Indoor Personnel Trajectory Location and Close Contact Personnel Query Method Based on Integrated Positioning

Abstract

The present invention provides a method for indoor personnel trajectory positioning and close contact personnel query based on fusion positioning, including: step 1, deploying WiFi-AP equipment; step 2, collecting data; step 3, constructing positioning characteristic equations; step 4, initial positioning calculation; step 5, correcting positioning. The method of the present invention uses the smart phones that people carry with them in the mobile Internet era, the standard Bluetooth communication and WiFi communication functions, combined with the WiFi network deployed indoors in large public buildings, to complete the construction of the basic positioning environment, with low construction cost, fast speed and easy promotion; with the monitoring background system, mobile application and fusion positioning algorithm provided by the method, it can complete the high-precision real-time positioning of people's activity trajectories and close contacts, and the positioning process is imperceptible to the positioned persons and there is no need to set a constraint mechanism, with good user experience and high application efficiency.

Description

Technical Field

[0001] The present invention relates to an indoor personnel trajectory positioning and close contact personnel query method based on integrated positioning. Background Art

[0002] Personnel trajectory tracking and intensive personnel investigation are mainly divided into two parts. One part is the trajectory and close contact personnel investigation when people are outdoors, and the other part is the trajectory and close contact personnel investigation when people are indoors. The first part mainly realizes accurate positioning of personnel through positioning technologies such as GPS, Beidou, and mobile communication, and queries close contact personnel based on the obtained positions, which is currently widely used. For the second part, due to the shielding of buildings, the positioning accuracy based on GPS, Beidou, and mobile communication is greatly reduced or even fails. Currently, common methods include two-dimensional code positioning, video surveillance positioning, etc.

[0003] Disadvantages of the prior art:

[0004] 1. Two-dimensional code positioning

[0005] This method is the most widely used method at present. This method mainly involves pasting two-dimensional codes with position marks in indoor places. When people pass by, they use various epidemic prevention APPs on their smartphones to scan the two-dimensional codes posted at the entrance for registration. Before using the epidemic prevention APP, people need to complete user registration, that is, enter their personal identity information into the epidemic prevention APP. After scanning the code, the epidemic prevention APP transmits the personal identity recognition information of people, the position information of the scanned two-dimensional code, and the scanning time to the background system of the epidemic prevention APP. The background system records the positions of each person's code scanning registration in chronological order, and connecting these position points together gives the activity trajectory of people. Then, close contact personnel are found through trajectory overlap. The accuracy of the obtained trajectory and the accuracy of close contact personnel depend on the posting density of two-dimensional codes and the completion degree of people's code scanning. Due to the large time consumption and low efficiency of code scanning, the number of posted two-dimensional codes is limited, which in turn limits the positioning accuracy. At the same time, in order to supervise passing personnel to complete code scanning, other constraint mechanisms such as personnel on duty and video surveillance need to be set up, resulting in problems such as low positioning accuracy and poor effectiveness in practice for this method.

[0006] 2. Video surveillance positioning

[0007] The video surveillance and positioning method installs cameras indoors to monitor and record the areas where people are active in real time, and then obtains the personnel trajectories and close contacts through manual video viewing or machine automatic image recognition methods. Among them, the method of manual video viewing takes a long time and has a huge workload, and the effect is not good. Generally, it takes several hours to complete the investigation of the video data recorded by one camera in a day, and the investigation effect also depends on factors such as the performance of the camera, the shooting angle, and the eyesight of the staff; while through the machine automatic image recognition method, the real-time video stream data or video data is recognized through image recognition technology, and then the identity information and location information of the people in the surveillance video are obtained. This method has extremely high costs and low feasibility. At present, the mainstream way to obtain personnel identity information through image recognition mainly relies on face recognition. However, when people are in the epidemic prevention state, they basically wear masks or other epidemic prevention equipment, which greatly reduces the recognition accuracy. At the same time, a large number of high-performance cameras need to be installed to achieve full coverage recognition, and the installation positions and angles are very particular. Moreover, a large amount of computer computing resources need to be invested to achieve fast or real-time recognition. Generally, millions of computer computing resources need to be invested to complete the real-time recognition of 50 4-million-pixel cameras. Summary of the Invention

[0008] Object of the Invention: The technical problem to be solved by the present invention is to provide a method for indoor personnel trajectory positioning and close contact personnel query based on fusion positioning in view of the deficiencies of the prior art. One is to solve the problems of the accuracy and efficiency of personnel trajectory positioning and close contact personnel query, and the other is to solve the problems of difficult implementation and high cost of traditional solutions.

[0009] The present invention includes the following steps:

[0010] Step 1, deploy WiFi-AP devices;

[0011] Step 2, collect data;

[0012] Step 3, construct a positioning feature equation;

[0013] Step 4, perform initial positioning calculation;

[0014] Step 5, correct the positioning.

[0015] Step 1 includes: Install WiFi-AP devices in the areas that need epidemic prevention monitoring. Suppose there are W WiFi-AP devices installed, record the MAC addresses of each WiFi-AP device, and set the MAC address of the wth AP device as MAC AP (w), where w ∈ {1, 2, 3,......, W};

[0016] Establish a three-dimensional coordinate system for a building. Select the southwest corner of the first floor of the building as the origin of the coordinate system, the due north direction as the positive direction of the Y-axis, the due east direction as the positive direction of the X-axis, and the vertically upward direction as the positive direction of the Z-axis. Based on the coordinate system, record the installation positions of each WiFi-AP device. The installation position of the w-th AP device is set as P AP (MAC AP (w)), and its value is shown as follows:

[0017] P AP (MAC AP (w)) = (X ap (MAC AP (w)), Y ap (MAC AP (w)), Z ap (MAC AP (w))) (1)

[0018] Where:

[0019] X ap (MAC AP (w)) represents the X coordinate value of the WiFi-AP device with the MAC address MAC AP (w);

[0020] Y ap (MAC AP (w)) represents the Y coordinate value of the WiFi-AP device with the MAC address MAC AP (w);

[0021] Z ap (MAC AP (w)) represents the Z coordinate value of the WiFi-AP device with the MAC address MAC AP (w);

[0022] After the WiFi-AP device is installed, it will continuously broadcast data packets with its own WiFi communication MAC address to the surrounding area.

[0023] Step 2 includes:

[0024] Step 2-1, obtain the personnel identification information through the personnel's smartphone, which is shown as follows:

[0025] Phone(s) = (s, n, MAC BT ) (2)

[0026] Where: Phone(s) represents the identification information combination corresponding to the smartphone numbered s; n is the personal identification information; MAC BT is the MAC address of the Bluetooth communication of the smartphone;

[0027] Combine the Phone(s) of all registered smartphones to obtain a set of smartphone identification information, denoted as QPhone, whose value is represented as follows:

[0028] QPhone = {Phone(1), Phone(2),......, Phone(s),...}

[0029] Step 2-2, collect positioning signals.

[0030] Step 2-2 includes: when a person carrying a smartphone enters the monitoring area, turn on the WiFi signal and Bluetooth signal switches of the smartphone, and perform the following steps:

[0031] Step 2-2-1, initialization: set the Bluetooth module of the smartphone to work in both slave and master modes simultaneously. In the slave mode, the smartphone Bluetooth module continuously broadcasts data packets containing its own Bluetooth communication MAC address to the surrounding area, but cannot establish a connection with the central device; while in the master mode, the smartphone Bluetooth module can scan peripheral Bluetooth devices and obtain the data packets broadcast by peripheral Bluetooth devices and their Bluetooth signal strengths;

[0032] Step 2-2-2, the smartphone cyclically collects the WiFi signal strength values of the data broadcast by each WiFi-AP device around it and the Bluetooth signal strength values of the data broadcast by other smartphone Bluetooth modules at the current position with a unified collection period T. Suppose at the collection moment k, I(k) WiFi signal strength values of the data broadcast by WiFi-AP devices and J(k) Bluetooth signal strength values of the data broadcast by other smartphone Bluetooth modules are collected;

[0033] Select the 3 largest values from the I(k) WiFi signal strength values of the data broadcast by WiFi-AP devices to form a set QRSSI WiFi (s)(k), whose value is represented as follows:

[0034] QRSSI WiFi (s)(k) = {RSSI WiFi (s)(k)(MAC AP (max 1 )), RSSI WiFi (s)(k)(MAG AP (max 2 )), RSSI WiFi (s)(k)(MAC AP (max 3 ))} (3)

[0035] Where: k is the acquisition time, which is acquired every T intervals, and the starting acquisition time value is divisible by T;

[0036] RSSI WiFi (s)(k)(MAC AP (max 1 )) represents the WiFi signal strength value of the broadcast data of the WiFi-AP device with the WiFi communication MAC address of MAC at the k acquisition time by the smartphone numbered s, where MAC AP (max 1 ) represents the WiFi communication MAC address of the WiFi-AP device corresponding to the signal value, where MAC AP (max 1 ) represents the WiFi communication MAC address of the WiFi-AP device corresponding to the signal value, where max 1 represents the device number of the WiFi-AP device with the strongest signal strength among the 3 strongest signal strength values, max 1 ∈ {1, 2, 3,......, W};

[0037] RSSI WiFi (s)(k)(MAC AP (max 2 )) represents the WiFi signal strength value of the broadcast data of the WiFi-AP device with the WiFi communication MAC address of MAC at the k acquisition time by the smartphone numbered s, where MAC AP (max 2 ) represents the WiFi communication MAC address of the WiFi-AP device corresponding to the signal value, where MAC AP (max 2 ) represents the WiFi communication MAC address of the WiFi-AP device corresponding to the signal value, where max 2 represents the device number of the second-strongest WiFi-AP device among the 3 strongest signal strength values, max 2 ∈ {1, 2, 3,......, W};

[0038] RSSI WiFi (s)(k)(MAC AP (max 3 )) represents the WiFi signal strength value of the broadcast data of the WiFi-AP device with the WiFi communication MAC address of MAC at the k acquisition time by the smartphone numbered s, where MAC AP (max 3 ) represents the WiFi communication MAC address of the WiFi-AP device corresponding to the signal value, where MAC AP (max 3 ) represents the WiFi communication MAC address of the WiFi-AP device corresponding to the signal value, where max 3 represents the device number of the third-strongest WiFi-AP device among the 3 strongest signal strength values, max3 ∈ {1, 2, 3,......, W};

[0039] Sort the Bluetooth signal strength values broadcast by J(k) other smartphone Bluetooth modules collected in descending order, and generate a number for each Bluetooth signal strength value, denoted as a(s)(k)(j), where s is the number of the data collection smartphone, k is the collection time, and j is an integer j ∈ {1, 2,..., J(k)}; Combine the Bluetooth signal strength values to obtain a set QRSSI BT (s)(k), whose value is expressed as follows:

[0040]

[0041] Among them: RSSI BT (s)(k)(MAC BT (a(s)(k)(j))) represents the Bluetooth signal strength value of the smartphone with the Bluetooth communication MAC address MAC BT (a(s)(k)(j)) broadcast by the smartphone numbered s at the k collection time, where MAC BT (a(s)(k)(j)) represents the Bluetooth communication MAC address value of the broadcast smartphone.

[0042] Step 3 includes:

[0043] Step 3-1, establish the relationship equation between WiFi signal strength and distance;

[0044] Step 3-2, establish the relationship equation between Bluetooth signal strength and distance.

[0045] Step 3-1 includes: The formula of the signal propagation model Shadowing model is as follows:

[0046]

[0047] Among them: RSSI R is the signal strength value received by the receiving point; RSSI 0 is the signal strength value received by the reference point; γ is the transmission medium factor; d is the distance between the receiving point and the transmitting point; d 0 is the distance between the reference point and the transmitting point;

[0048] Then perform the following steps:

[0049] Step a1, select a point 1 meter away from the WiFi-AP device in the monitoring area as the reference point, that is, d 0 is 1 meter;

[0050] Step a2, detect the WiFi signal strength value emitted by the WiFi-AP device at a distance of 1 meter and record it, which is the RSSI 0 value;

[0051] Step a3, detect the WiFi signal strength value emitted by the WiFi-AP device at a distance of 5 meters and record it, thus obtaining a set of d, RSSI R ;

[0052] Step a4, substitute d 0 , RSSI 0 , d, RSSI R into Equation (5) to obtain the value of the transmission medium factor γ of the WiFi-AP device in this detection environment;

[0053] The formula for the signal propagation strength and distance of each WiFi-AP is obtained through steps a1 to a4, as follows:

[0054] Where: RSSI WiFi (s)(k)(MAC AP (w)) represents the WiFi signal strength value of the data broadcast by the WiFi-AP device with the WiFi communication MAC address MAC AP (w) collected by the smartphone numbered s in the kth collection period;

[0055] RSSI WiFi (MAC AP (w)) 0 represents the WiFi signal strength value emitted by it at a distance of 1 meter from the WiFi-AP device with the WiFi communication MAC address MAC AP (w);

[0056] γ(MAC AP (w)) represents the transmission medium factor of the WiFi-AP device with the WiFi communication MAC address MAC AP (w) in the monitoring area;

[0057] d WiFi (s)(k)(MAC AP (w)) represents the distance value of the smartphone numbered s from the WiFi-AP device with the WiFi communication MAC address MAC AP (w) obtained by ranging based on the WiFi signal strength in the kth collection period;

[0058] Equation (6) is sorted out to obtain the following equation, that is, the equation of the relationship between the signal propagation signal strength and distance of each WiFi-AP device is obtained:

[0059]

[0060] Step 3-2 includes: The relationship equation between the Bluetooth communication wireless signal strength of the smart phone and the distance is expressed as follows:

[0061]

[0062] Where: d BT (s)(k)(MAC BT (a(s)(k)(j))) represents the distance value of the smart phone numbered s at the kth acquisition moment from the smart phone with the Bluetooth communication MAC address of MAC BT (a(s)(k)(j)).

[0063] Step 4 includes:

[0064] Step 4-1, preliminary positioning of the smart phone location: Substitute the elements in the QRSSI WiFi (s)(k) set into Equation (7) to obtain d WiFi (s)(k)(MAC AP (max 1 )), d WiFi (s)(k)(MAC AP (max 2 )) and d WiFi (s)(k)(MAC AP (max 3 ));

[0065] Apply the maximum likelihood estimation method to calculate the location of the smart phone, and its value is expressed as follows:

[0066] P c (s)(k) = (A T A) -1 A T b (9)

[0067] Where: P c (s)(k) represents the coordinates obtained by the preliminary positioning calculation of the smart phone numbered s in the kth acquisition cycle, and its value is Where X c (s)(k), Y c (s)(k), Z c (s)(k) represent the X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value respectively;

[0068] A is a matrix, and its value is

[0069]

[0070] b is a matrix, and its value is

[0071] where b(1) = X AP (MAC AP (max 1 )) 2 - X AP (MAC AP (max 3 )) 2 + Y AP (MAC AP (max 1 )) 2 - Y AP (MAC AP (max 3 )) 2 + Z AP (MAC AP (max 1 )) 2 - Z AP (MAC AP (max 3 )) 2 + d WiFi (s)(k)(MAC AP (max 3 )) 2 - d WiFi (s)(k)(MAC AP (max 1 )) 2 , b(2) = X AP (MAC AP (max 2 )) 2 - X AP (MAC AP (max 3 )) 2 + Y AP (MAC AP (max2)) 2 - Y AP (MAC AP (max 3 )) 2 + Z AP (MAC AP (max 2 )) 2 - Z AP (MAC AP (max 3 )) 2 + d WiFi (s)(k)(MACAP (max 3 )) 2 -d WiFi (s)(k)(MAC AP (max 2 )) 2

[0072] Record the coordinates of the smartphone numbered s at the collection time k as P(s)(k), and its value is set to:

[0073] P(s)(k) = (X c (s)(k), Y c (s)(k), Z c (s)(k)) (10);

[0074] Step 4-2, calculate the distance between smartphones:

[0075] Substitute the elements in QRSSI BT (s)(k) into Equation (8) in turn to obtain a value to form a new set, that is, obtain the set QdRSSI BT (s)(k) of the distance values obtained by ranging the smartphone with other surrounding smartphones based on Bluetooth signals at the collection time k. Its value is expressed as follows:

[0076]

[0077] Where: QdRSSI BT (s)(k) represents the set of distance values obtained by ranging the smartphone numbered s with other surrounding smartphones based on Bluetooth signals at time k.

[0078] In Step 4-2, the close contacts can be queried by the following method:

[0079] Set the query condition as: the identity identification information of the person to be queried is Pr, the query time range is [t 1 , t 2 , t 1 is the lower limit value of the time query range, t 2 is the upper limit value of the time query range. Let all the collection times covered by the time range be {k 1 , k 2 ,..., k e}, where k 1 ≥ t 1 , k e ≤ t 2 , and the close contact distance is within L meters. Then the query method is as follows:

[0080] Step b1: Find all elements in the QPhone set with the personal identification information Pr. Suppose F elements are found. Extract the smartphone numbers in these elements to form a new set, denoted as {s 1 s 2 s F}; s F is the smartphone number of the F-th element among the F elements with the personal information Pr found from the QPhone set;

[0081] Step b2: Find the set Qs of distance values obtained by ranging other smartphones around all smartphones with the collection time values {k 1 k 2 k e} and the numbers in {s 1 s 2 s F} based on Bluetooth signals, which is expressed as follows:

[0082]

[0083] Step b3: Find the elements in each subset QdRSSI BT (s f )(k e ) in the set Qs whose values are less than or equal to L. Form a new set Qsm with the elements less than or equal to L, and its values are expressed as follows:

[0084]

[0085] Where: JJ(s f )(k e ) represents the number of elements in the set QdRSSI BT (s f )(k e ) whose element values are less than or equal to L;

[0086] Step b4: Extract the labels MAC BT (a(s f )(k e )(j)) of all elements in the set Qsm to form a new set Qsmm, and its values are expressed as follows:

[0087]

[0088] Step b5: Find all elements in the QPhone set whose Bluetooth communication MAC address values are in the set Qsmm, and extract the personal identification information in these elements to form a new set. This set is the set of personal identification information of the close contact persons who meet the query conditions.

[0089] Step 5 includes:

[0090] Step 5-1, find QdRSSI BT The element with the smallest value in the set (s)(k), denoted as d BT (s)(k)(MAC BT (s)(k)(a(s)(k)(min))), where min ∈ {1, 2,..., J(k)};

[0091] Step 5-2, query in the set QPhone for the smartphone number value corresponding to the Bluetooth communication MAC address MAC BT (s)(k)(a(s)(k)(min)), denoted as s min ;

[0092] Step 5-3, based on the coordinates obtained from the initial WiFi positioning, use the three-dimensional space distance formula to calculate the distance dp between the smartphone numbered s and the smartphone closest to it WiFi (s)(k)(s min ), which is expressed as follows:

[0093]

[0094] Step 5-4, successively multiply d WiFi (s)(k)(MAC AP (max 1 ))、d WiFi (s)(k)(MAC AP (max 2 ))、 d WiFi (s)(k)(MAC AP (max 3 )) by to obtain their corrected values, denoted as d WiFi_fix (s)(k)(MAC AP (max 1 ))、d WiFi_fix (s)(k)(MAC AP (max 2 ))、 d WiFi_fix (s)(k)(MAC AP (max 3 ));

[0095] Step 5-5, based on the corrected ranging values, apply the maximum likelihood estimation method again to calculate the corrected value of the coordinates of the smartphone's location, which is expressed as follows:

[0096] P fix (s)(k)=(A T A) -1 AT b fix (16)

[0097] Where: P fix (s)(k) represents the coordinate value obtained by correcting the positioning of the smartphone numbered s at the k-th acquisition cycle, Where X fix (s)(k), Y fix (s)(k), Z fix (s)(k) represent its X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value respectively;

[0098] b fix is a matrix, and its value is Where

[0099] b fix (1) = X AP (MAC AP (max 1 )) 2 - X AP (MAC AP (max 3 )) 2 + Y AP (MAC AP (max 1 )) 2 - Y AP (MAC AP (max 3 )) 2 + Z AP (MAC AP (max 1 )) 2 - Z AP (MAC AP (max 3 )) 2 + d WiFi_fix (s)(k)(MAC AP (max 3 )) 2 - d WiFi_fix (s)(k)(MAC AP (max 1 )) 2 ,

[0100] b fix (2) = X AP (MAC AP (max 2 )) 2 - X AP (MAC AP (max 3)) 2 +Y AP (MAC AP (max 2 )) 2 -Y AP (MAC AP (max 3 )) 2 +Z AP (MAC AP (max 2 )) 2 -Z AP (MAC AP (max 3 )) 2 +d WiFi_fix (s)(k)(MAC AP (max 3 )) 2 -d WiFi_fix (s)(k)(MAC AP (max 2 )) 2

[0101] Update the coordinates of the smartphone numbered s at the acquisition time k to:

[0102] P(s)(k) = (X fix (s)(k), Y fix (s)(k), Z fix (s)(k)) (17)

[0103] Combine the coordinate values in the order of the acquisition time, and the movement trajectory of the smartphone in the monitoring area is obtained.

[0104] Advantageous effects: By using the smartphones carried by people in the mobile Internet era, the standard Bluetooth communication and WiFi communication functions, and combining with the WiFi network deployed indoors in large public buildings, the present invention method can complete the construction of the positioning basic environment, with low construction cost, fast speed and easy promotion; combined with the monitoring background system, mobile application program and fusion positioning algorithm provided by this method, it can complete the high-precision real-time positioning of people's activity trajectories and close contacts, and the positioning process is insensitive to the positioned person and there is no need to set a constraint mechanism, with good user experience and high application efficiency. Description of the Drawings

[0105] The following further describes the present invention in detail with reference to the drawings and specific embodiments, and the above and / or other advantages of the present invention will become clearer.

[0106] Figure 1 is the architecture diagram of the present invention.

[0107] Figure 2 is the flowchart of the method of the present invention.

[0108] Figure 3 is the structural schematic diagram. Specific implementation manner

[0109] As Figure 1 shown, the method of the present invention includes a WiFi-AP device (WiFi-AP: a WiFi wireless network access device, i.e., a wireless router device), a smart phone (supporting Bluetooth and WiFi communication), a monitoring background system, and a mobile application.

[0110] The WiFi-AP device is responsible for providing a benchmark and WiFi positioning signals for trajectory tracking and positioning;

[0111] The smart phone is responsible for detecting WiFi signals and Bluetooth signals and providing hardware and communication support for the operation of the mobile application;

[0112] The mobile application is responsible for user registration, WiFi and Bluetooth signal collection, positioning calculation, and transmitting registration information and positioning information to the monitoring background system;

[0113] The monitoring background system is responsible for registration information management, constructing a list of personnel trajectories and close contact personnel based on positioning information, and providing external query services.

[0114] Deploying the WiFi-AP device

[0115] (1) Installation and coordinate recording of the WiFi-AP device

[0116] Install a WiFi-AP device in the area that needs epidemic prevention monitoring, or use the existing AP devices in the building, ensuring that there is signal coverage of at least 3 or more WiFi-APs in the area to be detected. Suppose there are W WiFi-AP devices installed, record the MAC address of each AP device, denoted as MAC AP (w), w ∈ {1, 2, 3,......, W}; establish a three-dimensional coordinate system for the building (generally select the southwest corner of the first floor of the building as the origin of the coordinate system, the due north direction as the positive direction of the Y axis, the due east direction as the positive direction of the X axis, and the vertically upward direction as the positive direction of the Z axis), and record the installation position of each WiFi-AP device based on the coordinate system, denoted as P AP (MAC AP (w)), and its value is shown as the following formula:

[0117] P AP (MAC AP (w)) = (X ap (MAC AP (w)), Yap (MAC AP (w)), Z ap (MAC AP (w))) (1)

[0118] Wherein:

[0119] P AP (MAC AP (w)): represents the coordinate value of the WiFi-AP with the MAC address MAC AP (w);

[0120] X ap (MAC AP (w)): represents the X coordinate value of the WiFi-AP with the MAC address MAC AP (w);

[0121] Y ap (MAC AP (w)): represents the Y coordinate value of the WiFi-AP with the MAC address MAC AP (w);

[0122] Z ap (MAC AP (w)): represents the Z coordinate value of the WiFi-AP with the MAC address MAC AP (w);

[0123] (2) After the WiFi-AP device is installed, the WiFi device will continuously broadcast data packets with its own WiFi communication MAC address to the surrounding area;

[0124] Data collection

[0125] Collect the personal identification information of the collector and the intensity values of the WiFi signals of the data broadcast by the WiFi-AP devices in the current location environment and the intensity values of the Bluetooth signals of the data broadcast by other smart phone devices, and transmit the collected information to the monitoring back-end system. This step is completed by a mobile application, which can be in the form of a smart phone APP or a small program. The specific data collection steps are as follows:

[0126] (1) Collect personal identification information

[0127] Before people enter the monitoring area, they need to download and register a mobile application on their smart phones in advance. When registering, the mobile application needs to obtain the settings permissions of the smart phone's WiFi communication and Bluetooth communication. At the same time, the registered person needs to enter the personal identification information (which can be ID card, smart phone number, face features, etc.). Let the personal identification information be n hIt is indicated that the subscript h is the number; after registration is completed, the mobile application automatically obtains the Bluetooth communication MAC address of the smartphone used during registration, packs this information together with the personal identification information, and transmits it to the monitoring background system through the mobile communication network of the smartphone; the monitoring background program combines this information and generates a number for this information combination in an incrementing manner using the Bluetooth communication MAC address of the smartphone as the identifier, denoted as s. This combination is represented as Phone(s), and its value is expressed as follows:

[0128] Phone(s) = (s, n, MAC BT ) (2)

[0129] Where:

[0130] Phone(s): The identification information combination corresponding to the smartphone with the number s;

[0131] n: Personal identification information, which can be the smartphone number or the ID card number;

[0132] MAC BT : The MAC address of the Bluetooth communication of the smartphone;

[0133] Combining all the Phone(s) of the registered smartphones to obtain the smartphone identification information set, denoted as QPhone, and its value is expressed as follows:

[0134] QPhone = {Phone(1), Phone(2),......, Phone(s),...}

[0135] (2) Collect positioning signals

[0136] When a person carrying a registered smartphone enters the monitoring area, turn on the WiFi signal and Bluetooth signal switches of the smartphone, start the mobile application (which can run in the background), and then the mobile application completes the following steps:

[0137] Initialization

[0138] Set the Bluetooth module of the smartphone to work in both slave and master modes simultaneously. In the slave mode, the Bluetooth module of the smartphone continuously broadcasts data packets containing its own Bluetooth communication MAC address to the surrounding area, but cannot establish a connection with the central device; while in the master mode, the Bluetooth module of the smartphone can scan for peripheral Bluetooth devices and obtain the data packets broadcast by the peripheral Bluetooth devices and their Bluetooth signal strengths.

[0139] Collect data again

[0140] After initialization is completed, the mobile application deployed on the used smart phone device collects, in a unified collection period T (T can be set according to the real-time monitoring requirements, and is generally set to 2 seconds), the WiFi signal strength values of the WiFi signals broadcast by each surrounding WiFi-AP device detected by the smart phone and the Bluetooth signal strength values of the Bluetooth signals broadcast by other smart phone Bluetooth modules in a loop. Suppose that at the collection moment k, I(k) WiFi signal strength values of the WiFi signals broadcast by WiFi-AP devices and J(k) Bluetooth signal strength values of the Bluetooth signals broadcast by other smart phone Bluetooth modules are collected; among the I(k) WiFi signal strength values of the WiFi signals broadcast by WiFi-AP devices, select the 3 largest values to form a set, denoted by QRSSI WiFi (s)(k), and its value is expressed as follows:

[0141] QRSSI WiFi (s)(k) = {RSSI WiFi (s)(k)(MAC AP (max 1 ))), RSSI WiFi (s)(k)(MAC AP (max 2 ))), RSSI WiFi (s)(k)(MAC AP (max 3 )))} (3)

[0142] Where:

[0143] k is the collection moment, and it is collected once every interval of T. The starting collection moment value is divisible by T;

[0144] QRSSI WiFi (s)(k): represents the set of the 3 strongest signal strength values among the WiFi signals broadcast by the surrounding WiFi-AP devices collected by the smart phone numbered s at the k collection moment;

[0145] RSSI WiFi (s)(k)(MAC AP (max 1 )): represents the WiFi signal strength value of the WiFi signal broadcast by the WiFi-AP device with the WiFi communication MAC address MAC AP (max 1 ) collected by the smart phone numbered s at the k collection moment, where MAC AP (max 1 ) represents the WiFi communication MAC address of the broadcast device WiFi-AP device corresponding to this signal value, where max 1The device number of the WiFi-AP device with the strongest of the three strongest signal strength values, max 1 ∈ {1, 2, 3,......, W};

[0146] RSSI WiFi (s)(k)(MAC AP (max 2 )): Represents the WiFi signal strength value of the data broadcast by the WiFi-AP device with the WiFi communication MAC address of MAC AP (max 2 ) collected by the smartphone numbered s at the kth collection moment, where MAC AP (max 2 ) represents the WiFi communication MAC address of the broadcast device's WiFi-AP device corresponding to this signal value, where max 2 represents the device number of the second-strongest WiFi-AP device among the three strongest signal strength values, max 2 ∈ {1, 2, 3,......, W};

[0147] RSSI WiFi (s)(k)(MAC AP (max 3 )): Represents the WiFi signal strength value of the data broadcast by the WiFi-AP device with the WiFi communication MAC address of MAC AP (max 3 ) collected by the smartphone numbered s at the kth collection moment, where MAC AP (max 3 ) represents the WiFi communication MAC address of the broadcast device's WiFi-AP device corresponding to this signal value, where max 3 represents the device number of the third-strongest WiFi-AP device among the three strongest signal strength values, max 3 ∈ {1, 2, 3,......, W};

[0148] Sort the Bluetooth signal strength values broadcast by the J(k) other smartphone Bluetooth modules collected in descending order, and generate a number for each Bluetooth signal strength value, denoted as a(s)(k)(j), where s is the number of the data collection smartphone, k is the collection moment, and j is an integer j ∈ {1, 2,..., J(k)}; Combine these Bluetooth signal strength values to obtain a set, denoted as QRSSI BT (s)(k), and its value is represented as follows:

[0149]

[0150] Wherein:

[0151] QRSSI BT (s)(k): represents the set of Bluetooth signal strength values of the Bluetooth module broadcast data of other smartphones around the smartphone numbered s at the kth collection moment;

[0152] RSSI BT (s)(k)(MAC BT (a(s)(k)(j)): represents the Bluetooth signal strength value of the smartphone with the Bluetooth communication MAC address MAC BT (a(s)(k)(j)) collected by the smartphone numbered s at the kth collection moment, where MAC BT (a(s)(k)(j)) represents the Bluetooth communication MAC address value of the smartphone broadcasting this Bluetooth signal;

[0153] Construct a positioning feature equation

[0154] This method uses a trilateration positioning method based on RSSI for positioning. Therefore, the positioning feature equation is the equation of the relationship between WiFi signal strength and distance and the equation of the relationship between Bluetooth signal strength and distance. The equation construction is completed by the monitoring background system, and the construction methods are described as follows respectively.

[0155] (1) Establish an equation of the relationship between WiFi signal strength and distance

[0156] This step mainly establishes the equation of the relationship between the signal strength of each WiFi-AP device and distance. Here, the commonly used experimental method is used to establish the equation of the relationship between the signal strength of each WiFi-AP and distance based on the signal propagation model Shadowing model. The formula of the signal propagation model Shadowing model is as follows:

[0157]

[0158] Wherein:

[0159] RSSI R : The signal strength value received by the receiving point;

[0160] RSSI 0 : The signal strength value received by the reference point;

[0161] γ: Transmission medium factor;

[0162] d: The distance between the receiving point and the transmitting point;

[0163] d 0 : The distance between the reference point and the transmitting point;

[0164] The experimental method is:

[0165] (a1) Select a point 1 meter away from the WiFi-AP device in the monitoring area as the reference point, i.e., d 0 is 1 meter;

[0166] (a2) Detect the WiFi signal strength value emitted by the WiFi-AP device at a distance of 1 meter and record it, which is the RSSI 0 value;

[0167] (a3) Detect the WiFi signal strength value emitted by the WiFi-AP device at a distance of 5 meters and record it, thus obtaining a set of d, RSSI R ;

[0168] (a4) Substitute d 0 , RSSI 0 , d, RSSI R into Equation (5) to obtain the value of the transmission medium factor γ of the WiFi-AP device in this detection environment;

[0169] Through the above experimental method, the formula for the signal propagation strength and distance of each WiFi-AP can be obtained, and the formula is as follows:

[0170]

[0171]

[0172] Where:

[0173] RSSI WiFi (s)(k)(MAC AP (w)): Represents the WiFi signal strength value of the data broadcast by the WiFi-AP device with the MAC address of MAC AP (w) collected by the smartphone numbered s in the kth acquisition cycle;

[0174] RSSI WiFi (MAC AP (w)) 0 : The WiFi signal strength value emitted by it at a distance of 1 meter from the WiFi-AP device with the MAC address of MAC AP (w), obtained in the above experimental method;

[0175] γ(MAC AP (w)): The transmission medium factor of the WiFi-AP device with the MAC address of MAC AP (w) in the monitoring area, obtained in the above experimental method;

[0176] d WiFi (s)(k)(MACAP (w)): It represents the distance value between the smartphone numbered s at the k-th acquisition cycle and the WiFi-AP device with the WiFi communication MAC address of MAC based on the ranging obtained from the WiFi signal strength. AP (w).

[0177] After organizing Equation (6), the following equation is obtained, that is, the equation of the relationship between the signal propagation signal strength and the distance of each WiFi-AP device is obtained:

[0178]

[0179] (2) Establish the equation of the relationship between the Bluetooth signal strength and the distance

[0180] The equation of the relationship between the Bluetooth signal strength and the distance is the equation of the relationship between the wireless signal strength and the distance of the Bluetooth communication of each smartphone. Here, it is also established based on the Shadowing model of the signal propagation model. The reference point is selected as the point 1 meter away from the sending point, the reference point signal strength value is set as the empirical value -59, and the transmission medium factor value is set as the empirical value 2. Then, the equation of the relationship between the wireless signal strength and the distance of the Bluetooth communication of the smartphone can be expressed as follows:

[0181]

[0182] Where:

[0183] d BT (s)(k)(MAC BT (a(s)(k)(j))): It represents the distance value between the smartphone numbered s at the k-th acquisition moment and the smartphone with the Bluetooth communication MAC address of MAC BT (a(s)(k)(j)).

[0184] Initial positioning calculation

[0185] The initial positioning calculation mainly completes the initial positioning of the smartphone position and the calculation of the distance between smartphones, which is completed by the monitoring background system. The specific calculation process is as follows:

[0186] (1) Preliminary positioning of the smartphone position

[0187] This step mainly locates the smartphone position based on the distance value obtained from the WiFi signal. The main steps are as follows:

[0188] Substitute the elements in the QRSSI WiFi (s)(k) set into Equation (7) respectively to obtain d WiFi (s)(k)(MAC AP (max 1 )), d WiFi(s)(k)(MAC AP (max 2 )) and d WiFi (s)(k)(MAC AP (max 3 ));

[0189] The location of the smart phone can be calculated using the maximum likelihood estimation method, and its value is expressed as follows:

[0190] P c (s)(k) = (A T A) -1 A T b(9)

[0191] Where:

[0192] P c (s)(k): represents the coordinates obtained by the preliminary positioning calculation of the smart phone numbered s in the k-th acquisition cycle, and its value is Where X c (s)(k), Y c (s)(k), Z c (s)(k) represent its X-axis, Y-axis, and Z-axis coordinate values respectively;

[0193] A is a matrix, and its value is

[0194]

[0195] b: is a matrix, and its value is

[0196] Where b(1) = X AP (MAC AP (max 1 )) 2 - X AP (MAC AP (max 3 )) 2 + Y AP (MAC AP (max 1 )) 2 - Y AP (MAC AP (max 3 )) 2 + Z AP (MAC AP (max 1 )) 2 - Z AP (MAC AP (max 3 )) 2 + dWiFi (s)(k)(MAC AP (max 3 )) 2 -d WiFi (s)(k)(MAC AP (max 1 )) 2 , b(2) = X AP (MAC AP (max 2 )) 2 -X AP (MAC AP (max 3 )) 2 +Y AP (MAC AP (max 2 )) 2 - Y AP (MAC AP (max 3 )) 2 +Z AP (MAC AP (max 2 )) 2 -Z AP (MAC AP (max 3 )) 2 + d WiFi (s)(k)(MAC AP (max 3 )) 2 -d WiFi (s)(k)(MAC AP (max 2 )) 2

[0197] Record the coordinates of the smartphone numbered s at the collection time k as P(s)(k), and set its value to:

[0198] P(s)(k) = (X c (s)(k), Y c (s)(k), Z c (s)(k)) (10)

[0199] (2) Calculate the distance between smartphones

[0200] In this step, the distance values between smartphones are mainly calculated through the positioning feature equation obtained above by using the Bluetooth signal strength. The main steps are as follows:

[0201] Let QRSSI BTSubstitute the elements in (s)(k) into Equation (8) in sequence to obtain a value, which forms a new set, that is, the set of distance values obtained by ranging the smartphone with other surrounding smartphones based on Bluetooth signals at the acquisition moment k, denoted as QdRSSI BT (s)(k) is expressed as follows:

[0202]

[0203] Where:

[0204] QdRSSI BT (s)(k): represents the set of distance values obtained by ranging the smartphone numbered s with other surrounding smartphones based on Bluetooth signals at the moment k.

[0205] From this, the close contact personnel within any moment or time range and any close contact distance range can be queried through the personnel identity identification information entered during the registration of the mobile application, that is, the close contact personnel query method. The query method is as follows:

[0206] Let the query condition be: the identity identification information of the person to be queried is Pr, and the query time range is [t 1 , t 2 , and let all the acquisition moments it covers be {k 1 , k 2 ,..., k e}, where k 1 ≥t 1 , k e ≤t 2 , and the close contact distance is within L meters. Then the query method is as follows:

[0207] (1) Find all the elements with "personal identification information" as Pr from the QPhone set. Suppose F are found, and extract the smartphone numbers in the elements to form a new set, denoted as {s 1 , s 2 ,..., s F};

[0208] (2) Find the set of distance values obtained by ranging all the smartphones with acquisition moment values {k 1 , k 2 ,..., k e} and numbers in {s 1 , s 2 ,..., s F} with other surrounding smartphones based on Bluetooth signals. Form a set with the obtained results, denoted as Qs. Then its value can be expressed as follows:

[0209]

[0210] (3) Find each subset $Q_{dRSSI}$ in the set $Q_s$ BT (s f )(k e ) Among the elements whose values are less than or equal to $L$, form a new set with these elements, denoted as $Q_{sm}$, and its value is expressed as follows:

[0211]

[0212] Where:

[0213] $J_J(s f )(k e ) represents the set $Q_{dRSSI}$ BT (s f )(k e ) The number of elements whose values are less than or equal to $L$ in the set;

[0214] (4) Extract the labels MAC of all elements in the set $Q_{sm}$ BT (a(s f )(k e )(j)) to form a new set, denoted as $Q_{smm}$, and its value can be expressed as follows:

[0215]

[0216] (5) Find all elements in the $Q_{Phone}$ set whose Bluetooth communication MAC address values are in the set $Q_{smm}$, and extract the "personal identification information" in these elements to form a new set. This set is the "personal identification information" set of the close contacts who meet this query condition.

[0217] Corrected positioning

[0218] This step mainly performs correction calculations based on the initial positioning calculation results, which are completed by the monitoring background system. If there are elements in $dRSSI BT (s)(k)$, then execute this step; otherwise, skip this step. The specific calculation process of this step is as follows:

[0219] (1) Find the element with the smallest value in the set $Q_{dRSSI}$ BT (s)(k), denoted as $d$ BT (s)(k)(MAC BT (s)(k)(a(s)(k)(min))), where $min\in\{1, 2, \ldots, J(k)\}$;

[0220] (2) Query the "smartphone number" value of the element with Bluetooth communication MAC address $MAC BT (s)(k)(a(s)(k)(min)) in the set $Q_{Phone}$, denoted as $s$min ;

[0221] (3) Calculate the distance between the smartphone numbered s and the nearest smartphone using the three-dimensional space distance formula based on the coordinates obtained from the initial WiFi positioning, and let its value be dp WiFi (s)(k)(s min ), and its value is expressed as follows:

[0222] (4) Multiply d WiFi (s)(k)(MAC AP (max 1 ))、d WiFi (s)(k)(MAC AP (max 2 ))、 d WiFi (s)(k)(MAC AP (max 3 )) by to obtain its corrected value, which is respectively represented by d WiFi_fix (s)(k)(MAC AP (max 1 ))、d WiFi_fix (s)(k)(MAC AP (max 2 ))、d WiFi_fix (s)(k)(MAC AP (max3));

[0223] (5) Apply the maximum likelihood estimation method again based on the corrected ranging value to calculate the corrected value of the coordinates of the location where the smartphone is located, and its value is expressed as follows:

[0224] P fix (s)(k)=(A T A) -1 A T b fix (16)

[0225] Where:

[0226] P fix (s)(k) represents the coordinate value obtained by correcting the positioning of the location where the smartphone numbered s is located in the kth acquisition cycle, and its value is Where X fix (s)(k), Y fix (s)(k), Z fix (s)(k) respectively represent its X-axis, Y-axis, and Z-axis coordinate values;

[0227] b fix : is a matrix, and its value is where b fix (1) = X AP (MAC AP (max 1 )) 2 - X AP (MAC AP (max 3 )) 2 +Y AP (MAC AP (max 1 )) 2 -Y AP (MAC AP (max 3 )) 2 + Z AP (MAC AP (max 1 )) 2 -Z AP (MAC AP (max 3 )) 2 +d WiFi_fix (s)(k)(MAC AP (max 3 )) 2 - d WiFi_fix (s)(k)(MAC AP (max 1 )) 2 , b fix (2) = X AP (MAC AP (max 2 )) 2 -X AP (MAC AP (max 3 )) 2 +Y AP (MAC AP (max 2 )) 2 - Y AP (MAC AP (max 3 )) 2 +Z AP (MAC AP (max 2 )) 2 -Z AP (MAC AP (max 3 )) 2 +d WiFi_fix (s)(k)(MAC AP(max 3 )) 2 -d WiFi_fix (s)(k)(MAC AP (max 2 )) 2

[0228] Update the coordinates of the smartphone numbered s at the collection time k to:

[0229] P(s)(k) = (X fix (s)(k), Y fix (s)(k), Z fix (s)(k)) (17)

[0230] Combining these coordinate values in the order of the collection time, the movement trajectory of the smartphone in the monitoring area is obtained.

[0231] Application effect

[0232] The method of the present invention is applied in a 30,000-square-meter exhibition hall, using the WiFi-AP devices that provide WiFi services for the public in the hall. At the same time, it is required that the participating audience download the positioning APP provided by this method on their smartphones when entering the hall, and turn on the Bluetooth and WiFi switches. The positioning period is 2 seconds. After comprehensive testing, the positioning accuracy of the personnel trajectory in the hall by this method is within 4 meters, the query accuracy of close contacts within 10 meters is 100%, and the accuracy of the close contact distance is within 2 meters.

[0233] Randomly select the movement trajectory of a spectator's smartphone and compare it with the positioning trajectory of this method as Figure 3 shown.

[0234] The maximum positioning error is 2.89 meters, and the minimum positioning error is 0.72 meters;

[0235] When its coordinates are (30, 12.5, 1.3), the list of its actual close contacts and distances detected by the method of the present invention is shown in Table 1 below:

[0236] Table 1

[0237]

[0238] In summary, this method has high accuracy in calculating the personnel trajectory and the distance of close contacts, good real-time performance and accurate detection. At the same time, the implementation of this method does not require the investment of special hardware, and only needs to deploy or use the existing WiFi-AP devices in the area to be monitored and the smartphones carried by personnel. The construction cost is low, the implementation is fast, and the monitored personnel are unaware of the monitoring during the monitoring process, and the application experience is good.

[0239] The present invention provides a method for indoor personnel trajectory positioning and close contact personnel query based on integrated positioning. There are many methods and approaches to specifically implement this technical solution. The above description is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art of this technology, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention. Each component not clearly defined in this embodiment can be implemented by existing technologies.

Claims

1. Indoor personnel trajectory positioning and close contact personnel query method based on integrated positioning, characterized in that, it includes the following steps: Step 1, deploy WiFi-AP devices; Step 2, collect data; Step 3, construct a positioning feature equation; Step 4, perform initial positioning calculation; Step 5, correct the positioning; Step 1 includes: installing WiFi-AP devices in the area that requires epidemic prevention monitoring. Suppose there are W installed WiFi-AP devices, record the MAC address of each WiFi-AP device, and set the MAC address of the w-th AP device as MAC AP (w), where w ∈ {1, 2, 3, ……, W}; Establish a three-dimensional coordinate system for the building. Select the southwest corner of the first floor of the building as the origin of the coordinate system, the due north direction as the positive direction of the Y-axis, the due east direction as the positive direction of the X-axis, and the vertically upward direction as the positive direction of the Z-axis. Based on the coordinate system, record the installation position of each WiFi-AP device. The installation position of the w-th AP device is set as P AP (MAC AP (w)), and its value is shown as follows: P AP (MAC AP (w)) = (X ap (MAC AP (w)), Y ap (MAC AP (w)), Z ap (MAC AP (w))) (1) Wherein: X ap (MAC AP (w)) represents the X coordinate value of the WiFi-AP device with the MAC address MAC AP (w); Y ap (MAC AP (w)) represents the Y coordinate value of the WiFi-AP device with the MAC address MAC AP (w); Z ap (MAC AP (w)) represents the Z coordinate value of the WiFi-AP device with the MAC address MAC AP (w); After the WiFi-AP device is installed, it will continuously broadcast data packets with its own WiFi communication MAC address to the surrounding; Step 2 includes: Step 2-1, obtain the personnel identification information through the personnel's smart phone, expressed as follows: Phone(s)=(s,n,MAC BT ) (2) Where: Phone(s) represents the combined identification information corresponding to the smartphone numbered s; n is the personal identification information; MAC BT is the MAC address of the Bluetooth communication of the smartphone; Combine all the registered smart phones' Phone(s) to obtain the smart phone identification information set, denoted as QPhone, and its value is expressed as follows: QPhone = {Phone(1), Phone(2), ……, Phone(s), …} Step 2-2, collect positioning signals; Step 2-2 includes: when a person enters the monitoring area with a smart phone, turn on the WiFi signal and Bluetooth signal switches of the smart phone, and perform the following steps: Step 2-2-1, initialization: set the Bluetooth module of the smart phone to work in both slave and master working modes at the same time. The slave working mode is that the smart phone Bluetooth module continuously broadcasts data packets containing its own Bluetooth communication MAC address to the surrounding, but cannot establish a connection with the central device; while the master working mode is that the smart phone Bluetooth module can scan peripheral Bluetooth devices and obtain the data packets broadcast by peripheral Bluetooth devices and their Bluetooth signal strengths; Step 2-2-2, the smart phone collects the WiFi signal strength values of the data broadcast by each surrounding WiFi-AP device and the Bluetooth signal strength values of the data broadcast by other smart phone Bluetooth modules at the current position in a cyclic manner with a unified collection period T. Suppose that at the collection moment k, I(k) WiFi signal strength values of the data broadcast by WiFi-AP devices and J(k) Bluetooth signal strength values of the data broadcast by other smart phone Bluetooth modules are collected; Select three values with the largest magnitudes from the WiFi signal strength values broadcast by the I(k) WiFi-AP devices to form a set QRSSI WiFi (s)(k), whose value is represented as follows: QRSSI WiFi (s)(k) = {RSSI WiFi (s)(k)(MAC AP (max 1 ))), RSSI WiFi (s)(k)(MAC AP (max 2 )),RSSI WiFi (s)(k)(MAC AP (max 3 ))}(3) Wherein: k is the collection moment, and it is collected once every interval T, and the starting collection moment value can be divisible by T; RSSI WiFi (s)(k)(MAC AP (max 1 ) represents the WiFi signal strength value of the broadcast data of the WiFi-AP device with the MAC address MAC collected by the smartphone numbered s at the kth collection moment AP (max 1 ) where MAC AP (max 1 ) represents the WiFi communication MAC address of the broadcast device WiFi-AP device corresponding to the signal value, where max 1 represents the device number of the WiFi-AP device with the strongest signal strength among the 3 strongest signal strength values, max 1 ∈ {1, 2, 3, ……, W}; RSSI WiFi (s)(k)(MAC AP (max 2 )) represents the WiFi signal strength value of the broadcast data of the WiFi-AP device with the WiFi communication MAC address of MAC AP (max 2 ) collected by the smartphone numbered s at the kth collection moment, where MAC AP (max 2 ) represents the WiFi communication MAC address of the broadcast device WiFi-AP device corresponding to the signal value, where max 2 represents the device number of the second-strongest WiFi-AP device among the 3 strongest signal strength values, max 2 ∈ {1, 2, 3, ……, W}; RSSI WiFi (s)(k)(MAC AP (max 3 )) represents the WiFi signal strength value of the broadcast data of the WiFi-AP device with the WiFi communication MAC address MAC collected by the smartphone numbered s at the k collection moment AP (max 3 )), where MAC AP (max 3 ) represents the WiFi communication MAC address of the broadcast device WiFi-AP device corresponding to this signal value, where max 3 represents the device number of the 3rd strongest WiFi-AP device among the 3 strongest signal strength values, max 3 ∈ {1, 2, 3, ……, W}; Sort the Bluetooth signal strength values broadcast by J(k) other smartphone Bluetooth modules collected in descending order, and generate a number for each Bluetooth signal strength value, denoted by a(s)(k)(j), where s is the number of the data collection smartphone, k is the collection time, and j is an integer j ∈ {1, 2,..., J(k)}; Combine the Bluetooth signal strength values to obtain a set QRSSI BT (s)(k), and its value is expressed as follows: Where: RSSI BT (s)(k)(MAC BT (a(s)(k)(j))) represents the Bluetooth signal strength value of the smartphone with the serial number s at the kth collection moment, when the Bluetooth communication MAC address collected is MAC BT (a(s)(k)(j)), where MAC BT (a(s)(k)(j)) represents the Bluetooth communication MAC address value of the broadcasting smartphone; Step 3 includes: Step 3-1, establish the relationship equation between WiFi signal strength and distance; Step 3-2, establish the relationship equation between Bluetooth signal strength and distance; Step 3-1 includes: the formula of the signal propagation model Shadowing model is as follows: Where: RSSI R is the signal strength value received at the receiving point; RSSI 0 is the signal strength value received at the reference point; γ is the transmission medium factor; d is the distance between the receiving point and the transmitting point; d 0 is the distance between the reference point and the transmitting point; Then perform the following steps: Step a1, select a reference point 1 meter away from the WiFi-AP device within the monitoring area, i.e., d 0 is 1 meter; Step a2, detect the WiFi signal strength value emitted by the WiFi-AP device at a distance of 1 meter and record it, which is the RSSI 0 value; Step a3, detect the WiFi signal strength value emitted by the WiFi-AP device at a distance of 5 meters from it and record it, thus obtaining a set of d and RSSI R ; Step a4, substitute d 0 , RSSI 0 , d, RSSI R into Equation (5) to obtain the value of the transmission medium factor γ of the WiFi-AP device in this detection environment; Obtain the formula of the signal propagation strength and distance of each WiFi-AP through steps a1 to a4, as follows: Wherein: RSSI WiFi (s)(k)(MAC AP (w)) represents the WiFi signal strength value of the broadcast data of the WiFi-AP device with the MAC address of MAC AP (w) collected by the smart phone numbered s in the kth collection cycle; RSSI WiFi (MAC AP (w)) 0 Indicates the transmitted WiFi signal strength value at a distance of 1 meter from the WiFi-AP device with the WiFi communication MAC address of MAC AP (w); γ(MAC AP (w)) represents the transmission medium factor of the WiFi-AP device with WiFi communication MAC address MAC AP (w) within the monitoring area; d WiFi (s)(k)(MAC AP (w)) represents the distance value of the smartphone numbered s in the k-th acquisition cycle from the WiFi-AP device with the WiFi communication MAC address of MAC AP (w) obtained by ranging based on the WiFi signal strength; Equation (6) is sorted out to obtain the following equation, that is, the relationship equation of the signal propagation signal strength and distance of each WiFi-AP device is obtained: Step 3-2 includes: the relationship equation between the wireless signal strength of smart phone Bluetooth communication and distance is expressed as follows: where: d BT (s)(k)(MAC BT (a(s)(k)(j)) represents the distance value of the smartphone numbered s at the kth acquisition moment from the smartphone with the Bluetooth communication MAC address of MAC BT (a(s)(k)(j)); Step 4 includes: Step 4-1, preliminary positioning of the smartphone: Substitute the elements in the QRSSI WiFi (s)(k) set into Equation (7) to obtain d WiFi (s)(k)(MAC AP (max 1 ))、d WiFi (s)(k)(MAC AP (max 2 )) and d WiFi (s)(k)(MAC AP (max 3 )); Calculate the location of the smart phone using the maximum likelihood estimation method, and its value is expressed as follows: P c (s)(k) = (A T A) -1 A T b (9) Where: P c (s)(k) represents the coordinates obtained from the preliminary positioning calculation of the smartphone numbered s in the k-th acquisition cycle, and its value is Where X c (s)(k), Y c (s)(k), Z c (s)(k) represent the X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value respectively; A is a matrix, and its value is b is a matrix, and its value is where b(1) = X AP (MAC AP (max 1 )) 2 -X AP (MAC AP (max 3 )) 2 +Y AP (MAC AP (max 1 )) 2 -Y AP (MAC AP (max 3 )) 2 +Z AP (MAC AP (max 1 )) 2 -Z AP (MAC AP (max 3 )) 2 +d WiFi (s)(k)(MAC AP (max 3 )) 2 -d WiFi (s)(k)(MAC AP (max 1 )) 2 and b(2) = X AP (MAC AP (max 2 )) 2 -X AP (MAC AP (max 3 )) 2 +Y AP (MAC AP (max 2 )) 2 -Y AP (MAC AP (max 3 )) 2 +Z AP (MAC AP (max 2 )) 2 -Z AP (MAC AP (max 3 )) 2 +d WiFi (s)(k)(MAC AP (max 3 )) 2 -d WiFi (s)(k)(MAC AP (max 2 )) 2 Record the coordinates of the smart phone numbered s at the collection moment k as P(s)(k), and its value is set as: P(s)(k) = (X c (s)(k), Y c (s)(k), Z c (s)(k)) (10); Step 4-2, calculate the distance between smart phones: Substitute the elements in QRSSI BT (s)(k) into Equation (8) in sequence to obtain a value, which forms a new set, that is, obtain the set QdRSSI of the distance values obtained by ranging the smartphone with other surrounding smartphones based on Bluetooth signals at the acquisition moment k BT (s)(k), and its value is represented as follows: Among them: QdRSSI BT (s)(k) represents the set of distance values obtained by ranging the s-th smart phone with other surrounding smart phones based on Bluetooth signals at the k-th moment; In step 4-2, the following method can be used to query close contact personnel: Set the query conditions as follows: The identity identification information of the person to be queried is Pr, and the query time range is [t 1 , t 2 , where t 1 is the lower limit value of the time query range, and t 2 is the upper limit value of the time query range. Let all the acquisition moments covered by the time range be {k 1 , k 2 , …, k e}, where k 1 ≥ t 1 , and k e ≤ t 2 . If the close contact distance is within L meters, then the query method is as follows: Step b1, find all elements in the QPhone set with the personal identification information Pr. Suppose F elements are found, extract the smartphone numbers in the elements, and form a new set, denoted as {s 1 , s 2 , …, s F}; s F is the smartphone number of the F-th element among the F elements with the personal information Pr found from the QPhone set; Step b2, find out all the distance value sets Qs of all smartphones with the acquisition time values being {k 1 , k 2 , …, k e} and the numbers being in {s 1 , s 2 , …, s F}, which are obtained by ranging other surrounding smartphones based on Bluetooth signals, as shown below: Step b3, find out each subset QdRSSI in the set Qs BT (s f )(k e ) elements whose values are less than or equal to L, and form a new set Qsm with the elements less than or equal to L. Its value is expressed as follows: where: JJ(s f )(k e ) represents the number of elements in the set QdRSSI BT (s f )(k e ) whose element values are less than or equal to L; Step b4, extract the labels MAC of all elements in set Qsm BT (a(s f )(k e )(j)) to form a new set Qsmm, whose value is represented as follows: Step b5: Find all elements in the QPhone set whose Bluetooth communication MAC address values are in the set Qsmm, and extract the personal identification information in these elements to form a new set, which is the personal identification information set of close contacts that meets the query conditions; Step 5 includes: Step 5-1, find QdRSSI BT The element with the smallest value in the (s)(k) set, denoted as d BT (s)(k)(MAC BT (s)(k)(a(s)(k)(min)), min ∈ {1, 2, …, J(k)}; Step 5-2, query the smartphone number value of the (s)(k)(a(s)(k)(min)) element with the Bluetooth communication MAC address of MAC in the set QPhone, and set it as s BT (s)(k)(a(s)(k)(min)) element, and set it as s min ; Step 5-3: Based on the coordinates obtained from the initial WiFi positioning, use the three-dimensional space distance formula to calculate the distance dp between the smartphone numbered s and the smartphone closest to it. WiFi (s)(k)(s min ) is expressed as follows: Step 5-4, successively take d WiFi (s)(k)(MAC AP (max 1 ))、d WiFi (s)(k)(MAC AP (max 2 ))、d WiFi (s)(k)(MAC AP (max 3 )) multiply by to obtain their corrected values, which are respectively represented by d WiFi_fix (s)(k)(MAC AP (max 1 ))、d WiFi_fix (s)(k)(MAC AP (max 2 ))、d WiFi_fix (s)(k)(MAC AP (max 3 )); Step 5-5: Based on the corrected ranging value, apply the maximum likelihood estimation method again to calculate the corrected value of the coordinates of the location where the smartphone is located, expressed as follows: P fix (s)(k) = (A T A) -1 A T b fix (16) Where: P fix (s)(k) represents the coordinate value obtained by correcting the positioning of the smartphone numbered s at the k-th acquisition cycle, Where X fix (s)(k), Y fix (s)(k), Z fix (s)(k) represent its X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value respectively; b fix is a matrix, and its value is where b fix (1) = X AP (MAC AP (max 1 )) 2 - X AP (MAC AP (max 3 )) 2 + Y AP (MAC AP (max 1 )) 2 - Y AP (MAC AP (max 3 )) 2 + Z AP (MAC AP (max 1 )) 2 - Z AP (MAC AP (max 3 )) 2 + d WiFi_fix (s)(k)(MAC AP (max 3 )) 2 - d WiFi_fix (s)(k)(MAC AP (max 1 )) 2 , b fix (2) = X AP (MAC AP (max 2 )) 2 -X AP (MAC AP (max 3 )) 2 +Y AP (MAC AP (max 2 )) 2 -Y AP (MAC AP (max 3 )) 2 +Z AP (MAC AP (max 2 )) 2 -Z AP (MAC AP (max 3 )) 2 +d WiFi_fix (s)(k)(MAC AP (max 3 )) 2 -d WiFi_fix (s)(k)(MAC AP (max 2 )) 2 Update the coordinates of the smartphone numbered s at the acquisition moment k to: P(s)(k) = (X fix (s)(k), Y fix (s)(k), Z fix (s)(k)) (17) Combine the coordinate values in the order of the acquisition moments, and the movement trajectory of the smartphone within the monitoring area is obtained.

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