A control method, electronic device and system

Abstract

This application provides a control method, the method comprising: sending alarm information to a second device when a first device meets abnormal conditions based on first information, so that the second device controls the first device to move towards a target path based on the alarm information; receiving identification information collected by the first device according to the target path, the identification information being associated with the target path; and sending a movement command to the first device based on the identification information, so that the first device moves towards a target location according to the target path based on the movement command. This application also provides an electronic device and a system.

Description

Technical Field

[0001] This invention relates to control technology, and more specifically to a control method, electronic device, and system. Background Technology

[0002] With advancements in science and technology, most organizations now use specialized transport vehicles to collect waste. However, if these vehicles deviate from their designated routes during transport, staff often need to be on-site to inspect and resolve the issue. This not only requires dedicated staff to oversee the process, increasing personnel costs, but is also time-consuming and labor-intensive. Furthermore, current transport vehicles rely heavily on positioning systems for navigation and control when moving along real-time planned routes. Because positioning systems have relatively large errors, servers need to both calculate the route in real-time and send numerous commands to correct the vehicle's current path, thus increasing server load. Summary of the Invention

[0003] To address the existing technical problems, this application aims to provide a control method, electronic device, and system that can not only remotely control a transport vehicle to return to the correct transport path when it deviates from the transport path, but also reduce the server's query rate per second for transport vehicle requests by issuing movement commands based on the identification information collected by the transport vehicle, thereby reducing the server's load and improving the server's response speed for each transport vehicle request.

[0004] The technical solution of this application is implemented as follows:

[0005] According to one aspect of this application, a control method is provided, applied to a server, characterized in that the method includes:

[0006] If the first device meets the abnormal conditions based on the first information, an alarm message is sent to the second device so that the second device controls the first device to move toward the target path based on the alarm message.

[0007] The device receives identification information collected by the first device along the target path, and the identification information is associated with the target path.

[0008] Based on the identification information, a movement command is sent to the first device, so that the first device moves to the target location according to the target path based on the movement command.

[0009] In the above scheme, determining that the first device meets the abnormal conditions based on the first information includes at least one of the following:

[0010] If no identification information is received from the first device based on the target path within the first time period, it is determined that the first device meets the abnormal conditions;

[0011] If an alarm request is received from the first device, it is determined that the first device meets the abnormal conditions;

[0012] If the first distance between the current location of the first device and the target path is determined to satisfy the distance parameter based on the positioning information of the first device, then the first device is determined to meet the abnormal condition.

[0013] In the above scheme, determining that the first distance between the current location of the first device and the target path satisfies the distance parameter based on the positioning information of the first device includes:

[0014] Obtain the Bluetooth location information and 5G location information of the first device;

[0015] The first location of the first device is determined based on the Bluetooth positioning information, and the second location of the first device is determined based on the 5G positioning information;

[0016] The first location and the second location are fused and calculated according to the location weights of the Bluetooth base station and the 5G base station to determine the current location of the first device;

[0017] If the first distance between the current location and the target path is greater than or equal to the distance parameter, it is determined that the first distance satisfies the distance parameter.

[0018] In the above scheme, before performing the fusion calculation of the first location and the second location according to the location weights of the Bluetooth base station and the 5G base station, the method further includes:

[0019] The third position of the first device is determined based on the speed parameters and transportation time parameters of the first device, and the third position represents the actual position of the first device.

[0020] The first position and the second position are compared with the third position to determine the first position error of the Bluetooth base station and the second position error of the 5G base station.

[0021] The first position error and the second position error are calculated using the weighted least squares method to determine the first position weight of the Bluetooth base station and the second position weight of the 5G base station.

[0022] The step of fusing the first location and the second location according to the location weights of the Bluetooth base station and the 5G base station to determine the current location of the first device includes:

[0023] The first position and the second position are fused and calculated according to the first position weight and the second position weight to determine the current position of the first device.

[0024] In the above scheme, after determining the first location weight of the Bluetooth base station and the second location weight of the 5G base station, the method further includes:

[0025] The first position, the second position, and the third position are calculated using the backpropagation (BP) algorithm for neural network errors to determine the third position error of the Bluetooth base station and the fourth position error of the 5G base station.

[0026] The first position weight is updated based on the third position error to obtain the third position weight of the Bluetooth base station; and the second position weight is updated based on the fourth position error to obtain the fourth position weight of the 5G base station.

[0027] The step of fusing the first location and the second location according to the location weights of the Bluetooth base station and the 5G base station to determine the current location of the first device includes:

[0028] The first position and the second position are fused and calculated according to the third position weight and the fourth position weight to determine the current position of the first device.

[0029] In the above scheme, determining the first location of the first device based on the Bluetooth positioning information includes:

[0030] Based on multiple sets of Bluetooth signal arrival angle (AOA) parameters sent by the Bluetooth base station, multiple fourth positions of the first device are determined; and based on multiple sets of first received signal strength (RSSI) parameters collected by the first device against the Bluetooth base station in an indoor environment, multiple fifth positions of the first device are determined.

[0031] The first position of the first device is determined by fusing the plurality of fourth positions and the plurality of fifth positions using a decision tree model.

[0032] In the above scheme, determining the second location of the first device based on the 5G positioning information includes:

[0033] Based on multiple sets of Direction of Arrival (DOA) parameters sent by the 5G base station, the sixth position of the first device is determined; and based on multiple sets of second RSSI parameters collected by the first device in an indoor environment for the 5G base station, the seventh position of the first device is determined.

[0034] The second position of the first device is determined by fusing the sixth and seventh positions using a decision tree model.

[0035] In the above scheme, determining the seventh location of the first device based on multiple sets of second RSSI parameters collected by the first device against the 5G base station in an indoor environment includes:

[0036] If no historical positioning parameters matching the positioning parameters sent by the 5G base station are found in the Channel State Information (CSI) fingerprint database, the transmission distance of multiple sets of second RSSI between the first device and multiple 5G base stations is determined based on the multiple sets of second RSSI parameters.

[0037] The eighth position of the first device is determined based on the multiple sets of second RSSI transmission distances;

[0038] If the eighth position meets the error condition with the actual position of the first device, the eighth position is corrected based on the historical positioning parameters in the CSI fingerprint database to obtain the seventh position of the first device.

[0039] In the above scheme, the step of fusing the first location and the second location according to the location weights of the Bluetooth base station and the 5G base station to determine the current location of the first device includes:

[0040] The first position and the second position are fused according to the position weights of the Bluetooth base station and the 5G base station to obtain the fused position of the Bluetooth base station and the 5G base station;

[0041] The merged positions of the Bluetooth base station and the 5G base station are filtered and corrected to obtain the current position of the first device.

[0042] In the above scheme, the target path includes at least one sub-path;

[0043] The step of receiving the identification information collected by the first device based on the target path, wherein the identification information is associated with the target path, includes:

[0044] The first device receives identification information collected based on the at least one sub-path, where each identification information corresponds to a sub-path.

[0045] According to a second aspect of this application, a control method is provided, applied to a first device, characterized in that the method further includes:

[0046] Identification information is collected according to the target path, and the identification information is associated with the target path;

[0047] Send the identification information to the server;

[0048] Receive the movement instruction sent by the server based on the identification information;

[0049] Based on the movement command, move to the target location according to the target path.

[0050] The method in the above scheme further includes:

[0051] Multiple sets of first RSSI parameters for Bluetooth base stations and multiple sets of second RSSI parameters for 5G base stations were collected in an indoor environment.

[0052] The server sends the multiple sets of first RSSI parameters and the multiple sets of second RSSI parameters to the server so that the server can determine the current location of the first device based on the multiple sets of first RSSI parameters and the multiple sets of second RSSI parameters.

[0053] According to a third aspect of this application, an electronic device is provided, characterized in that the electronic device comprises:

[0054] The sending unit is configured to send alarm information to the second device when the first device meets the abnormal conditions based on the first information, so that the second device controls the first device to move towards the target path based on the alarm information; and to send a movement command to the first device based on the identification information, so that the first device moves towards the target location according to the target path based on the movement command.

[0055] A receiving unit is configured to receive the identification information collected by the first device based on the target path, wherein the identification information is associated with the target path.

[0056] According to a fourth aspect of this application, an electronic device is provided, characterized in that the electronic device comprises:

[0057] A data acquisition unit is used to acquire identification information according to a target path, wherein the identification information is associated with the target path;

[0058] The sending unit is used to send the identification information to the server;

[0059] A receiving unit is configured to receive a movement instruction sent by the server based on the identification information;

[0060] A moving unit is used to move to a target location according to the target path based on the moving command.

[0061] According to a fifth aspect of this application, a control system is provided, characterized in that the system comprises:

[0062] The first device is configured to collect multiple sets of first RSSI parameters for Bluetooth base stations and multiple sets of second RSSI parameters for 5G base stations in an indoor environment, and send the multiple sets of first RSSI parameters and the multiple sets of second RSSI parameters to a server; it is also configured to collect identification information according to a target path, and send the identification information to the server, wherein the identification information is associated with the target path; it is also configured to send an alarm request to the server; and it is also configured to move to a target location according to the target path based on a movement command sent by the server.

[0063] A Bluetooth base station is used to send AOA parameters for the first device to the server;

[0064] The 5G base station is used to send DOA parameters for the first device to the server;

[0065] The server is configured to send alarm information to the second device when it is determined that the first device meets abnormal conditions based on the AOA parameters, the DOA parameters, the multiple sets of first RSSI parameters, and the multiple sets of second RSSI parameters; it is also configured to send alarm information to the second device when it is determined that the first device meets abnormal conditions based on the alarm request; it is also configured to send alarm information to the second device when it is determined that the first device meets abnormal conditions based on the reception duration of the current identification information; and it is also configured to send a movement command to the first device based on the identification information sent by the first device.

[0066] The second device is used to control the first device to move toward the target path based on the alarm information.

[0067] The control method, apparatus, and system provided in this invention send an alarm message to a second device when an abnormal condition is determined to be met by a first device. The second device then controls the first device to move towards a target path based on the alarm message. This allows the second device to remotely control the first device to return to the correct target path if the first device deviates from it, eliminating the need for on-site manual intervention. This reduces labor costs and improves the transportation efficiency of the first device by minimizing the time required for on-site processing. Furthermore, the server sends a movement command to the first device based on the identification information collected by the first device, enabling the first device to move towards the target location. This reduces the server's load and improves the server's response speed to requests from the first device. Attached Figure Description

[0068] Figure 1 This is a schematic diagram of the implementation process of the control method in this application. Figure 1 ;

[0069] Figure 2This is a schematic diagram of the method for fusing Bluetooth positioning and 5G positioning in this application;

[0070] Figure 3 This is a schematic diagram illustrating the flow implementation of the control method in this application. Figure 2 ;

[0071] Figure 4 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 1 ;

[0072] Figure 5 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 2 ;

[0073] Figure 6 This is a schematic diagram of the structural composition of the control system in this application;

[0074] Figure 7 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 3 . Detailed Implementation

[0075] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0076] Figure 1 This is a schematic diagram of the implementation process of the control method in this application. Figure 1 ;like Figure 1 As shown, the method includes:

[0077] Step 101: If the first device meets the abnormal conditions based on the first information, an alarm message is sent to the second device so that the second device controls the first device to move towards the target path based on the alarm message.

[0078] In this application, the method can be applied to a server that can determine whether a first device meets an abnormal condition based on first information.

[0079] In one implementation, the server may store a transport path, and this transport path corresponds to identification information. An image acquisition device (such as a camera) is installed on the first device. As the first device moves along the transport path towards the target location, it can acquire the identification information through the image acquisition device and send it to the server. If the server does not receive the identification information sent by the first device based on the target path within a first time period (e.g., within 1 minute), it determines that the first device meets an abnormal condition and sends an alarm message to a second device, enabling the second device to control the first device to move towards the target path based on the alarm message.

[0080] Here, the first device can be a transport vehicle capable of transporting goods, such as hospital waste, garbage, restaurant food, etc. The abnormal condition can refer to the first device deviating from the transport route.

[0081] In another implementation, the first device can also send an alarm request to the server if it deviates from the transport path. If the server receives the alarm request sent by the first device, it determines that the first device meets the abnormal conditions and sends alarm information to the second device through the second communication connection, so that the second device controls the first device to move to the target path based on the alarm information.

[0082] Here, if the first device fails to collect identification information or fails to collect it, it can be determined that the first device has deviated from the transportation path.

[0083] Here, the second device can be a control terminal for remotely controlling the first device, such as a mobile phone, tablet, computer, watch, etc., used by staff. When the second device receives an alarm message sent by the server, it can remotely control the first device to move to the target path based on the alarm message. Alternatively, if remote control of the first device based on the alarm message fails, or if it is impossible to remotely control the first device to move to the target path, the first device can be viewed on-site and moved to the target path.

[0084] In the third implementation, the server can also obtain the location information of the first device. If the server determines that the first distance between the current location of the first device and the target path meets the distance parameter based on the location information, it determines that the first device meets the abnormal condition. Then, it sends an alarm message to the second device through the second communication connection so that the second device controls the first device to move towards the target path based on the alarm message.

[0085] Here, the server can also establish communication connections with Bluetooth base stations and 5G base stations. Based on this communication connection, it can receive Bluetooth positioning information sent by the Bluetooth base station for the first device, and 5G positioning information sent by the 5G base station for the first device. Based on the Bluetooth positioning information, a first location of the first device can be determined, and based on the 5G positioning information, a second location of the first device can be determined. Then, according to the location weights of the Bluetooth base station and the 5G base station, the first location and the second location can be fused to determine the current location of the first device. Next, the server can also calculate a first distance between the current location of the first device and the target path. If the first distance between the current location of the first device and the target path is greater than or equal to a distance parameter, then the first distance is determined to satisfy the distance parameter.

[0086] In this application, due to the different environments of 5G base stations and Bluetooth base stations, the positioning errors obtained by the two are also different. For example, in a closed space surrounded by walls, the positioning errors of the two are relatively large, and it is necessary to reasonably allocate the weights of Bluetooth base stations and 5G base stations to avoid excessive errors in the fusion result. Therefore, before the server performs fusion calculation on the first position and the second position according to the position weights of Bluetooth base stations and 5G base stations, the server can also determine the third position of the first device based on the speed parameters and transportation time parameters of the first device, where the third position represents the actual position of the first device; then the first position and the second position are compared with the third position respectively, and the first position error of the Bluetooth base station and the second position error of the 5G base station are determined according to the comparison results; then the first position error and the second position error are calculated by weighted least squares method to determine the first position weight of the Bluetooth base station and the second position weight of the 5G base station.

[0087] Specifically, based on the comparison results, the position error of the positioning base station with the smallest error to the third position can be used as a reference. At the same time, the data and errors used to locate other base stations are recorded. Then, based on the position error of each base station and the reference value, the weight of each positioning base station (5G base station and Bluetooth base station) is calculated by weighted least squares method.

[0088] In this application, when the server performs a fusion calculation on the first location and the second location according to the location weights of the Bluetooth base station and the 5G base station to determine the current location of the first device, it can specifically perform a fusion calculation on the first location and the second location according to the weights of the first location and the second location to determine the current location of the first device.

[0089] In this application, after determining the first position weight of the Bluetooth base station and the second position weight of the 5G base station, the server can further calculate the first position, the second position, and the third position using a neural network error back propagation algorithm (BP) to determine the third position error of the Bluetooth base station and the fourth position error of the 5G base station; then, the server updates the first position weight based on the third position error to obtain the third position weight of the Bluetooth base station; and updates the second position weight based on the fourth position error to obtain the fourth position weight of the 5G base station.

[0090] In this application, when the server performs a fusion calculation on the first location and the second location according to the location weights of the Bluetooth base station and the 5G base station to determine the current location of the first device, it can also perform a fusion calculation on the first location and the second location according to the third location weight and the fourth location weight to determine the current location of the first device.

[0091] Here, the backpropagation algorithm avoids the need for extensive manual calculations to set neural network parameters. Gradient descent is also incorporated to avoid calculating every single parameter, improving efficiency. The BP neural network consists of an input layer, hidden layers, and an output layer. Its operation involves forward propagation of the working signal and backward propagation of the error signal. The current real-time location, 5G positioning location, and BLE positioning location are used as the input dataset. First, the weights of the BP neural network are initialized, with initial weights set to random numbers between (-1, 1) and initial biases set to random numbers between (0, 1). Then, a weighted summation is performed on the nodes from the input layer to the hidden layer, using the following formula:

[0092]

[0093] Where n represents the data of each node in the input layer, i represents a node in the input layer (1 represents the first node), W represents the weights of each node in the input layer, X represents the input value of each node in the input layer, and a represents the input layer to hidden layer bias. After summing, the input layer is activated using the sigmoid function, where the activation function is:

[0094]

[0095] Here, the activation function is the weighted sum obtained by formula (1) before activating the output layer, where x is the result of each node in the hidden layer calculated by formula (1). s(x) is the sigmoid result of the current node.

[0096] After activation, a weighted summation is performed on the hidden layer -> output layer nodes. The summation formula is as follows:

[0097]

[0098] Where n represents the data of each node in the hidden layer, i represents a node in the hidden layer (1 represents the first node), w represents the weights of each node in the hidden layer, and x represents the input values ​​of each node in the hidden layer. b represents the hidden layer to output layer bias. The sigmoid function is then used to activate the output layer, and finally, the error of the samples is calculated using the following formula:

[0099] E = (yS(x))(1-S(x))S(x)

[0100] Where y is the output layer sample value, and s(x) is the sigmoid result of the current node.

[0101] The forward propagation process is now complete. The backward propagation begins, and the process is similar to the forward propagation. First, a weighted summation is performed on the output layer -> hidden layer values ​​to calculate the hidden layer error. The calculation formula is as follows:

[0102]

[0103] Where s(x) is the sigmoid result of the current node. We perform a weighted summation of the errors for each node in the right layer. Here, we initialize the learning rate γ to 0.1 and update the weights and biases of the input layer -> hidden layer and hidden layer -> output layer based on the calculated errors.

[0104]

[0105]

[0106] Where s(x) is the sigmoid result of the current node, E is the error of the current node, and w and a are the updated weights and biases.

[0107] This completes one learning iteration. The BP neural network will then be iteratively trained, with the input and output values ​​and the weights of the two localization systems continuously updated. The final result will be obtained after the specified number of training iterations.

[0108] In this application, the first device is further equipped with a positioning terminal module for an indoor positioning system. This positioning terminal module includes a 5G positioning module and a Bluetooth positioning module. The 5G positioning module also serves as an IoT communication system. The 5G positioning module employs 5G NR-Light technology, ensuring certain medium-to-high speeds, medium-to-low latency, and reliability requirements. Simultaneously, it reduces equipment cost and complexity.

[0109] In this application, the first device can establish a communication connection with a Bluetooth base station via the Bluetooth positioning module and with a 5G base station via the 5G positioning module. In an indoor environment, the first device can also send Bluetooth signals to the Bluetooth base station via the Bluetooth positioning module and 5G signals to the 5G base station via the 5G positioning module, collecting multiple sets of first RSSI parameters from the Bluetooth base station and multiple sets of second RSSI parameters from the 5G base station. These parameters are then sent to a server via the first communication connection. The Bluetooth base station can also send multiple sets of Bluetooth Angle-of-Arrival (AOA) parameters to the server, and the 5G base station can send multiple sets of Direction of Arrival (DOA) parameters to the server. Based on the AOA and first RSSI parameters, the server can determine the first device's first location. Based on the DOA and second RSSI parameters, the server can determine the first device's second location.

[0110] Here, the Bluetooth base station can calculate the AOA parameters by receiving Bluetooth signals (such as direction-finding data packets) sent to it by the first device. The Bluetooth base station can contain different antenna arrays. Because the spatial positions of the different antennas are different, the path length of the Bluetooth signal reaching each antenna is also different. The Bluetooth base station can obtain phase information by performing I / Q sampling on the signal on each antenna. Based on the phase information of two antennas, the phase difference can be obtained. Then, according to the phase array antenna scanning principle, the AOA parameters of the Bluetooth base station can be obtained using the formulas for phase difference and beam pointing angle.

[0111] Since the scanning principle of phased array antennas and the formula for beam pointing angle are known technologies, the specific calculation formula for calculating the AOA angle parameter will not be described in detail here.

[0112] In this application, after receiving multiple sets of AOA parameters sent by the Bluetooth base station to the first device, the server can calculate the two sets of AOA parameters separately using the triangulation method to obtain multiple fourth positions (i.e., Bluetooth positions) of the first device.

[0113] In this application, since RSSI is proportional to the logarithm of the distance, after receiving multiple sets of first RSSI parameters sent by the first device, the server can also calculate the multiple sets of first RSSI parameters using the RSSI ranging formula to obtain multiple RSSI transmission distances between the first device and more than three Bluetooth base stations, and calculate the transmission distance of each RSSI according to the multilateral positioning method to obtain multiple fifth positions of the first device.

[0114] In this application, when the server determines the first position of the first device based on multiple sets of AOA parameters and multiple sets of first RSSI parameters, it can specifically perform fusion calculation on the multiple fourth positions and the multiple fifth positions based on the decision tree model generated by the C4.5 algorithm to determine the first position of the first device.

[0115] Here, the server can use a decision tree model to fuse multiple fourth positions and multiple fifth positions. First, the dataset formed by the multiple fourth and fifth positions can be divided into feature segments to find the optimal feature, which is the fused position. For example, if the dataset includes 10 features (multiple fourth positions determined based on AOA parameters and multiple fifth positions determined based on RSSI transmission distance), the average position value of the 10 features is calculated. Then, the position of each of the 10 features is compared with this average position value to obtain the error for each feature. The position with the smallest error is then determined as the first position of the first device. Positions with larger errors can be directly deleted.

[0116] Here, during the training of the decision tree, data collection is first required to collect multiple sets of AOA positioning locations from multiple Bluetooth base stations and multiple sets of RSSI positioning locations from the first RSSI to establish datasets. Then, the datasets are divided according to the information gain ratio to determine the optimal feature (i.e. the optimal fusion location) from the datasets.

[0117] Here, the purpose of partitioning the dataset is to traverse the collected data and add data that meets the criteria to the returned dataset. The information gain ratio is the ratio of information gain to the empirical entropy of the training set. Features are defined based on data from AOA or RSSI fingerprint databases. After selecting the optimal features, a decision tree can be built based on the dataset features.

[0118] Here, during the learning process of the decision tree, the node splitting process will be repeated continuously to classify the training samples as much as possible, which may result in too many tree branches. Therefore, some branches (such as features with large distance differences) can be actively removed to reduce the risk of overfitting. After training is completed and the decision tree is constructed, it can be used for actual data processing.

[0119] In this application, when using 5G base stations to locate the first device, at least two 5G base stations are required. The more data collected, the more location data is obtained, and the higher the positioning accuracy of the first device. Specifically, when the first device sends a 5G signal (such as a signal transmitted via Orthogonal Frequency Division Multiplexing (OFDM)) to the 5G base station, it first needs to be mixed with a 5G carrier to perform Quadrature Amplitude Modulation (QAM) modulation on the bit stream, modulating the current signal to the 5G signal band. Then, serial-to-parallel conversion and Inverse Fast Fourier Transform (IFFT) are performed sequentially to convert the parallel data into serial data. Due to inter-symbol interference, the subcarriers no longer maintain good orthogonality when the signal reaches the receiving end; therefore, a guard interval is added between symbols before transmission. The 5G signal is then transmitted to the 5G base station via the transmission module. After receiving an OFDM signal, the 5G base station first preprocesses the signal through its receiving module. This involves synchronizing the data frames to obtain their start positions and Fast Fourier Transform (FFT) windows, and then performing an FFT to convert the data from the time domain to the frequency domain. Following this conversion, compensation is made for losses caused by sampling frequency offset. Subcarriers with good channel conditions are selected and assigned different weights based on varying channel conditions. The data is then uploaded to an edge cloud server, where it is used to perform DOA (Depth of Average Ability) calculations using the Estimating Signal Parameter via Rotational Invariance Techniques (ESPRIT) method.

[0120] Here, OFDM (Orthogonal Frequency Division Multiplexing) can transmit a large amount of data even with narrow bandwidth. It converts high-speed data signals into parallel low-speed sub-data streams and divides the channel into several sub-channels. Isolation bands are set between sub-channels to reduce mutual interference between sub-channels, resulting in higher quality of the acquired signal.

[0121] In this application, after the 5G base station uploads n subcarriers with good channel conditions to the edge cloud server, the edge cloud server can form n data sequences from the data on the corresponding subcarriers in a frame, and then perform DOA estimation on each sequence using the ESPRIT method.

[0122] Here, the basic idea of ​​ESPRIT is to divide the data sequence into two completely identical subarrays with equal offset distances between the subarray elements. This distance reflects the fixed relationship between each subarray, i.e., the rotation invariance of the subarrays. The incident angles of the two subarrays differ only by a rotation invariance factor, which contains the direction of arrival information of each incident signal.

[0123] The following is a method for finding DOA parameters using the least squares method:

[0124]

[0125] in, U is a rotation-invariant relation matrix. s Let H be the noise subspace spanned by the vectors corresponding to the large eigenvalues; H represents the rotation, transpose, and conjugate of the matrix. After obtaining the matrix, use the formula... Obtain the angle of arrival (DOA) parameters. for A diagonal matrix in the array. τ is the arrival time delay of adjacent elements, θ k Let DOA be the distance between array elements, and |Δ| be the distance between array elements.

[0126] Each subcarrier is assigned a weight based on the channel conditions, and the DOA parameters are weighted and averaged to obtain a target angle for the first device.

[0127] In this application, after receiving multiple target angles sent by the edge cloud server, the server can calculate the two sets of target angle parameters using triangulation to obtain multiple sixth positions (i.e., 5G positions) of the first device.

[0128] In this application, since RSSI is proportional to the logarithm of the distance, after receiving multiple sets of second RSSI parameters sent by the first device, the server can also calculate the multiple sets of second RSSI parameters using the RSSI ranging formula to obtain multiple RSSI transmission distances between the first device and more than three 5G base stations, and calculate the transmission distance of each RSSI according to the multilateral positioning method to obtain multiple seventh locations of the first device.

[0129] In this application, when the server determines the second position of the first device based on multiple sets of DOA parameters and multiple sets of second RSSI parameters, it can specifically perform fusion calculation on the multiple sixth positions and the multiple seventh positions based on the decision tree model generated by the C4.5 algorithm to determine the second position of the first device.

[0130] For a specific decision tree model, please refer to the above description of Bluetooth base stations. The only difference is that the data set features in the decision tree are replaced with DOA parameters and the second RSSI parameters.

[0131] Existing technologies do not utilize the high bandwidth and low latency of 5G networks to upload data to the MEC edge cloud server for processing, resulting in long positioning delays. This application reduces data processing latency by processing data on the MEC edge cloud server and returning the processing results.

[0132] In this application, when the server determines the seventh location of the first device based on multiple sets of second RSSI parameters collected by the first device against 5G base stations in an indoor environment, it can first search for historical positioning parameters that match the positioning parameters sent by the 5G base station in the Channel State Information (CSI) fingerprint database. If no historical positioning parameters matching the positioning parameters sent by the 5G base station are found in the CSI fingerprint database, multiple sets of second RSSI transmission distances between the first device and multiple 5G base stations are determined based on the multiple sets of second RSSI parameters collected by the first device against the 5G base stations; and the eighth location of the first device is determined based on the multiple sets of second RSSI transmission distances. If the eighth location meets the error condition with the actual location of the first device, the eighth location is corrected based on the historical positioning parameters in the CSI fingerprint database to obtain the seventh location of the first device.

[0133] Here, when determining the multiple sets of second RSSI transmission distances between the first device and multiple 5G base stations based on the multiple sets of second RSSI parameters collected by the first device for 5G base stations, it can be achieved by an RSSI ranging model:

[0134]

[0135]

[0136]

[0137] Among them, RSSI AB To obtain the signal strength between points A and B using the RSSI ranging model, RSSI is the RSSI value received from point A at point B. Q and U are empirical constants, which can be calculated using the RSSI and the positions of three positioning base stations A, B, and C (here, environmental changes will cause changes in Q and U; the impact of environmental changes is reduced by estimating the two constants. The above formula yields Q and U from the three base stations, and the average value is taken to obtain the final Q and U); A, B, and C represent the x and y coordinates of the positions. AB This represents the RSSI value received from B at location A. RSSI AC This represents the RSSI value received from C at location A.

[0138] Then, by establishing error corrections for both multilateral positioning and CSI fingerprint positioning methods at each 5G base station, the location of the positioning terminal is obtained. Since the fingerprint database exists, the server can quickly match new positioning data with historical positioning data, reducing the time spent on calculation.

[0139] Here, 5G base stations can establish a CSI fingerprint database based on parameters such as latency, power, and frequency:

[0140]

[0141] Where h(t) is the fingerprint expression, t is a time point in the time domain, N is the total number of propagation paths, n is a path in the propagation path, 1 is the first path in the propagation path, and a n For channel gain, e- j2π∫ τ n τ represents the frequency offset, t represents time, and τ represents the frequency shift. n This refers to channel delay.

[0142] For example, if there are obstacles between 5G base station A and the target path where the first device is located, the data (latency, power, and frequency) of 5G base station A obtained by the backend server will be inaccurate. In this case, the data of 5G base station A is matched with the data (latency, power, and frequency) in the CSI fingerprint database. If the match is successful, the RSSI transmission distance is obtained directly. If the match fails, the RSSI transmission distance of 5G base station A needs to be calculated using the RSSI data of 5G base station A. Then, the target position is calculated based on the triangulation method. If the target position differs significantly from the actual position, data B (latency, power, and frequency) with a small error compared to the actual position is searched in the CSI fingerprint database. This data B is used to correct the data (latency, power, and frequency) of 5G base station A. The next time the data of 5G base station A is detected, data B is directly used to match the RSSI transmission distance in the CSI fingerprint database to obtain the target position.

[0143] This application accelerates data processing speed by establishing a CSI database for 5G base stations.

[0144] In this application, when the server performs a fusion calculation on the first position and the second position according to the position weights of the Bluetooth base station and the 5G base station to determine the current position of the first device, it can first perform a fusion calculation on the first position and the second position according to the position weights of the Bluetooth base station and the 5G base station to obtain the fused position of the Bluetooth base station and the 5G base station; and then filter and correct the fused position of the Bluetooth base station and the 5G base station to obtain the current position of the first device.

[0145] Here, the Kalman filter model can be used to filter and correct the fusion position of the Bluetooth base station and the 5G base station.

[0146] Since the filtering process of the Kalman filter model is an existing technique, it will not be described in detail here.

[0147] In this application, Bluetooth and 5G systems differ in device type, signal transmission method, and positioning calculation method. Bluetooth obtains the AOA angle parameters and RSSI of signal propagation through an antenna array, while 5G obtains the 5G network signal, DOA angle, and RSSI from the first device, combined with CSI error correction. Both positioning methods first obtain the position of the first device (positioning terminal), then combine and calculate these positions to achieve a more accurate location. Furthermore, machine learning models are incorporated into the AOA and RSSI positioning calculations, training the algorithms with massive amounts of data to achieve even greater accuracy.

[0148] In addition, in this application, the Bluetooth base station is connected to the cascade port of the 5G smart indoor distribution system, and the cascade port provides power to the terminal equipment (first device) of the Bluetooth base station, which solves the maintenance problem that the Bluetooth positioning module of the first device needs to replace the battery regularly. Moreover, the 5G base station can be deployed together with the Bluetooth base station, thereby reducing the time spent on base station deployment.

[0149] Step 102: Receive the identification information collected by the first device according to the target path, wherein the identification information is associated with the target path;

[0150] In this application, the second device can determine the transportation route based on the transportation start point information and the transportation destination information, and send the transportation route to the server. After receiving the transportation route, the server can assign identification information to the transportation route and establish a correspondence between the transportation route and the identification information.

[0151] For example, the identification information can be affixed to the ground at regular intervals along the transport route, or it can be projected onto the ground at regular intervals using a projection device. This allows the first device to acquire the identification information via its image acquisition unit as it moves along the target path.

[0152] Here, the identification information includes, but is not limited to, QR code information, RFID code information, barcode information, etc.

[0153] In this application, the server can also divide the transportation route into multiple sub-paths based on preset path parameters, assign an identification information to each sub-path, and establish an association between each sub-path and the corresponding identification information.

[0154] For example, the signage information can be posted on the ground between the start and end points of the corresponding sub-path, or the signage information can be projected onto the ground between the start and end points of the corresponding sub-path using a projection device.

[0155] The server receives identification information collected by the first device based on the at least one sub-path, where each identification information corresponds to a sub-path.

[0156] Step 103: Send a movement command to the first device based on the identification information, so that the first device moves to the target location according to the target path based on the movement command.

[0157] In this application, when the first device identifies the corresponding identification information along the target path and sends the identification information to the server, the server can identify the target path or target sub-path that the first device is currently traveling on based on the correspondence between the identification information and the path or sub-path, and thus can send a movement command to the first device based on the target path or target sub-path.

[0158] Here, the movement command includes, but is not limited to, commands that control the first device to move forward, backward, turn left, turn right, stop, etc.

[0159] For example, in a scenario involving the collection of hospital waste (hereinafter referred to as medical waste), department staff need to classify and place the medical waste in their department at designated medical waste collection points. The staff responsible for collecting the medical waste (also known as the second device) determines the transportation route based on the location information of the medical waste collection points in different departments and the location information of the central collection point, and sends this transportation route to the server. The server then divides the transportation route into multiple sub-paths, for example, 2 meters long, based on the total length of the route, and assigns a QR code label to each sub-path. Staff can affix the QR code label to the ground at the start and end points of the corresponding sub-path, or they can use a projection device to project the QR code label onto the ground at the start and end points of the corresponding sub-path. Thus, when the first device (also known as the transport vehicle) travels along the transportation route, it can collect the QR code label information on the ground through an image acquisition device (camera) and send the collected QR code label information to the server. Because the server stores the correspondence between each identifier and its corresponding sub-path, after receiving the QR code identifier information sent by the first device, the server can determine the current sub-path of the first device based on this correspondence, and then send a movement command to the first device based on that sub-path. Since the vehicle movement command in this application is issued entirely through communication between the collected ground QR code identifiers and the server, and the transportation path is also stored on the server, the server does not need to perform real-time path calculations or continuously issue commands to correct the path due to positioning errors, greatly reducing the server's load.

[0160] Here, medical waste at a collection point may come from one department or several neighboring departments. In this application, a transport vehicle (i.e., the first device) can transport only one type of medical waste, which facilitates the classification and treatment of medical waste. In addition, due to the large number of departments and types of medical waste, the demand for transport vehicles also increases accordingly. The characteristics of 5G enable that when a certain number of transport vehicles are running simultaneously, the server's instructions can be received by the transport vehicles in a timely manner, ensuring the normal operation of transportation.

[0161] In this application, the server issues movement commands to the first device based on the QR code identification information collected by the image acquisition device (such as a camera) on the target path, ensuring that the first device can move along the planned path. The first device can automatically transport goods from the starting point to the destination by recognizing and collecting QR codes on the path. Compared with the prior art of real-time path planning or pre-input of the planned path for the transport vehicle to move automatically by relying on the positioning system, the method of issuing commands through real-time communication during the journey reduces the probability of deviation from the path. The positioning system in this application can be used to send relevant alarm requests to the server if the first device deviates from the path during transportation, and when it is determined that the first device has deviated from the normal path, the server sends alarm information to the operator's second device, so that the operator can remotely control the first device to return to the prescribed path based on the second device, or manually operate the first device to the transportation destination on-site when remote control of the first device is not possible.

[0162] Here, if the first device deviates from the transportation path by more than 5 meters or fails to recognize the QR code within a certain period of time, the communication module on the first device will send an alarm request to the sending server.

[0163] This application utilizes a pre-planned route and QR codes for real-time communication between the transport vehicle and the server. The server only sends instructions when the transport vehicle starts or when a QR code is collected, reducing the server's QPS and improving its response speed to each transport vehicle's request. Compared to traditional IoT-based automated transport processes, this method introduces an indoor positioning system. Traditional methods using GPS positioning have poor accuracy in indoor environments, making it difficult for staff to remotely return the vehicle to the correct path, often requiring on-site inspection and troubleshooting. This method, using an indoor positioning system, provides more accurate positioning in indoor environments, allowing staff to view the real-time location of the transport equipment and remotely resolve issues such as route deviations that can be addressed with remote commands, eliminating the need for on-site intervention. When the transport vehicle deviates from the route, compared to GPS's difficulty in determining whether the vehicle has truly deviated indoors, the indoor positioning system provides more accurate real-time location tracking, resulting in more timely alarms. Therefore, the introduction of an indoor positioning system significantly automates the process and enhances the visibility of the transport vehicle and its route.

[0164] Figure 2 This is a schematic diagram of the method for fusing Bluetooth positioning and 5G positioning in this application, as shown below. Figure 2 As shown, it includes:

[0165] Step 201: The Bluetooth base station obtains phase information by sampling the I / Q signals on each antenna in the antenna array, obtains the phase difference based on the two phase information of the two antennas, and then obtains the AOA parameters of the Bluetooth base station by using the phase difference and beam pointing angle formula according to the phase array antenna scanning principle.

[0166] Step 202: The server calculates the two sets of AOA parameters using the three-point positioning method to obtain multiple AOA positioning positions of the first device.

[0167] Step 203: When the server obtains multiple sets of first RSSI parameters based on Bluetooth through the first device, it calculates the multiple sets of first RSSI parameters using the RSSI ranging formula to obtain the multiple RSSI transmission distances between the first device and more than three Bluetooth base stations.

[0168] Step 204: The server calculates the transmission distance of each RSSI according to the triangulation method to obtain multiple RSSI positioning positions of the first device.

[0169] Step 205: The server performs a fusion calculation on the AOA positioning location and RSSI positioning location based on the position weight of each Bluetooth base station to determine the Bluetooth location of the first device.

[0170] Here, the server can use a decision tree model to fuse AOA and RSSI location data. First, the dataset formed by the AOA and RSSI location data is divided into feature classes, and the optimal feature is identified; this optimal feature is the fused location. For example, if the dataset includes 10 features (AOA location determined by AOA parameters and RSSI location determined by RSSI transmission distance), the average location value of the 10 features is calculated. Then, the location of each of the 10 features is compared with this average location value to obtain the error for each feature. The location with the smallest error is then determined as the terminal location. Locations with larger errors can be directly deleted.

[0171] Step 206: The 5G base station collects the OFDM signal sent by the first device (positioning terminal);

[0172] Step 207: After processing the OFDM signal, the 5G base station (5G positioning base station) uploads the data to the edge cloud server, which then uses the ESPRIT method to calculate the DOA parameters.

[0173] Step 208: The server calculates the two sets of DOA parameters using the three-point positioning method to obtain multiple DOA positioning positions of the first device.

[0174] Step 209: The server establishes a CSI fingerprint database based on parameters such as latency, power, and frequency.

[0175] Step 210: When the server obtains multiple sets of second RSSI parameters based on 5G through the first device, it first quickly retrieves historical data that matches the second RSSI parameter from the CIR fingerprint database.

[0176] Step 211: If the matching fails, the RSSI ranging model formula is used to calculate multiple sets of second RSSI parameters to obtain the multiple RSSI transmission distances between the first device and more than three 5G base stations.

[0177] Step 212: The server calculates the transmission distance of each RSSI according to the three-point positioning method, and corrects the error of the calculation result through the CSI fingerprint database to obtain multiple RSSI positioning positions of the first device.

[0178] Here, if there are obstacles between 5G base station A and the target path where the first device is located, the data (latency, power, and frequency) of 5G base station A obtained by the backend server will be inaccurate. In this case, the data of 5G base station A is matched with the data (latency, power, and frequency) in the CSI fingerprint database. If the match is successful, the RSSI transmission distance is obtained directly. If the match fails, the RSSI transmission distance of 5G base station A needs to be calculated using the RSSI data of 5G base station A. Then, the target position is calculated based on the triangulation method. If the target position differs greatly from the actual position, data B (latency, power, and frequency) with a small error compared to the actual position is searched in the CSI fingerprint database. This data B is used to correct the data (latency, power, and frequency) of 5G base station A. The next time the data of 5G base station A is detected, data B is directly used to match the RSSI transmission distance in the CSI fingerprint database to obtain the target position.

[0179] Step 213: The server performs a fusion calculation on the DOA location and RSSI location based on the location weight of each 5G base station to determine the 5G location of the first device.

[0180] Step 214: The server performs location fusion calculation on the Bluetooth location and 5G location based on the location weights of the 5G base station and the Bluetooth base station, and filters the fusion result using Kalman filtering technology to obtain the final location of the first device.

[0181] Here, when fusing 5G and Bluetooth locations, the 5G and Bluetooth locations can be compared with the actual location of the first device. Based on the comparison results, the error between the 5G and Bluetooth locations can be determined. Then, the location with the smallest error is used as a reference (e.g., the Bluetooth location has the smallest error). Then, the 5G error and the reference value (i.e., the Bluetooth location), the Bluetooth error and the Bluetooth location are used as the least squares input to output the weights of the Bluetooth base station and the 5G base station. Finally, the 5G location and the Bluetooth location are fused according to these weights.

[0182] For example, Bluetooth location A and 5G location B are obtained by using a BP neural network to obtain the weights of A and B, and then the fusion calculation is: [(A location * A weight) + (B location * B weight)] ÷ 2 = fused location.

[0183] Figure 3 This is a schematic diagram illustrating the flow implementation of the control method in this application. Figure 2 ,like Figure 3 As shown, it includes:

[0184] Step 301: Collect identification information according to the target path, wherein the identification information is associated with the target path;

[0185] Step 302: Send the identification information to the server;

[0186] Step 303: Receive the movement instruction sent by the server based on the identification information;

[0187] Step 304: Move to the target location according to the target path based on the movement command.

[0188] In this application, the method is applied to a first device, namely a transport vehicle. The first device can also collect multiple sets of first RSSI parameters for Bluetooth base stations and multiple sets of second RSSI parameters for 5G base stations in an indoor environment; and send the multiple sets of first RSSI parameters and the multiple sets of second RSSI parameters to the server, so that the server can determine the current position of the first device based on the multiple sets of first RSSI parameters and the multiple sets of second RSSI parameters.

[0189] For a detailed explanation of the process on the first device side, please refer to [link / reference]. Figure 1 The relevant descriptions of the server side are not repeated here.

[0190] Figure 4 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 1 ,like Figure 4 As shown, the electronic device includes:

[0191] The sending unit 401 is configured to send alarm information to the second device when it is determined based on the first information that the first device meets the abnormal conditions, so that the second device controls the first device to move towards the target path based on the alarm information; and to send a movement command to the first device based on the identification information, so that the first device moves towards the target location according to the target path based on the movement command.

[0192] The receiving unit 402 is used to receive the identification information collected by the first device based on the target path, wherein the identification information is associated with the target path.

[0193] In a preferred embodiment, the receiving unit 402 is specifically used to receive the identification information collected by the first device based on the at least one sub-path, where each identification information corresponds to a sub-path.

[0194] In a preferred embodiment, the electronic device further includes:

[0195] The determining unit 403 determines that the first device meets the abnormal condition if it does not receive the identification information sent by the first device based on the target path within a first time period; or, if it receives the alarm request sent by the first device, it determines that the first device meets the abnormal condition; or, if it determines that the first distance between the current location of the first device and the target path meets the distance parameter based on the positioning information of the first device, it determines that the first device meets the abnormal condition.

[0196] In a preferred embodiment, the electronic device further includes: an acquisition unit 404 and a calculation unit 405;

[0197] The acquisition unit 404 is used to acquire the Bluetooth positioning information and 5G positioning information of the first device;

[0198] The determining unit 403 is further configured to determine a first location of the first device based on the Bluetooth positioning information, and a second location of the first device based on the 5G positioning information; and if the first distance between the current location and the target path is greater than or equal to a distance parameter, determine that the first distance satisfies the distance parameter.

[0199] The calculation unit 405 is used to perform a fusion calculation on the first location and the second location according to the location weights of the Bluetooth base station and the 5G base station to determine the current location of the first device.

[0200] In a preferred embodiment, the electronic device further includes: a comparison unit 406;

[0201] The determining unit 403 is further configured to determine a third position of the first device based on the speed parameters and transportation time parameters of the first device, wherein the third position represents the actual position of the first device;

[0202] The comparison unit 406 is used to compare the first position and the second position with the third position respectively to determine the first position error of the Bluetooth base station and the second position error of the 5G base station.

[0203] The calculation unit 405 is further configured to calculate the first position error and the second position error using the weighted least squares method to determine the first position weight of the Bluetooth base station and the second position weight of the 5G base station; and to perform a fusion calculation on the first position and the second position according to the first position weight and the second position weight to determine the current position of the first device.

[0204] In a preferred embodiment, the electronic device further includes an update unit 407.

[0205] Specifically, the calculation unit 405 is further configured to calculate the first position, the second position, and the third position using the backpropagation algorithm (BP) of the neural network error to determine the third position error of the Bluetooth base station and the fourth position error of the 5G base station; and to perform a fusion calculation on the first position and the second position according to the third position weight and the fourth position weight to determine the current position of the first device.

[0206] The update unit 407 is used to update the first position weight based on the third position error to obtain the third position weight of the Bluetooth base station; and to update the second position weight based on the fourth position error to obtain the fourth position weight of the 5G base station.

[0207] In a preferred embodiment, the determining unit 403 is further configured to determine multiple fourth positions of the first device based on multiple sets of Bluetooth signal arrival angle (AOA) parameters sent by the Bluetooth base station; and to determine multiple fifth positions of the first device based on multiple sets of first received signal strength (RSSI) parameters collected by the first device against the Bluetooth base station in an indoor environment.

[0208] The calculation unit 405 is also used to perform fusion calculations on the plurality of fourth positions and the plurality of fifth positions through a decision tree model to determine the first position of the first device.

[0209] In a preferred embodiment, the determining unit 403 is further configured to determine the sixth position of the first device based on multiple sets of direction of arrival (DOA) parameters sent by the 5G base station; and to determine the seventh position of the first device based on multiple sets of second RSSI parameters collected by the first device for the 5G base station in an indoor environment.

[0210] The calculation unit 405 is also used to perform a fusion calculation on the sixth position and the seventh position through a decision tree model to determine the second position of the first device.

[0211] In a preferred embodiment, the electronic device further includes: a correction unit 408;

[0212] The determining unit 403 is further configured to, if no historical positioning parameters matching the positioning parameters sent by the 5G base station are found in the Channel State Information (CSI) fingerprint database, determine multiple sets of second RSSI transmission distances between the first device and multiple 5G base stations based on the multiple sets of second RSSI parameters; and determine the eighth location of the first device based on the multiple sets of second RSSI transmission distances.

[0213] The correction unit 408 is used to correct the eighth position based on the historical positioning parameters in the CSI fingerprint database if the eighth position and the actual position of the first device meet the error condition, so as to obtain the seventh position of the first device.

[0214] In a preferred embodiment, the calculation unit 405 is further configured to perform a fusion calculation on the first position and the second position according to the position weights of the Bluetooth base station and the 5G base station to obtain the fused position of the Bluetooth base station and the 5G base station;

[0215] The correction unit 408 is also used to filter and correct the fused position of the Bluetooth base station and the 5G base station to obtain the current position of the first device.

[0216] It should be noted that the electronic device provided in the above embodiments, when controlling the first device, is only illustrated by the division of the above-described program modules. In practical applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the processing described above. In addition, the electronic device provided in the above embodiments and the control method embodiments provided above belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0217] Figure 5 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 2 ,like Figure 5 As shown, the electronic device includes:

[0218] The acquisition unit 501 is used to acquire identification information according to the target path, wherein the identification information is associated with the target path;

[0219] Sending unit 502 is used to send the identification information to the server;

[0220] The receiving unit 503 is used to receive the movement instruction sent by the server based on the identification information;

[0221] The moving unit 504 is used to move to the target location according to the target path based on the moving command.

[0222] In the preferred embodiment, the acquisition unit 501 is also used to acquire multiple sets of first RSSI parameters for Bluetooth base stations and multiple sets of second RSSI parameters for 5G base stations in an indoor environment;

[0223] The sending unit 502 is further configured to send the plurality of first RSSI parameters and the plurality of second RSSI parameters to the server, so that the server can determine the current location of the first device based on the plurality of first RSSI parameters and the plurality of second RSSI parameters.

[0224] It should be noted that the electronic device provided in the above embodiments, when controlling the first device, is only illustrated by the division of the above-described program modules. In practical applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the processing described above. In addition, the electronic device provided in the above embodiments and the control method embodiments provided above belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0225] Figure 6 This is a schematic diagram of the structural composition of the control system in this application, as shown below. Figure 6 As shown, the control system includes:

[0226] The first device 601 is configured to collect multiple sets of first RSSI parameters for Bluetooth base stations and multiple sets of second RSSI parameters for 5G base stations in an indoor environment, and send the multiple sets of first RSSI parameters and the multiple sets of second RSSI parameters to a server; it is also configured to collect identification information according to a target path, and send the identification information to the server, wherein the identification information is associated with the target path; it is also configured to send an alarm request to the server; and it is also configured to move to a target location according to the target path based on a movement command sent by the server.

[0227] Bluetooth base station 602 is used to send AOA parameters for the first device to the server;

[0228] 5G base station 603 is used to send DOA parameters for the first device to the server;

[0229] Server 604 is configured to send alarm information to a second device when it is determined that the first device meets abnormal conditions based on the AOA parameters, the DOA parameters, the multiple sets of first RSSI parameters, and the multiple sets of second RSSI parameters; it is also configured to send alarm information to the second device when it is determined that the first device meets abnormal conditions based on the alarm request; it is also configured to send alarm information to the second device when it is determined that the first device meets abnormal conditions based on the reception duration of the current identification information; and it is also configured to send a movement command to the first device based on the identification information sent by the first device.

[0230] The second device 605 is used to control the first device to move toward the target path based on the alarm information.

[0231] It should be noted that the control system provided in the above embodiments and the control method embodiments provided in the above embodiments belong to the same concept. For details of its specific implementation process, please refer to the method embodiments, which will not be repeated here.

[0232] This application also provides an electronic device, which includes: a processor and a memory for storing a computer program capable of running on the processor.

[0233] When the processor runs the computer program, it executes any one of the method steps in the above-described data communication method.

[0234] Figure 7 This is a schematic diagram of the structural composition of the electronic device in this application. Figure 3 Electronic device 700 can be a computer, digital broadcasting terminal, information transceiver, medical equipment, fitness equipment, personal digital assistant, or other terminal. Figure 7 The illustrated electronic device 700 includes at least one processor 701, a memory 702, at least one network interface 704, and a user interface 703. The various components in the electronic device 700 are coupled together via a bus system 705. It is understood that the bus system 705 is used to implement communication between these components. In addition to a data bus, the bus system 705 also includes a power bus, a control bus, and a status signal bus. However, for clarity, ... Figure 7 The general labeled all buses as Bus System 705.

[0235] The user interface 703 may include a monitor, keyboard, mouse, trackball, click wheel, buttons, touchpad, or touch screen.

[0236] It is understood that memory 702 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 702 described in the embodiments of this application is intended to include, but is not limited to, these and any other suitable types of memory.

[0237] In this embodiment, the memory 702 is used to store various types of data to support the operation of the electronic device 700. Examples of this data include: any computer program for operation on the electronic device 700, such as the operating system 7021 and application program 7022; contact data; phonebook data; messages; pictures; audio, etc. The operating system 7021 includes various system programs, such as the framework layer, core library layer, driver layer, etc., for implementing various basic services and handling hardware-based tasks. The application program 7022 may include various applications, such as a media player, browser, etc., for implementing various application services. Programs implementing the methods of this embodiment may be included in the application program 7022.

[0238] The methods disclosed in the embodiments of this application can be applied to processor 701, or implemented by processor 701. Processor 701 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 701 or by instructions in the form of software. The processor 701 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 701 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this application can be directly manifested as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory 702. Processor 701 reads the information in memory 702 and combines its hardware to complete the steps of the aforementioned method.

[0239] In an exemplary embodiment, the electronic device 700 may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the aforementioned method.

[0240] In an exemplary embodiment, this application also provides a computer-readable storage medium, such as a memory 702 including a computer program, which can be executed by a processor 701 of an electronic device 700 to complete the steps described in the foregoing method. The computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, or CD-ROM; it may also be various devices including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

[0241] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs any one of the method steps of the control method described above.

[0242] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0243] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0244] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0245] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0246] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0247] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A control method applied to a server, characterized in that, The method includes: If the first device meets the abnormal conditions based on the first information, an alarm message is sent to the second device so that the second device controls the first device to move toward the target path based on the alarm message. The device receives identification information collected by the first device along the target path, and the identification information is associated with the target path. Based on the identification information, a movement command is sent to the first device, so that the first device moves to the target location according to the target path based on the movement command; The step of determining that the first device meets the abnormal conditions based on the first information includes: Obtain the Bluetooth location information and 5G location information of the first device; The first location of the first device is determined based on the Bluetooth positioning information, and the second location of the first device is determined based on the 5G positioning information; The third position of the first device is determined based on the speed parameters and transportation time parameters of the first device, and the third position represents the actual position of the first device. The first position and the second position are compared with the third position to determine the first position error of the Bluetooth base station and the second position error of the 5G base station. The first position error and the second position error are calculated using the weighted least squares method to determine the first position weight of the Bluetooth base station and the second position weight of the 5G base station. The first position and the second position are fused and calculated according to the first position weight and the second position weight to determine the current position of the first device; If the first distance between the current location and the target path is greater than or equal to the distance parameter, it is determined that the first distance satisfies the distance parameter, and the first device is determined to meet the abnormal condition.

2. The method according to claim 1, characterized in that, The determination that the first device meets the abnormal conditions based on the first information also includes at least one of the following: If no identification information is received from the first device based on the target path within the first time period, it is determined that the first device meets the abnormal conditions; If an alarm request is received from the first device, it is determined that the first device meets the abnormal conditions.

3. The method according to claim 1, characterized in that, After determining the first location weight of the Bluetooth base station and the second location weight of the 5G base station, the method further includes: The first position, the second position, and the third position are calculated using the backpropagation (BP) algorithm for neural network errors to determine the third position error of the Bluetooth base station and the fourth position error of the 5G base station. The first position weight is updated based on the third position error to obtain the third position weight of the Bluetooth base station; and the second position weight is updated based on the fourth position error to obtain the fourth position weight of the 5G base station. The step of fusing the first position and the second position according to the first position weight and the second position weight to determine the current position of the first device includes: The first position and the second position are fused and calculated according to the third position weight and the fourth position weight to determine the current position of the first device.

4. The method according to claim 1, characterized in that, Determining the first location of the first device based on the Bluetooth positioning information includes: Based on multiple sets of Bluetooth signal arrival angle (AOA) parameters sent by the Bluetooth base station, multiple fourth positions of the first device are determined; and based on multiple sets of first received signal strength (RSSI) parameters collected by the first device against the Bluetooth base station in an indoor environment, multiple fifth positions of the first device are determined. The first position of the first device is determined by fusing the plurality of fourth positions and the plurality of fifth positions using a decision tree model.

5. The method according to claim 1, characterized in that, Determining the second location of the first device based on the 5G positioning information includes: Based on multiple sets of Direction of Arrival (DOA) parameters sent by the 5G base station, the sixth position of the first device is determined; and based on multiple sets of second RSSI parameters collected by the first device in an indoor environment for the 5G base station, the seventh position of the first device is determined. The second position of the first device is determined by fusing the sixth and seventh positions using a decision tree model.

6. The method according to claim 5, characterized in that, The method of determining the seventh location of the first device based on multiple sets of second RSSI parameters collected by the first device against the 5G base station in an indoor environment includes: If no historical positioning parameters matching the positioning parameters sent by the 5G base station are found in the Channel State Information (CSI) fingerprint database, the transmission distance of multiple sets of second RSSI between the first device and multiple 5G base stations is determined based on the multiple sets of second RSSI parameters. The eighth position of the first device is determined based on the multiple sets of second RSSI transmission distances; If the eighth position meets the error condition with the actual position of the first device, the eighth position is corrected based on the historical positioning parameters in the CSI fingerprint database to obtain the seventh position of the first device.

7. The method according to claim 1, characterized in that, The step of fusing the first position and the second position according to the first position weight and the second position weight to determine the current position of the first device includes: The first position and the second position are fused according to the first position weight and the second position weight to obtain the fused position of the Bluetooth base station and the 5G base station; The merged positions of the Bluetooth base station and the 5G base station are filtered and corrected to obtain the current position of the first device.

8. The method according to claim 1, characterized in that, The target path includes at least one sub-path; The step of receiving the identification information collected by the first device based on the target path, wherein the identification information is associated with the target path, includes: The device receives identification information collected by the first device based on the at least one sub-path, where each identification information corresponds to a sub-path.

9. A control method applied to a first device, characterized in that, The method includes: Identification information is collected according to the target path, and the identification information is associated with the target path; Send the identification information to the server; Receive the movement instruction sent by the server based on the identification information; Based on the movement command, move to the target location according to the target path; If the server determines that the first device meets the abnormal conditions based on the first information, the server sends an alarm message to the second device so that the second device controls the first device to move towards the target path based on the alarm message. Wherein, the server determines that the first device meets the abnormal conditions based on the first information, including: Obtain the Bluetooth location information and 5G location information of the first device; The first location of the first device is determined based on the Bluetooth positioning information, and the second location of the first device is determined based on the 5G positioning information; The third position of the first device is determined based on the speed parameters and transportation time parameters of the first device, and the third position represents the actual position of the first device. The first position and the second position are compared with the third position to determine the first position error of the Bluetooth base station and the second position error of the 5G base station. The first position error and the second position error are calculated using the weighted least squares method to determine the first position weight of the Bluetooth base station and the second position weight of the 5G base station. The first position and the second position are fused and calculated according to the first position weight and the second position weight to determine the current position of the first device; If the first distance between the current location and the target path is greater than or equal to the distance parameter, it is determined that the first distance satisfies the distance parameter, and the first device is determined to meet the abnormal condition.

10. The method according to claim 9, characterized in that, The method further includes: Multiple sets of first RSSI parameters for Bluetooth base stations and multiple sets of second RSSI parameters for 5G base stations were collected in an indoor environment. The server sends the multiple sets of first RSSI parameters and the multiple sets of second RSSI parameters to the server so that the server can determine the current location of the first device based on the multiple sets of first RSSI parameters and the multiple sets of second RSSI parameters.

11. An electronic device, characterized in that, The electronic device includes: The sending unit is configured to send alarm information to the second device when the first device meets the abnormal conditions based on the first information, so that the second device controls the first device to move towards the target path based on the alarm information; and to send a movement command to the first device based on the identification information, so that the first device moves towards the target location according to the target path based on the movement command. A receiving unit is configured to receive the identification information collected by the first device based on the target path, wherein the identification information is associated with the target path; The acquisition unit is used to acquire the Bluetooth positioning information and 5G positioning information of the first device; The determining unit determines that the first device meets an abnormal condition if, based on the positioning information of the first device, the first distance between the current location of the first device and the target path satisfies a distance parameter; wherein, determining that the first device meets an abnormal condition based on the first information includes: determining a first location of the first device based on the Bluetooth positioning information, and determining a second location of the first device based on the 5G positioning information; determining a third location of the first device based on the speed parameter and transportation time parameter of the first device, wherein the third location represents the actual location of the first device; The comparison unit is used to compare the first position and the second position with the third position respectively to determine the first position error of the Bluetooth base station and the second position error of the 5G base station; The calculation unit is configured to calculate the first position error and the second position error using a weighted least squares method to determine the first position weight of the Bluetooth base station and the second position weight of the 5G base station; and to perform a fusion calculation on the first position and the second position according to the first position weight and the second position weight to determine the current position of the first device. If the determining unit determines that the first distance between the current location and the target path is greater than or equal to the distance parameter, it is further configured to determine that the first distance satisfies the distance parameter and to determine that the first device meets the abnormal condition.

12. An electronic device, characterized in that, The electronic device includes: A data acquisition unit is used to acquire identification information according to a target path, wherein the identification information is associated with the target path; The sending unit is used to send the identification information to the server; A receiving unit is configured to receive a movement instruction sent by the server based on the identification information; A movement unit, configured to move to a target location according to the target path based on the movement command; The server is configured to send an alarm message to a second device when it determines that the electronic device meets an abnormal condition based on first information, so that the second device controls the electronic device to move towards the target path based on the alarm message. Determining that the electronic device meets the abnormal condition based on the first information includes: acquiring Bluetooth and 5G positioning information of the electronic device; determining a first position of the electronic device based on the Bluetooth positioning information and a second position of the electronic device based on the 5G positioning information; determining a third position of the electronic device based on its speed and transport time parameters, the third position representing the actual position of the electronic device; comparing the first and second positions with the third position to determine a first position error of the Bluetooth base station and a second position error of the 5G base station; calculating the first and second position errors using a weighted least squares method to determine the first position weight of the Bluetooth base station and the second position weight of the 5G base station; performing a fusion calculation on the first and second positions according to the first and second position weights to determine the current position of the electronic device; if a first distance between the current position and the target path is greater than or equal to a distance parameter, it is determined that the first distance satisfies the distance parameter, and the electronic device meets the abnormal condition.

13. A control system, characterized in that, The system includes: The first device is configured to collect multiple sets of first RSSI parameters for Bluetooth base stations and multiple sets of second RSSI parameters for 5G base stations in an indoor environment, and send the multiple sets of first RSSI parameters and the multiple sets of second RSSI parameters to a server; it is also configured to collect identification information according to a target path, and send the identification information to the server, wherein the identification information is associated with the target path; it is also configured to send an alarm request to the server; and it is also configured to move to a target location according to the target path based on a movement command sent by the server. A Bluetooth base station is used to send AOA parameters for the first device to the server; The 5G base station is used to send DOA parameters for the first device to the server; The server is configured to send alarm information to a second device when it is determined that the first device meets abnormal conditions based on the AOA parameters, the DOA parameters, the multiple sets of first RSSI parameters, and the multiple sets of second RSSI parameters; and to send a movement command to the first device based on the identification information sent by the first device; wherein, determining that the first device meets abnormal conditions based on the AOA parameters, the DOA parameters, the multiple sets of first RSSI parameters, and the multiple sets of second RSSI parameters includes: determining a first position of the first device based on the AOA parameters and the multiple sets of first RSSI parameters, and determining a second position of the first device based on the DOA parameters and the multiple sets of second RSSI parameters; and based on the speed parameters and transportation time parameters of the first device. A third position of the first device is determined, the third position representing the actual position of the first device; the first position and the second position are compared with the third position to determine the first position error of the Bluetooth base station and the second position error of the 5G base station; the first position error and the second position error are calculated using weighted least squares to determine the first position weight of the Bluetooth base station and the second position weight of the 5G base station; the first position and the second position are fused according to the first position weight and the second position weight to determine the current position of the first device; if the first distance between the current position and the target path is greater than or equal to a distance parameter, the first distance is determined to satisfy the distance parameter, and the first device is determined to meet the abnormal condition; The second device is used to control the first device to move toward the target path based on the alarm information.

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