Internet of Things equipment positioning method based on base station information

Abstract

The invention is suitable for the technical field of Internet of Things, and provides an Internet of Things equipment positioning method based on base station information, and the method comprises the following steps: enabling Internet of Things equipment to access a mobile communication network through a wireless communication module; information of at least three surrounding base stations is collected through a communication protocol, the information of the base stations comprises base station IDs and signal intensities, and base station coordinates are determined through the base station IDs; preliminarily determining the distance between the Internet of Things equipment and each base station according to the signal intensity and the coordinates of the base stations, and calculating the preliminary coordinates of the Internet of Things equipment by adopting a triangulation positioning algorithm; determining a comprehensive path loss index of signal propagation according to the initial coordinates, the base station coordinates and an electronic map; and correcting the distance between the Internet of Things equipment and the base station according to the comprehensive path loss index to obtain a corrected coordinate of the Internet of Things equipment. According to the method, the correction coordinates consider the influence of various factors such as buildings and terrains, the positioning is more accurate, and the use cost is lower.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a method for positioning Internet of Things devices based on base station information. Background Art

[0002] With the rapid development of Internet of Things technology, the application scenarios of Internet of Things devices are becoming more and more extensive. From smart homes to smart cities, Internet of Things devices have penetrated into all aspects of our lives. In these application scenarios, accurate positioning of Internet of Things devices has become one of the key technologies for realizing intelligent management and services. Traditional Internet of Things device positioning methods mainly rely on satellite positioning technologies such as GPS. However, installing GPS devices in Internet of Things devices will increase costs. In indoor environments or areas with poor satellite signal coverage, the accuracy of GPS positioning will be seriously affected, and it cannot meet the needs of high-precision positioning of Internet of Things devices. In recent years, base station positioning technology based on mobile communication networks has attracted much attention due to its wide coverage and low cost. As a signal transmission source, the base station in the mobile communication network has known and stable location information. By measuring parameters such as the signal strength between the Internet of Things device and the base station, the positioning of the Internet of Things device can be achieved. However, since the signal propagation process will be affected by various factors such as buildings and terrain, there is a certain deviation between the signal strength and the actual distance between the Internet of Things device and the base station, which affects the accuracy of positioning. Therefore, it is necessary to provide an Internet of Things device positioning method based on base station information to solve the above problems. Summary of the invention

[0003] In view of the shortcomings of the prior art, the purpose of the present invention is to provide an Internet of Things device positioning method based on base station information to solve the problems existing in the above-mentioned background technology.

[0004] The present invention is implemented as follows: a method for locating an Internet of Things device based on base station information, the method comprising the following steps:

[0005] Enable IoT devices to access mobile communication networks through wireless communication modules;

[0006] Collect information of at least three surrounding base stations through a communication protocol, wherein the base station information includes a base station ID and a signal strength, and determine the base station coordinates through the base station ID;

[0007] The distance between the IoT device and each base station is preliminarily determined based on the signal strength and base station coordinates, and the preliminary coordinates of the IoT device are calculated using a triangulation positioning algorithm;

[0008] Determine the comprehensive path loss index of signal propagation based on the preliminary coordinates, base station coordinates and electronic map;

[0009] The distance between the IoT device and the base station is corrected according to the comprehensive path loss index to obtain the corrected coordinates of the IoT device.

[0010] As a further solution of the present invention: the step of preliminarily determining the distance between the IoT device and each base station according to the signal strength and the base station coordinates, and using the triangulation positioning algorithm to calculate the preliminary coordinates of the IoT device specifically includes:

[0011] Based on the logarithmic distance path loss model, the distance between the IoT device and each base station is calculated according to the signal strength and base station coordinates;

[0012] Extract three of the information of several base stations at random to obtain a base station group, list all the base station groups, and calculate the preliminary coordinates corresponding to each base station group based on the triangulation positioning algorithm;

[0013] Several preliminary coordinates are analyzed to obtain final preliminary coordinates.

[0014] As a further solution of the present invention: the step of analyzing a plurality of preliminary coordinates to obtain the final preliminary coordinates specifically includes:

[0015] Count the frequency of occurrence of each preliminary coordinate among all preliminary coordinates;

[0016] According to the distribution of the preliminary coordinates, the abnormally deviated preliminary coordinates are eliminated based on the mean and standard deviation;

[0017] For the remaining preliminary coordinates, the weighted average coordinates are calculated according to their occurrence frequencies. The weighted average coordinates are the final preliminary coordinates. w i Represents the coordinates (x i ,y i ), M is the number of remaining preliminary coordinates, (x final ,y final ) represents the weighted average coordinate.

[0018] As a further solution of the present invention: the step of determining the comprehensive path loss index of signal propagation according to the preliminary coordinates, the base station coordinates and the electronic map specifically includes:

[0019] Importing the preliminary coordinates and the base station coordinates into an electronic map to determine a signal transmission path, wherein the electronic map includes terrain data, building data, and vegetation data to determine environmental factors along the signal transmission path;

[0020] Determine the adjustment coefficient, building blocking factor and vegetation attenuation factor in the signal transmission process according to environmental factors;

[0021] Retrieve the basic path loss index n b, the adjustment coefficient t1, building blocking factor t2 and vegetation attenuation factor t3 are applied to the basic path loss index to calculate the comprehensive path loss index n c , n c =n b ×(1+t1)×(1+t2)×(1+t3).

[0022] As a further solution of the present invention: the step of determining the adjustment coefficient, the building blocking factor and the vegetation attenuation factor in the signal transmission process according to environmental factors specifically includes:

[0023] Input terrain information in environmental factors into the terrain adjustment library and output the corresponding adjustment coefficient;

[0024] Extracting building information from environmental factors, determining the blocking area and density factor of the building according to the building information, and calculating the building blocking factor according to the building blocking area and density factor;

[0025] Extract vegetation information from environmental factors, determine the basic attenuation coefficient, vegetation density and vegetation height factor according to the vegetation information, and calculate the vegetation attenuation factor, where the basic attenuation coefficient is determined by the vegetation type.

[0026] As a further solution of the present invention: the step of determining the blocking area and density factor of the building according to the building information specifically includes:

[0027] Determine a projection area of ​​the building on the ground according to the building information, and determine a blocking area of ​​the building according to the signal transmission path and the projection area;

[0028] The building density on the signal transmission path is determined, and a density factor is determined according to the building density.

[0029] As a further solution of the present invention: when the distance between the IoT device and the base station is corrected according to the comprehensive path loss index, the corrected distance Where d0 is the distance before correction.

[0030] Another object of the present invention is to provide an Internet of Things device positioning system based on base station information, the system comprising:

[0031] A mobile communication access module, used to enable the IoT device to access the mobile communication network through the wireless communication module;

[0032] A base station information collection module is used to collect information of at least three surrounding base stations through a communication protocol, wherein the base station information includes a base station ID and a signal strength, and the base station coordinates are determined through the base station ID;

[0033] A preliminary coordinate determination module is used to preliminarily determine the distance between the IoT device and each base station based on the signal strength and the base station coordinates, and to calculate the preliminary coordinates of the IoT device using a triangulation positioning algorithm;

[0034] A path loss index module, used to determine a comprehensive path loss index of signal propagation based on preliminary coordinates, base station coordinates and electronic maps;

[0035] The corrected coordinate determination module is used to correct the distance between the Internet of Things device and the base station according to the comprehensive path loss index to obtain the corrected coordinates of the Internet of Things device.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The present invention obtains the signal strength and base station coordinates by collecting information of at least three base stations in the surrounding area; the distance between the IoT device and each base station is preliminarily determined based on the signal strength and base station coordinates, and the preliminary coordinates of the IoT device are calculated using a triangulation positioning algorithm. Then, the comprehensive path loss index of signal propagation is determined based on the preliminary coordinates, base station coordinates and electronic maps, and the electronic map contains terrain data, building data and vegetation data. Finally, the distance between the IoT device and the base station is corrected based on the comprehensive path loss index to obtain the corrected coordinates of the IoT device. In this way, the corrected coordinates take into account the influence of multiple factors such as buildings and terrain, and the positioning is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 The present invention is a flowchart of a method for positioning an IoT device based on base station information.

[0039] Figure 2 A flowchart for determining preliminary coordinates in a method for positioning an IoT device based on base station information.

[0040] Figure 3 The present invention is a flowchart for obtaining the final preliminary coordinates in a method for positioning an IoT device based on base station information.

[0041] Figure 4 A flowchart for determining a comprehensive path loss index in an IoT device positioning method based on base station information.

[0042] Figure 5 The present invention is a flowchart for determining an adjustment coefficient, a building blocking factor, and a vegetation attenuation factor in a positioning method for an Internet of Things device based on base station information.

[0043] Figure 6 A flowchart for determining blocking area and density factor in an IoT device positioning method based on base station information.

[0044] Figure 7This is a structural diagram of an Internet of Things device positioning system based on base station information. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0046] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0047] like Figure 1 As shown, an embodiment of the present invention provides an Internet of Things device positioning method based on base station information, and the method includes the following steps:

[0048] S100, enabling the IoT device to access the mobile communication network through the wireless communication module;

[0049] S200, collecting information of at least three surrounding base stations through a communication protocol, wherein the base station information includes a base station ID and a signal strength, and determining the base station coordinates through the base station ID;

[0050] S300, preliminarily determining the distance between the IoT device and each base station according to the signal strength and the base station coordinates, and using a triangulation positioning algorithm to calculate the preliminary coordinates of the IoT device;

[0051] S400, determining a comprehensive path loss index of signal propagation according to the preliminary coordinates, the base station coordinates and the electronic map;

[0052] S500: Correct the distance between the IoT device and the base station according to the comprehensive path loss index to obtain corrected coordinates of the IoT device.

[0053] It should be noted that the base station in the mobile communication network is a signal transmission source, and its location information is known and stable. By measuring parameters such as the signal strength between the IoT device and the base station, the IoT device can be positioned. However, since the signal propagation process is affected by various factors such as buildings and terrain, there is a certain deviation between the signal strength and the actual distance between the IoT device and the base station, which affects the accuracy of positioning. The embodiments of the present invention are intended to solve the above problems.

[0054] In the embodiment of the present invention, first, the Internet of Things device needs to access the mobile communication network through a SIM card or other wireless communication module. After the device accesses the network, it collects information of multiple base stations (at least three) around it through AT commands or other communication protocols. The base station information includes the base station ID and the signal strength. Then, the corresponding base station coordinates are searched in the database through the base station ID. Then, the distance between the Internet of Things device and each base station is preliminarily determined according to the signal strength and the base station coordinates. The signal strength (RSSI) is inversely proportional to the distance between the Internet of Things device and the base station, that is, the farther the distance, the weaker the signal strength. Then, the preliminary coordinates of the Internet of Things device are calculated using a triangulation positioning algorithm. In the embodiment of the present invention, an electronic map is constructed in advance. The electronic map contains terrain, buildings, and vegetation information, including geographic information system (GIS) data, satellite images, and digital elevation models (DEM). In this way, the comprehensive path loss index of signal propagation can be accurately determined according to the preliminary coordinates, base station coordinates, and the electronic map. Then, the distance between the Internet of Things device and the base station is corrected according to the comprehensive path loss index, and then the corrected coordinates of the Internet of Things device are calculated. In this way, the corrected coordinates take into account the influence of multiple factors such as buildings and terrain, and the positioning is more accurate.

[0055] like Figure 2 As shown, as a preferred embodiment of the present invention, the step of preliminarily determining the distance between the IoT device and each base station according to the signal strength and the base station coordinates, and using the triangulation positioning algorithm to calculate the preliminary coordinates of the IoT device specifically includes:

[0056] S301, based on a logarithmic distance path loss model, calculate and determine the distance between the IoT device and each base station according to the signal strength and the base station coordinates;

[0057] S302, extracting three of the plurality of base station information at random to obtain a base station group, listing all the base station groups, and calculating the preliminary coordinates corresponding to each base station group based on a triangulation positioning algorithm;

[0058] S303, analyzing several preliminary coordinates to obtain final preliminary coordinates.

[0059] In the embodiment of the present invention, the commonly used logarithmic distance path loss model is used to calculate the distance between the IoT device and each base station, and then three of the base station information are randomly extracted to obtain a base station group. All base station groups are listed. Assuming there are K base stations, then The preliminary coordinates of the IoT devices determined by each base station group are calculated based on the triangulation positioning algorithm. Finally, several preliminary coordinates need to be analyzed to obtain the final preliminary coordinates to make the result more accurate.

[0060] like Figure 3As shown, as a preferred embodiment of the present invention, the step of analyzing a plurality of preliminary coordinates to obtain the final preliminary coordinates specifically includes:

[0061] S3031, counting the frequency of occurrence of each preliminary coordinate in all preliminary coordinates;

[0062] S3032, according to the distribution of the preliminary coordinates, eliminating abnormally deviated preliminary coordinates based on the mean and standard deviation;

[0063] S3033, for the remaining preliminary coordinates, calculate the weighted average coordinate according to their occurrence frequencies, and the weighted average coordinate is the final preliminary coordinate.

[0064] In the embodiment of the present invention, it is also necessary to count the frequency of occurrence of each preliminary coordinate in all preliminary coordinates. The higher the frequency of occurrence of a coordinate, the more base station combinations support this coordinate, and the higher the accuracy. Then, according to the distribution of the preliminary coordinates, the abnormally deviated preliminary coordinates are eliminated based on the mean and standard deviation. Finally, for the remaining preliminary coordinates, the weighted average coordinate is calculated according to their frequency of occurrence. The weighted average coordinate is the final preliminary coordinate. w i Represents the coordinates (x i ,y i ), M is the number of remaining preliminary coordinates, (x final ,y final ) represents the weighted average coordinate, so that the final preliminary coordinate has a higher accuracy.

[0065] like Figure 4 As shown, as a preferred embodiment of the present invention, the step of determining the comprehensive path loss index of signal propagation according to the preliminary coordinates, the base station coordinates and the electronic map specifically includes:

[0066] S401, importing the preliminary coordinates and the base station coordinates into an electronic map to determine a signal transmission path, wherein the electronic map includes terrain data, building data, and vegetation data, and determines environmental factors along the signal transmission path;

[0067] S402, determining an adjustment coefficient, a building blocking factor, and a vegetation attenuation factor in a signal transmission process according to environmental factors;

[0068] S403, retrieve basic path loss index n b , the adjustment coefficient t1, building blocking factor t2 and vegetation attenuation factor t3 are applied to the basic path loss index to calculate the comprehensive path loss index n c .

[0069] In the embodiment of the present invention, the preliminary coordinates and the coordinates of each base station are imported into an electronic map to determine the signal transmission path, and the environmental factors along the signal transmission path are determined, wherein the environmental factors are composed of terrain information, building information, and vegetation information. Then, the adjustment coefficient, building blocking factor, and vegetation attenuation factor in the signal transmission process are determined according to the environmental factors, and the basic path loss index n is retrieved. b , to determine the value, which is usually a value measured in open space or free space, then apply the adjustment factor t1, building blocking factor t2 and vegetation attenuation factor t3 to the basic path loss index to calculate the comprehensive path loss index n c , n c =n b ×(1+t1)×(1+t2)×(1+t3).

[0070] like Figure 5 As shown, as a preferred embodiment of the present invention, the step of determining the adjustment coefficient, the building blocking factor and the vegetation attenuation factor in the signal transmission process according to environmental factors specifically includes:

[0071] S4021, inputting terrain information in environmental factors into a terrain adjustment library, and outputting corresponding adjustment coefficients;

[0072] S4022, extracting building information from environmental factors, determining the blocking area and density factor of the building according to the building information, and calculating the building blocking factor according to the building blocking area and density factor;

[0073] S4023, extracting vegetation information from environmental factors, determining a basic attenuation coefficient, vegetation density and vegetation height factor according to the vegetation information, and calculating a vegetation attenuation factor, wherein the basic attenuation coefficient is determined by the vegetation type.

[0074] In the embodiment of the present invention, a terrain adjustment library is established in advance. The terrain adjustment library contains several terrain types. Each terrain type corresponds to an adjustment coefficient. When the terrain information in the environmental factors is input into the terrain adjustment library, the corresponding adjustment coefficient will be automatically output. For example, the adjustment coefficient of the plain area is 1 (indicating that the impact on the path loss is small), while the adjustment coefficient of the mountainous area is large. Then the building information in the environmental factors is extracted, and the blocking area BA and density factor DF of the building are determined according to the building information. The building blocking factor t2 is calculated according to the building blocking area and density factor. Among them, BA irepresents the blocking area of ​​the i-th building (a total of N buildings), and PL is the total length of the signal transmission path. Then, vegetation information in the environmental factors is extracted. Vegetation information includes vegetation type, vegetation density and height. According to the vegetation information, the basic attenuation coefficient BA, vegetation density DY and vegetation height factor HF are determined. The vegetation types are classified into trees, shrubs and grasslands, and a basic attenuation coefficient is determined in advance for each type. Each vegetation height range corresponds to a vegetation height factor. In this way, the vegetation attenuation factor t3 can be calculated. Among them, BA j represents the basic attenuation coefficient of the jth vegetation block (a total of S vegetation blocks), DY j represents the vegetation density of the jth vegetation patch, HF j Represents the vegetation height factor of the jth vegetation block.

[0075] like Figure 6 As shown, as a preferred embodiment of the present invention, the step of determining the blocking area and density factor of the building according to the building information specifically includes:

[0076] S40221, determining a projection area of ​​the building on the ground according to the building information, and determining a blocking area of ​​the building according to the signal transmission path and the projection area;

[0077] S40222, determine the building density on the signal transmission path, and determine a density factor according to the building density.

[0078] In the embodiment of the present invention, the projection area of ​​the building on the ground is determined according to the extracted building information, and the blocking area of ​​the building is determined according to the signal transmission path and the projection area, wherein the projection area is located on the signal transmission path, and the signal transmission path divides the projection area into two parts, and the area of ​​the smaller part is the blocking area. Then, the building density on the signal transmission path is determined, and the density factor is determined according to the building density, and each building density range corresponds to a density factor.

[0079] In the embodiment of the present invention, when the distance between the IoT device and the base station is corrected according to the comprehensive path loss index, the corrected distance Among them, d0 is the distance before correction. After the distance between the IoT device and each base station is completely corrected, the triangulation positioning algorithm is used to calculate the corrected coordinates of the IoT device.

[0080] like Figure 7 As shown, an embodiment of the present invention further provides an Internet of Things device positioning system based on base station information, the system comprising:

[0081] The mobile communication access module 100 is used to enable the IoT device to access the mobile communication network through the wireless communication module;

[0082] The base station information collection module 200 is used to collect information of at least three surrounding base stations through a communication protocol, wherein the base station information includes a base station ID and a signal strength, and the base station coordinates are determined through the base station ID;

[0083] A preliminary coordinate determination module 300 is used to preliminarily determine the distance between the IoT device and each base station according to the signal strength and the base station coordinates, and calculate the preliminary coordinates of the IoT device using a triangulation positioning algorithm;

[0084] A path loss index module 400, for determining a comprehensive path loss index of signal propagation based on preliminary coordinates, base station coordinates and an electronic map;

[0085] The corrected coordinate determination module 500 is used to correct the distance between the IoT device and the base station according to the comprehensive path loss index to obtain the corrected coordinates of the IoT device.

[0086] The above only describes in detail the preferred embodiments of the present invention, which is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0087] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0088] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0089] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the disclosure in the specification and examples. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

Claims

1. The method for locating IoT devices based on base station information is characterized in that: The method comprises the following steps: Enable IoT devices to access mobile communication networks through wireless communication modules; Collect information of at least three surrounding base stations through a communication protocol, wherein the base station information includes a base station ID and a signal strength, and determine the base station coordinates through the base station ID; The distance between the IoT device and each base station is preliminarily determined based on the signal strength and base station coordinates, and the preliminary coordinates of the IoT device are calculated using a triangulation positioning algorithm; Determine the comprehensive path loss index of signal propagation based on the preliminary coordinates, base station coordinates and electronic map; The distance between the IoT device and the base station is corrected according to the comprehensive path loss index to obtain the corrected coordinates of the IoT device.

2. The method for locating an IoT device based on base station information according to claim 1, characterized in that: The step of preliminarily determining the distance between the IoT device and each base station according to the signal strength and the base station coordinates, and using a triangulation positioning algorithm to calculate the preliminary coordinates of the IoT device specifically includes: Based on the logarithmic distance path loss model, the distance between the IoT device and each base station is calculated according to the signal strength and base station coordinates; Extract three of the information of several base stations at random to obtain a base station group, list all the base station groups, and calculate the preliminary coordinates corresponding to each base station group based on the triangulation positioning algorithm; Several preliminary coordinates are analyzed to obtain final preliminary coordinates.

3. The method for locating an Internet of Things device based on base station information according to claim 2, characterized in that: The step of analyzing a plurality of preliminary coordinates to obtain the final preliminary coordinates specifically includes: Count the frequency of occurrence of each preliminary coordinate among all preliminary coordinates; According to the distribution of the preliminary coordinates, the abnormally deviated preliminary coordinates are eliminated based on the mean and standard deviation; For the remaining preliminary coordinates, the weighted average coordinates are calculated according to their occurrence frequencies. The weighted average coordinates are the final preliminary coordinates. w i Represents the coordinates (x i ,y i ), M is the number of remaining preliminary coordinates, (x final ,y final ) represents the weighted average coordinate.

4. The method for locating an IoT device based on base station information according to claim 1, characterized in that: The step of determining the comprehensive path loss index of signal propagation according to the preliminary coordinates, the base station coordinates and the electronic map specifically includes: Importing the preliminary coordinates and the base station coordinates into an electronic map to determine a signal transmission path, wherein the electronic map includes terrain data, building data, and vegetation data to determine environmental factors along the signal transmission path; Determine the adjustment coefficient, building blocking factor and vegetation attenuation factor in the signal transmission process according to environmental factors; Retrieve the basic path loss index n b , the adjustment coefficient t1, building blocking factor t2 and vegetation attenuation factor t3 are applied to the basic path loss index to calculate the comprehensive path loss index n c , n c =n b ×(1+t1)×(1+t2)×(1+t3).

5. The method for locating an Internet of Things device based on base station information according to claim 4, characterized in that: The step of determining the adjustment coefficient, the building blocking factor and the vegetation attenuation factor in the signal transmission process according to environmental factors specifically includes: Input terrain information in environmental factors into the terrain adjustment library and output the corresponding adjustment coefficient; Extracting building information from environmental factors, determining the blocking area and density factor of the building according to the building information, and calculating the building blocking factor according to the building blocking area and density factor; Extract vegetation information from environmental factors, determine the basic attenuation coefficient, vegetation density and vegetation height factor according to the vegetation information, and calculate the vegetation attenuation factor, where the basic attenuation coefficient is determined by the vegetation type.

6. The method for locating an Internet of Things device based on base station information according to claim 5, characterized in that: The step of determining the blocking area and density factor of the building according to the building information specifically includes: Determine a projection area of ​​the building on the ground according to the building information, and determine a blocking area of ​​the building according to the signal transmission path and the projection area; The building density on the signal transmission path is determined, and a density factor is determined according to the building density.

7. The method for locating an Internet of Things device based on base station information according to claim 4, characterized in that: When the distance between the IoT device and the base station is corrected according to the comprehensive path loss index, the corrected distance Among them, d0 is the distance before correction.

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