic parameters of the physical device are specifically environmental data, transmission power, signal strength, signal quality, and the like, where the environmental data includes, but is not limited to, temperature, humidity, wind speed, lightning, distance, and the like. The distance refers to the distance between the host Internet of things equipment and the Internet of things sub-equipment.
Then, after collecting a plurality of groups of training samples, performing data processing on the training samples to obtain a training sample set, and labeling the transmitting power and corresponding characteristic parameters. For example, as shown in table (1) below, a table may be established to classify and sequence the transmit powers and corresponding characteristic parameters in the training sample set. Wherein the Qos represents a signal quality.
| Recording | Temperature of | Humidity | Wind speed | Thunder and lightning | Distance between two adjacent plates | Transmitting power | Qos |
| 1 | |||||||
| 2 | |||||||
| 3 | |||||||
| 4 |
Watch (1)
Finally, inputting each group of training samples in the training sample set into a machine learning model based on the XGboost algorithm one by one for training, and obtaining the machine learning model capable of obtaining the optimal transmitting power through continuous iterative training, namely the preset machine learning model.
Furthermore, because the quantity of training samples that can gather in the internet is limited, consequently, acquireing the environmental parameter of host computer thing networking equipment and substituting predetermine after machine learning model calculates and obtains its corresponding optimum transmitting power, and pass through the power regulation transmitter is adjusted after host computer thing networking equipment, through thing networking sub-equipment acquires the signal quality after adjusting transmitting power and uploads, will data such as the environmental parameter of thing networking equipment, optimum transmitting power and the signal strength after adjusting input as training samples predetermine machine learning model and carry out the iterative training, in order to realize right predetermine the update of machine learning model to obtain the optimum machine learning model of predetermineeing.
Referring to fig. 5, a schematic structural diagram of a device 200 for adjusting the transmission power of an internet of things device according to an embodiment of the present invention is provided, where the device 200 for adjusting the transmission power of an internet of things device includes: a first obtaining module 210, a judging module 220, a second obtaining module 230, a calculating module 240 and a sending module 250.
The first obtaining module 210 is configured to obtain signal quality of a wireless signal transmitted by the internet of things device.
The determining module 220 is configured to determine whether the signal quality is lower than a preset threshold.
The second obtaining module 230 is configured to obtain environmental data of an environment where the internet of things device is located when the signal quality is lower than a preset threshold, where the environmental data includes at least one of a transmission distance, a temperature, humidity, a wind speed, and a lightning level.
The calculating module 240 is configured to calculate an optimal transmitting power of the internet of things device according to the environment data.
The sending module 250 is configured to send the optimal transmission power to the internet of things device, so that the internet of things device sends a signal at the optimal transmission power.
In some embodiments, the calculation module 240 is specifically configured to: inputting the environment data into a preset machine learning model; and receiving the optimal transmitting power calculated by the preset machine learning model according to the environment data.
In some embodiments, referring to fig. 6, a schematic structural diagram of another apparatus 200 for adjusting transmission power of an internet of things device provided in the embodiments of the present invention is shown, based on the apparatus 200 for adjusting transmission power of an internet of things device shown in fig. 5, where the apparatus 200 for adjusting transmission power of an internet of things device further includes: a third acquisition module 260 and a training module 270.
The third obtaining module 260 is configured to obtain training samples, where the training samples include environmental data, transmission power, and signal quality.
The training module 270 is configured to input the training samples into a training model, train the training model, and obtain the preset machine learning model.
In some embodiments, the training model is an extreme gradient boost model.
It should be noted that, since the apparatus for adjusting the transmission power of the internet of things device in the present embodiment is based on the same inventive concept as the method embodiment described above, the corresponding content in the method embodiment is also applicable to the apparatus embodiment, and is not described in detail here.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device is a hardware structure capable of executing the method for adjusting the transmission power of the internet of things device shown in fig. 2 to 4. The electronic device 300 includes:
at least one processor 310; and a memory 320 communicatively coupled to the at least one processor 310, one processor 310 being illustrated in fig. 7. The memory 320 stores instructions executable by the at least one processor 310 to enable the at least one processor 310 to perform the method for adjusting transmit power of internet of things devices described above with reference to fig. 2-4. The processor 310 and the memory 320 may be connected by a bus or other means, and fig. 7 illustrates an example of a connection by a bus.
The memory 320 is a non-volatile computer-readable storage medium and may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions/modules corresponding to the method for adjusting the transmission power of the internet of things device in the embodiment of the present application, for example, the modules shown in fig. 5 to 6. The processor 310 executes various functional applications of the server and data processing by running nonvolatile software programs, instructions and modules stored in the memory 320, namely, implementing the method for adjusting the transmission power of the internet of things device according to the above method embodiment.
The memory 320 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the apparatus for adjusting transmission power of the internet of things device, and the like. Further, the memory 320 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 320 may optionally include memory located remotely from the processor 310, and such remote memory may be connected over a network to a means for adjusting the transmit power of the internet of things device. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 320, and when executed by the one or more processors 310, perform the method for adjusting the transmission power of the internet of things device in any of the above method embodiments, for example, perform the method steps of fig. 2 to 4 described above, and implement the functions of the modules and units in fig. 5 to 6.
The product can execute the method provided by the embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the methods provided in the embodiments of the present application.
Embodiments of the present invention also provide a non-transitory computer-readable storage medium storing computer-executable instructions for execution by one or more processors, for example, to perform the method steps of fig. 2-4 described above to implement the functions of the modules of fig. 5-6.
Embodiments of the present invention also provide a computer program product, including a computer program stored on a non-volatile computer-readable storage medium, where the computer program includes program instructions, which, when executed by a computer, cause the computer to perform the method for adjusting the transmission power of an internet of things device in any of the above-mentioned method embodiments, for example, to execute the method steps in fig. 2 to 4 described above, and implement the functions of the modules in fig. 5 to 6.
The embodiment of the invention provides a method, a device and electronic equipment for adjusting the transmitting power of equipment of the Internet of things, wherein the method comprises the steps of detecting and judging whether the signal quality of a wireless signal transmitted by the equipment of the Internet of things is lower than a preset threshold value, acquiring environmental data of the environment where the equipment of the Internet of things is located when the signal quality of the wireless signal is lower than the preset threshold value, calculating the optimal transmitting power of the equipment of the Internet of things according to the environmental data, and finally sending the optimal transmitting power to the equipment of the Internet of things so that the equipment of the Internet of things can transmit the signal at the optimal transmitting power.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a general hardware platform, and certainly can also be implemented by hardware. It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a computer readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; within the idea of the invention, also technical features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for adjusting the transmission power of Internet of things equipment is characterized by comprising the following steps:
acquiring the signal quality of a wireless signal transmitted by the Internet of things equipment;
judging whether the signal quality is lower than a preset threshold value or not;
if so, acquiring environment data of the environment where the Internet of things equipment is located;
calculating the optimal transmitting power of the Internet of things equipment according to the environment data;
sending the optimal transmitting power to the Internet of things equipment so that the Internet of things equipment transmits signals at the optimal transmitting power;
wherein the environmental data includes at least one of transmission distance, temperature, humidity, wind speed, and lightning level.
2. The method of claim 1,
the calculating the optimal transmitting power of the internet of things equipment according to the environment data further comprises:
inputting the environment data into a preset machine learning model;
and receiving the optimal transmitting power calculated by the preset machine learning model according to the environment data.
3. The method of claim 2, further comprising:
acquiring training samples, wherein the training samples comprise environmental data, transmission power and signal quality;
and inputting the training samples into a training model, and training the training model to obtain the preset machine learning model.
4. The method of claim 3, wherein the training model is an extreme gradient boost model.
5. An apparatus for adjusting transmission power of internet of things equipment, comprising:
the first acquisition module is used for acquiring the signal quality of a wireless signal transmitted by the Internet of things equipment;
the judging module is used for judging whether the signal quality is lower than a preset threshold value or not;
the second acquisition module is used for detecting environmental data of the environment where the Internet of things equipment is located when the signal quality is lower than a preset threshold value, wherein the environmental data comprises at least one of transmission distance, temperature, humidity, wind speed and lightning level;
the computing module is used for computing the optimal transmitting power of the Internet of things equipment according to the environment data;
and the sending module is used for sending the optimal transmitting power to the Internet of things equipment so that the Internet of things equipment can transmit signals at the optimal transmitting power.
6. The apparatus of claim 5,
the calculation module is specifically configured to: inputting the environment data into a preset machine learning model; and receiving the optimal transmitting power calculated by the preset machine learning model according to the environment data.
7. The apparatus of claim 6, further comprising:
a third obtaining module, configured to obtain a training sample, where the training sample includes environment data, transmission power, and signal quality;
and the training module is used for inputting the training samples into a training model, training the training model and obtaining the preset machine learning model.
8. The apparatus of claim 7,
the training model is an extreme gradient lifting model.
9. An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.
10. A non-transitory computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform the method of any one of claims 1-4.
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