Power Consumption Optimization Method for Location Tracking Devices Based on the Internet of Things

Abstract

The present invention discloses a method for optimizing the power consumption of a positioning and tracking device based on the Internet of Things, which relates to the technical field of power consumption optimization of positioning and tracking devices. Existing methods for optimizing the power consumption of positioning and tracking devices achieve precise positioning through various technologies such as GPS, cellular networks, Wi-Fi, and Bluetooth. However, these devices consume a large amount of electrical energy during continuous positioning and data transmission, resulting in insufficient battery life of the devices, especially in the case of battery power supply. The main reasons for this problem include high-frequency data acquisition and transmission, complex signal processing algorithms, and high power consumption of multiple wireless communication modules. Through this optimization method, the data affecting power consumption is analyzed and optimized, improving the battery life of the device, reducing unnecessary power consumption, enhancing the reliability and accuracy of signal transmission, ensuring that the device can operate efficiently in various complex environments, extending the service life of the device, and improving the overall performance and user experience.

Description

Technical Field

[0001] The present invention relates to the technical field of power consumption optimization of positioning and tracking devices, and specifically to a method for optimizing the power consumption of positioning and tracking devices based on the Internet of Things. Background Art

[0002] Positioning and tracking devices based on the Internet of Things (IoT) are widely used in fields such as logistics, traffic management, and environmental monitoring. They achieve precise positioning through various technologies such as GPS, cellular networks, Wi-Fi, and Bluetooth. However, these devices consume a large amount of electrical energy during continuous positioning and data transmission, resulting in insufficient battery life, especially in the case of battery-powered devices. The main reasons for this problem include high-frequency data collection and transmission, complex signal processing algorithms, and high energy consumption of multiple wireless communication modules. In addition, signal occlusion and interference in different environments also increase the difficulty of power consumption optimization. Therefore, there is an urgent need to develop low-power positioning algorithms, optimize communication protocols, and use more energy-efficient hardware designs to improve the battery life performance and application reliability of IoT positioning and tracking devices. Summary of the Invention

[0003] The purpose of the present invention is to propose a method for optimizing the power consumption of positioning and tracking devices based on the Internet of Things in order to solve the problems of high-frequency data collection and transmission, complex signal processing algorithms, high energy consumption of multiple wireless communication modules, and signal occlusion and interference in different environments that also increase the difficulty of power consumption optimization.

[0004] The purpose of the present invention can be achieved through the following technical solutions: A method for optimizing the power consumption of positioning and tracking devices based on the Internet of Things, the specific steps are as follows:

[0005] S100: Obtain the power consumption impact data of the positioning and tracking device based on the Internet of Things; the power consumption impact data includes the hardware data and software system data of the device itself and the external environment data;

[0006] S200: Optimize the hardware data of the positioning and tracking device itself, specifically:

[0007] S201: Analyze and optimize the communication connection between the hardware of the positioning and tracking device itself. First, evaluate the existing interfaces of the positioning and tracking device and confirm the types of various hardware interfaces used in the device; then obtain the data transmission requirements and determine the types of hardware interfaces used in the device through the requirements;

[0008] S202: Analyze the data transmission requirements, obtain and analyze the delay, bandwidth, and power consumption of each interface, and then calculate the transmission data requirement value for the transmission data requirements;

[0009] S300: Optimize the software system data, the specific process is as follows:

[0010] S301: Obtain the data to be processed by the software system, including the total amount of data, the difficulty level of the data, and the analysis time limit; the difficulty level of the data is assigned through the data scale and data quality, and then the weighted calculation is performed to obtain the difficulty level of the data;

[0011] S302: Then, through the formula Output the predicted power consumption value YJFZ for data processing, where s1 is the total amount of data, Ns is the difficulty level of the data, t1 is the analysis time limit; a1, a2, and a3 are all preset correction factors; match the predicted power consumption value YJFZ for data processing with the preset required data processing power consumption level interval;

[0012] S400: Analyze the external environment data, and the external environment data includes geographical location data, moving speed data, environmental temperature data, and signal strength data; specifically:

[0013] S401: Analyze the geographical location data to obtain the predicted received signal strength;

[0014] S402: Analyze the positioning and tracking device during movement to obtain the predicted moving received signal strength.

[0015] As a preferred embodiment of the present invention, the analysis of the demand for data transmission is specifically as follows:

[0016] Obtain and analyze the delay, bandwidth, and power consumption of each interface, calculate the demand for transmitting data, and obtain the data volume and transmission frequency of the transmitted data. Then, calculate the total bandwidth demand based on the data volume and transmission frequency, and match the total bandwidth demand with the preset peak bandwidth; then, obtain the maximum allowable delay during the transmission process of the transmitted data and the average delay during the transmission process of the transmitted data; then, detect the transmitted data to obtain the reliability after the transmitted data is transmitted; use a checksum and / or hash function to generate the check value of the data packet. After the data is transmitted, the receiving end calculates the check value of the received data packet and compares it with the check value of the sending end to confirm the consistency of the data; again, implement the confirmation mechanism, the receiving end sends a confirmation signal for each correctly received data packet, and the unconfirmed data packets are retransmitted; finally, count the transmission error rate and the number of retransmissions; the reliability is equal to a fixed value minus the transmission error rate multiplied by the corresponding preset weight factor, plus the number of retransmissions multiplied by the corresponding preset weight factor.

[0017] As a preferred embodiment of the present invention, the calculation of the demand for transmitted data to obtain the transmitted data demand value is specifically as follows:

[0018] Through the formula Output the transmission data requirement value SJXZ, where α, β, δ, χ, and ε are the total bandwidth, peak bandwidth, maximum allowable delay duration, average delay duration, and reliability value respectively; b1, b2, b3, b4, and b5 are all corresponding preset weight factors; match the transmission data requirement value SJXZ with the preset data transmission requirement intervals of various hardware interface types; if the transmission data requirement value SJXZ belongs to the preset data transmission requirement interval of the I2C hardware interface type, select the I2C hardware interface type; if the transmission data requirement value SJXZ belongs to the preset data transmission requirement interval of the SPI hardware interface type, select the SPI hardware interface type; if the transmission data requirement value SJXZ belongs to the preset data transmission requirement interval of the UART hardware interface type, select the UART hardware interface type; if the transmission data requirement value SJXZ belongs to the preset data transmission requirement interval of the GPIO hardware interface type, select the GPIO hardware interface type; select a hardware interface type other than the corresponding hardware interface type for deep sleep.

[0019] As a preferred embodiment of the present invention, match the predicted power consumption value YJFZ of data processing with the preset required data processing power consumption level intervals, specifically:

[0020] The preset required data processing power consumption level intervals include processing power consumption level interval one, processing power consumption level interval two, processing power consumption level interval three, processing power consumption level interval four, and processing power consumption level interval five; if the predicted power consumption value YJFZ of data processing belongs to processing power consumption level interval one, generate a processing power consumption level one signal and control the device to process data at power consumption level one; if the predicted power consumption value YJFZ of data processing belongs to processing power consumption level interval two, generate a processing power consumption level two signal and control the device to process data at power consumption level two; if the predicted power consumption value YJFZ of data processing belongs to processing power consumption level interval three, generate a processing power consumption level three signal and control the device to process data at power consumption level three; if the predicted power consumption value YJFZ of data processing belongs to processing power consumption level interval four, generate a processing power consumption level four signal and control the device to process data at power consumption level four; if the predicted power consumption value YJFZ of data processing belongs to processing power consumption level interval five, generate a processing power consumption level five signal and control the device to process data at power consumption level five.

[0021] As a preferred embodiment of the present invention, the specific process of analyzing the geographical location data is:

[0022] Record the geographical location information through the positioning module, and analyze the signal strength and occlusion situation in combination with map data; if the geographical location information recorded by the positioning module and combined with the map data is a mountainous area, then obtain the longitude, latitude and altitude of the geographical location information, as well as obtain the terrain data and map data; if the geographical location information recorded by the positioning module and combined with the map data is a forest or an area with dense cities and high-rise buildings, then obtain the terrain data and map data by obtaining the geographical location information, and obtain the terrain height profile between the emission point and the receiving point according to the obtained geographical location information. If the height of a certain point in the path exceeds the straight-line height between the emission point and the receiving point, it is regarded as having occlusion, and obtain the height of the occluder and the distance from the occluder to the receiving point; calculate the expected received signal strength, and match it with the preset transmission intensity interval. If the expected received signal strength belongs to transmission intensity interval one, then control the signal transmitter to increase the intensity of the transmitted signal and increase it by 1% of the current intensity of the transmitted signal. If the expected received signal strength r belongs to transmission intensity interval two, then control the signal transmitter to increase the intensity of the transmitted signal and increase it by 2% of the current intensity of the transmitted signal; if the expected received signal strength belongs to transmission intensity interval two hundred, then control the signal transmitter to increase the intensity of the transmitted signal and increase it by 200% of the current intensity of the transmitted signal.

[0023] As a preferred embodiment of the present invention, the specific process of analyzing the positioning and tracking device during movement is as follows:

[0024] Obtain the geographical location information of the positioning and tracking device through the positioning module to obtain the moving speed of the positioning and tracking device; then, through the change of the environmental data during the movement of the positioning and tracking device, and then obtain the real-time expected received signal strength S r Perform the calculation of the expected mobile received signal strength to obtain the expected mobile received signal strength, and then substitute the real-time expected received signal strength into the curve graph to obtain the expected mobile received signal strength curve graph; then analyze the data in the graph to obtain the slope value, and compare it with the corresponding preset execution range of the slope value; the corresponding preset execution range of the slope value is execution range one, execution range two and execution range three; if the slope value belongs to execution range one, then increase the signal strength of the current transmitted signal; if the slope value belongs to execution range two, then keep the current signal strength of the transmitted signal unchanged; if the slope value belongs to execution range three, then decrease the signal strength of the current transmitted signal.

[0025] Compared with the prior art, the beneficial effects of the present invention are:

[0026] 1. By optimizing the hardware data transmission method of the positioning and tracking device itself, the present invention can significantly improve the power consumption efficiency and overall performance of the device. The specific implementation includes analyzing and optimizing the communication connections of each hardware interface, and selecting the most suitable hardware interface type according to the actual data transmission requirements. This optimization method not only improves the data transmission efficiency, reduces the power consumption, but also ensures the reliability and accuracy of data transmission, greatly extends the battery life of the positioning and tracking device, and improves the overall reliability of the device and the adaptability of the application scenario.

[0027] 2. By optimizing the data processing of the software system, the present invention can significantly improve the energy efficiency and performance of the positioning and tracking device. The specific process includes first analyzing the data to be processed by the software system, and evaluating the total amount of data, difficulty level, and analysis timeliness. The data difficulty level is evaluated through the data scale and data quality. The data scale is assigned according to the size of the data set and the storage space, and the data quality is assigned by checking missing values, duplicate values, and outliers, and consistency verification is performed. This method can not only effectively reduce the power consumption while meeting the data processing requirements, but also dynamically adjust the power consumption level according to the changes in the data processing requirements, thereby extending the battery life of the device, improving the overall operation efficiency and reliability, and ensuring the timeliness and accuracy of data processing.

[0028] 3. By analyzing and optimizing the external environment data, the present invention can significantly improve the power consumption management and signal transmission efficiency of the positioning and tracking device. The specific process includes: analyzing the geographical location data, and evaluating the signal strength and occlusion situation in combination with the map data; in addition, by analyzing the moving speed of the device, and dynamically adjusting the signal transmission intensity in combination with the real-time environmental data changes, to ensure the stability of signal transmission and the minimization of power consumption during the movement. This optimization method not only improves the battery life of the device, reduces unnecessary energy consumption, but also enhances the reliability and accuracy of signal transmission, ensures that the device can operate efficiently in various complex environments, and at the same time extends the service life of the device, improves the overall performance and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings.

[0030] Figure 1 It is a method step diagram of the present invention;

[0031] Figure 2 It is a predicted moving received signal strength curve diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0032] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0033] It should be understood that the terms "including" and "comprising" used in the specification and claims of this disclosure indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0034] It should also be understood that the terms used in this disclosure specification are only for the purpose of describing specific embodiments and are not intended to limit this disclosure. As used in this disclosure specification and claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms. It should also be further understood that the term "and / or" used in this disclosure specification and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0035] Please refer to Figure 1 As shown, a method for optimizing the power consumption of a positioning and tracking device based on the Internet of Things, the specific steps are as follows:

[0036] S100: Obtain the power consumption impact data of the positioning and tracking device through the corresponding sensors and the Internet of Things; the power consumption impact data includes the hardware data and software system data of the device itself and the external environment data;

[0037] S200: Optimize the hardware data of the positioning and tracking device itself, specifically:

[0038] S201: Analyze and optimize the communication connection between the hardware of the positioning and tracking device itself; first, evaluate the existing interfaces of the positioning and tracking device and confirm the types of various hardware interfaces used in the device, such as I2C, SPI, UART, and GPIO, etc.; then, obtain the requirements for data transmission, and then determine the types of hardware interfaces used in the device according to the requirements;

[0039] S202: Analyze the requirements for data transmission; by obtaining and analyzing the latency, bandwidth, and power consumption of each interface; then calculate the requirements for transmitting data, and by obtaining the data volume and transmission frequency of the transmitted data, calculate the total bandwidth requirement according to the data volume and transmission frequency, and match the total bandwidth requirement with the preset peak bandwidth; then obtain the maximum allowable latency during the transmission of the transmitted data and the average latency during the transmission of the transmitted data; then detect the transmitted data to obtain the reliability after the transmission of the transmitted data; then generate the check value of the data packet by using a checksum (such as CRC) or a hash function to ensure the integrity before data transmission. After data transmission, the receiving end calculates the check value of the received data packet and compares it with the check value of the sending end to confirm the consistency of the data; again, implement a confirmation mechanism (such as ACK / NACK), the receiving end sends a confirmation signal for each correctly received data packet, and the unconfirmed data packets are retransmitted; finally, by counting the transmission error rate and the number of retransmissions; the reliability value (the reliability value is the numerical value corresponding to the reliability) is equal to a fixed value minus the transmission error rate multiplied by the corresponding preset weight factor plus the number of retransmissions multiplied by the corresponding preset weight factor; that is, ε = GD - (CW1×es1 + CW2×es2), where GD is the fixed value, and the value is customarily set by those skilled in the art, and CW1 and CW2 are the numerical values of the transmission error rate and the number of retransmissions; es1 and es2 are the preset weight factors corresponding to the transmission error rate and the number of retransmissions respectively.

[0040] Then, through the formula Output the transmission data requirement value SJXZ. Among them, α, β, δ, χ, and ε are the numerical values corresponding to the total bandwidth, peak bandwidth, maximum allowable latency duration, average latency duration, and reliability value respectively; b1, b2, b3, b4, and b5 are all the corresponding preset weight factors; then match the transmission data requirement value SJXZ with the preset data transmission requirement intervals of various hardware interface types; if the transmission data requirement value SJXZ belongs to the preset data transmission requirement interval of the I2C hardware interface type, then select the I2C hardware interface type; if the transmission data requirement value SJXZ belongs to the preset data transmission requirement interval of the SPI hardware interface type, then select the SPI hardware interface type; if the transmission data requirement value SJXZ belongs to the preset data transmission requirement interval of the UART hardware interface type, then select the UART hardware interface type; if the transmission data requirement value SJXZ belongs to the preset data transmission requirement interval of the GPIO hardware interface type, then select the GPIO hardware interface type; select the hardware interface types other than the corresponding hardware interface types to enter deep sleep.

[0041] S300: Optimize the data of the software system. The specific process is as follows:

[0042] S301: Analyze the data required for the software system. The analysis information of the data to be processed includes the total amount of data, data difficulty, and analysis time limit. The data difficulty is determined by analyzing the data scale (the size, number of rows, number of columns, and storage space of the data set) and data quality (using tools such as Pandas to check whether there are missing values, duplicate values, and outliers in the data to ensure data integrity; for data consistency, check whether the data conforms to the expected format and range, such as date format and numerical range, and can use regular expressions and data validation libraries such as Cerberus for verification). Then, assign values based on the data scale and data quality (assign values according to the size of the data scale, the larger the scale, the larger the assigned value for the data scale; assign values according to the quality of the data, the better the quality, the smaller the assigned value for the data quality). Then, perform a weighted calculation on the assigned value of the data scale and the assigned value of the data quality to obtain the data difficulty.

[0043] S302: Then, through the formula Output the predicted power consumption value YJFZ for data processing, where s1 is the total amount of data, Ns is the data difficulty, and t1 is the analysis time limit; a1, a2, and a3 are all preset correction factors. Then, match the predicted power consumption value YJFZ for data processing with the preset required data processing power consumption level intervals, which are processing power consumption level interval one, processing power consumption level interval two, processing power consumption level interval three, processing power consumption level interval four, and processing power consumption level interval five. If the predicted power consumption value YJFZ for data processing belongs to processing power consumption level interval one, generate a processing power consumption level one signal and control the device to process data at power consumption level one; if the predicted power consumption value YJFZ for data processing belongs to processing power consumption level interval two, generate a processing power consumption level two signal and control the device to process data at power consumption level two; if the predicted power consumption value YJFZ for data processing belongs to processing power consumption level interval three, generate a processing power consumption level three signal and control the device to process data at power consumption level three; if the predicted power consumption value YJFZ for data processing belongs to processing power consumption level interval four, generate a processing power consumption level four signal and control the device to process data at power consumption level four; if the predicted power consumption value YJFZ for data processing belongs to processing power consumption level interval five, generate a processing power consumption level five signal and control the device to process data at power consumption level five.

[0044] S400: Analyze the external environment data, which includes geographical location data, moving speed data, environmental temperature data, and signal strength data. Specifically:

[0045] S401: Analyze the geographical location data, which includes mountainous areas, cities, areas with dense high-rise buildings, etc. (It should be noted that different geographical locations will affect the positioning signal strength and positioning accuracy, and thus affect the power consumption of the device); record the geographical location information through the positioning module, and analyze the signal strength and occlusion situation in combination with map data (such as terrain and buildings); if the geographical location information recorded by the positioning module and combined with the map data is a mountainous area, then obtain the longitude, latitude and altitude of the geographical location information, as well as obtain the terrain data and map data; if the geographical location information recorded by the positioning module and combined with the map data is a forest or a city or an area with dense high-rise buildings, then obtain the terrain data and map data by obtaining the geographical location information, and obtain the terrain height profile between the transmitter and the receiver according to the obtained geographical location information. If the height of a certain point in the path exceeds the straight-line height between the transmitter and the receiver, it is regarded as having occlusion, and obtain the height of the occluder and the distance from the occluder to the receiver;

[0046] Then, through the formula Output the predicted received signal strength S r , where PL(d) is the path loss at a distance of d, PL(d0) is the path loss at the reference distance d0, n is the path loss exponent, d is the distance between the transmitter and the receiver, β is a constant related to the environment, h 遮挡 is the height of the occluder, d 遮挡 is the distance from the occluder to the receiver, S t is the transmitted signal strength, n 遮挡 is the occlusion loss, ∑n 遮挡 is the sum of all occlusion losses; and match the predicted received signal strength S r with the preset transmission intensity intervals. The preset transmission intensity intervals are preset transmission intensity interval one, preset transmission intensity interval two,..., preset transmission intensity interval two hundred; if the predicted received signal strength S r belongs to preset transmission intensity interval one, then control the signal transmitter to increase the intensity of the transmitted signal, and increase it by 1% of the current intensity of the transmitted signal, and obtain the power consumption of the signal intensity; if the predicted received signal strength S r belongs to preset transmission intensity interval two, then control the signal transmitter to increase the intensity of the transmitted signal, and increase it by 2% of the current intensity of the transmitted signal, and obtain the power consumption of the signal intensity; if the predicted received signal strength S r belongs to preset transmission intensity interval two hundred, then control the signal transmitter to increase the intensity of the transmitted signal, and increase it by 200% of the current intensity of the transmitted signal, and obtain the power consumption of the signal intensity;

[0047] S402: By analyzing the location tracking device when it is moving, the location tracking device's geographic location information is obtained through the positioning module to obtain the moving speed of the location tracking device; then, by analyzing the environmental data changes during the movement of the location tracking device, the real-time estimated received signal strength S is obtained. r Calculate the expected mobile received signal strength and output the expected mobile received signal strength S through the formula Sy = Sr-v×τ y , where v is the moving speed of the positioning and tracking device, and τ is the signal strength influence coefficient corresponding to the moving speed of the positioning and tracking device;

[0048] See also Figure 2 As shown, the real-time estimated received signal strength S y Substitute the data into the curve to obtain the estimated mobile received signal strength curve; then set a fixed time interval (the fixed time interval is t1-t2; the real-time estimated received signal strength S calculated during the mobile process is calculated) y The corresponding time is marked as t1; then based on t1 as the starting point, move forward a fixed time according to the time axis, marked as t2;), and marked as t; then calculate through the slope within the fixed time interval t, and obtain the estimated received signal strength S y The two intersection points of the curve and the fixed time interval t are marked as J1 and J2; the slope value is calculated by J1 and J2, and the slope value is compared with the preset execution range corresponding to the slope value; the preset execution ranges corresponding to the slope value are execution range 1, execution range 2 and execution range 3; if the slope value belongs to execution range 1, the current strength of the transmitted signal is increased, and the mobile receiving signal strength S is estimated y Match with the preset transmission strength range; if the slope value belongs to the execution range 2, the current signal strength of the transmission signal remains unchanged; if the slope value belongs to the execution range 3, the current strength of the transmission signal is reduced, and the mobile receiving signal strength S is estimated. y Match with the preset transmission strength interval; similarly, if the expected mobile receiving signal strength S y When the preset transmission intensity range is 1, the control signal transmitter increases the intensity of the transmission signal and increases the current intensity of the transmission signal by 1% to obtain the power consumption of the signal intensity; if the mobile receiving signal intensity S is expected to be y When the preset intensity range is 2, the signal transmitter is controlled to increase the intensity of the transmitted signal and increase the current intensity of the transmitted signal by 2% to obtain the power consumption of the signal intensity; if the mobile receiving signal intensity S is expected to be y When the preset transmission intensity range is 200, the signal transmitting end is controlled to increase the intensity of the transmission signal and increase the current intensity of the transmission signal by 200% to obtain the power consumption of the signal intensity.

[0049] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation manners. Obviously, according to the content of this specification, many modifications and variations can be made. These embodiments are selected and specifically described in this specification in order to better explain the principle and practical application of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A method for optimizing power consumption of a positioning and tracking device based on the Internet of Things, the specific steps are as follows: S100: Obtain power consumption impact data of positioning and tracking devices based on the Internet of Things; The power consumption impact data includes the device’s own hardware data, software system data, and external environment data; S200: Optimizing the hardware data of the positioning and tracking device itself, specifically: S201: Analyze and optimize the communication connection between the hardware of the positioning and tracking device itself, first evaluate the existing interface of the positioning and tracking device, and confirm the various hardware interface types used in the device; then obtain the data transmission requirements, and determine the hardware interface type used in the device according to the requirements; S202: Analyze the demand for data transmission, obtain and analyze the delay, bandwidth and power consumption of each interface, calculate the demand for data transmission, and obtain the data volume and transmission frequency of the transmitted data, then calculate the total bandwidth demand based on the data volume and transmission frequency, and match the total bandwidth demand with the preset peak bandwidth; then measure the maximum allowable delay in the data transmission process and the average delay in the data transmission process; then detect the transmitted data to obtain the reliability of the transmitted data; use the checksum and / or hash function to generate the check value of the data packet, after the data transmission, the receiving end calculates the check value of the received data packet and compares it with the check value of the sending end to confirm the consistency of the data; again, implement the confirmation mechanism, the receiving end sends a confirmation signal for each correctly received data packet, and retransmits the unconfirmed data packet; finally, count the transmission error rate and the number of retransmissions; The reliability value is equal to the fixed value minus the transmission error rate multiplied by the corresponding preset weight factor, plus the number of retransmissions multiplied by the corresponding preset weight factor, and then the transmission data demand is calculated to obtain the transmission data demand value, which is obtained by the formula Output the transmission data demand value SJXZ, where α, β, δ, χ and ε are the values ​​corresponding to the total bandwidth, peak bandwidth, maximum allowable delay time, average delay time and reliability value respectively; b1, b2, b3, b4 and b5 are the corresponding preset weight factors; match the transmission data demand value SJXZ with the data transmission demand interval preset by various hardware interface types; if the transmission data demand value SJXZ belongs to the data transmission demand interval preset by the I2C hardware interface type, select the I2C hardware interface type; if the transmission data demand value SJXZ belongs to the data transmission demand interval preset by the SPI hardware interface type, select the SPI hardware interface type; if the transmission data demand value SJXZ belongs to the data transmission demand interval preset by the UART hardware interface type, select the UART hardware interface type; if the transmission data demand value SJXZ belongs to the data transmission demand interval preset by the GPIO hardware interface type, select the GPIO hardware interface type; select a hardware interface type other than the corresponding hardware interface type for deep sleep; S300: Optimize the software system data. The specific process is as follows: S301: Obtain the data that the software system needs to process, including the total amount of data, data difficulty, and analysis timeliness; the data difficulty is assigned by the data scale and data quality, and then weighted calculation is performed to obtain the data difficulty; S302: Then through the formula Output the estimated power consumption value YJFZ for data processing, where s1 is the total amount of data, Ns is the data difficulty, and t1 is the analysis time; a1, a2, and a3 are all preset correction factors; match the estimated power consumption value YJFZ for data processing with the preset required data processing power consumption level range; S400: Analyze the external environment data, where the external environment data includes geographic location data, moving speed data, ambient temperature data, and signal strength data; specifically: S401: Analyze the geographic location data, record the geographic location information through the positioning module, and analyze the signal strength and obstruction in combination with the map data; if the positioning module records the geographic location information and combines the map data to show that it is a mountainous area, then obtain the longitude, latitude and altitude of the geographic location information and obtain the terrain data and map data; if the positioning module records the geographic location information and combines the map data to show that it is a forest or a city or a high-rise building dense area, then obtain the terrain data and map data by obtaining the geographic location information, and obtain the terrain height profile between the transmitting point and the receiving point based on the acquired geographic location information. If the height of a point in the path exceeds the straight line height between the transmitting point and the receiving point, it is considered to be obstructed, and the height of the obstruction and the distance from the obstruction to the receiving point are obtained; the expected received signal strength is obtained by calculation, and it is matched with the preset transmission strength interval. If the expected received signal strength belongs to the transmission strength interval one, the signal transmitting end is controlled to increase the strength of the transmitted signal, and increase the current strength of the transmitted signal by 1%. If the expected received signal strength r When it belongs to the transmission strength interval 2, the control signal transmitting end increases the strength of the transmission signal and increases it by 2% of the current strength of the transmission signal; if the expected received signal strength belongs to the transmission strength interval 200, the control signal transmitting end increases the strength of the transmission signal and increases it by 200% of the current strength of the transmission signal; S402: Analyze the positioning and tracking device when it moves to obtain the expected mobile received signal strength.

2. The method for optimizing power consumption of a positioning and tracking device based on the Internet of Things according to claim 1, characterized in that: Match the estimated data processing power consumption value YJFZ with the preset required data processing power consumption level range, specifically: The preset required data processing power consumption level intervals include processing power consumption level interval one, processing power consumption level interval two, processing power consumption level interval three, processing power consumption level interval four and processing power consumption level interval five; if the data processing estimated power consumption value YJFZ belongs to the processing power consumption level interval one, a processing power consumption level one signal is generated, and the device is controlled to process data at power consumption level one; if the data processing estimated power consumption value YJFZ belongs to the processing power consumption level interval two, a processing power consumption level two signal is generated, and the device is controlled to process data at power consumption level two; if the data processing estimated power consumption value YJFZ belongs to the processing power consumption level interval three, a processing power consumption level three signal is generated, and the device is controlled to process data at power consumption level three; if the data processing estimated power consumption value YJFZ belongs to the processing power consumption level interval four, a processing power consumption level four signal is generated, and the device is controlled to process data at power consumption level four; if the data processing estimated power consumption value YJFZ belongs to the processing power consumption level interval five, a processing power consumption level five signal is generated, and the device is controlled to process data at power consumption level five.

3. The method for optimizing power consumption of a positioning and tracking device based on the Internet of Things according to claim 1, characterized in that: The specific process of analyzing the positioning tracking device while it is moving is as follows: The location information of the positioning and tracking device is obtained through the positioning module to obtain the moving speed of the positioning and tracking device; then the environmental data changes during the movement of the positioning and tracking device are analyzed, and the real-time estimated received signal strength S is obtained. r Calculate the estimated mobile received signal strength to obtain the estimated mobile received signal strength, and then substitute the real-time estimated received signal strength into the curve graph to obtain the estimated mobile received signal strength curve graph; Then, the slope value is obtained by analyzing the data in the figure, and it is compared with the preset execution range corresponding to the slope value; the preset execution range corresponding to the slope value is execution range 1, execution range 2 and execution range 3; if the slope value belongs to execution range 1, the current strength of the transmitted signal is increased; if the slope value belongs to execution range 2, the current strength of the transmitted signal remains unchanged; If the slope value belongs to execution range three, the current strength of the transmitted signal is reduced.

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