College data acquisition method and system based on campus scene

Abstract

The invention relates to the technical field of data acquisition and processing, and discloses a college data acquisition method and system based on a campus scene, and the method comprises the steps: collecting the activity position data of a student in a campus in real time through a customized APP in a mobile terminal, and transmitting the activity position data to a data server in real time through a network when the mobile terminal is normally online; bluetooth beacons which can be interconnected with mobile terminals are deployed in all places of a campus, and after students carry the mobile terminals to enter the corresponding places of the campus, the mobile terminals can establish communication with the Bluetooth beacons in the corresponding places and transmit arrival signals to a data server. According to the invention, the Bluetooth beacons are deployed in each place of the campus, so that each area has fixed geographic coordinate information, and after carrying the mobile terminal, a student can automatically trigger Bluetooth scanning and identify beacon arrival signals when entering a specific area, and upload data such as beacon numbers, time and signal intensity to the server.

Description

Technical Field

[0001] The present invention relates to the technical field of data acquisition and processing, and in particular to a method and system for collecting university data based on campus scenarios. Background Art

[0002] The development of campus IoT environments is becoming an increasingly important component of smart campuses. By deploying various sensors and intelligent devices in smart classrooms, smart dormitories, libraries, laboratories, and other locations, real-time monitoring, data collection, and automatic control of the physical environment and human behavior can be achieved, thereby improving management efficiency and user experience. The interconnection of data across various scenarios not only enables automatic environmental adjustments and safety warnings, but also integrates multi-source data to provide a scientific basis for school management decisions and improvements in teaching and research.

[0003] At present, the collection of student behavior data on campus mainly relies on customized APPs or software plug-ins to obtain terminal users' activity data and location data. However, when the data collection of the mobile terminal is interrupted due to unstable signals, device power failure, etc., the data collection will not be able to proceed normally. Therefore, how to ensure the continuity and integrity of student behavior data as much as possible when the mobile terminal data collection is interrupted is an urgent problem to be solved in this field. Summary of the Invention

[0004] In response to the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a data collection method and system for colleges and universities based on campus scenarios, so that when the data collection of the mobile terminals carried by students is interrupted, it can predict student behavior and fill in the data to ensure the continuity of behavioral data.

[0005] In order to achieve the above-mentioned purpose, the present invention provides the following technical solution: a method for collecting university data based on a campus scene, the method comprising the following steps: Use a customized APP in the mobile terminal to collect students' activity location data on campus in real time. When the mobile terminal is online, the activity location data is transmitted to the data server in real time through the network; Deploy Bluetooth beacons that can connect to mobile terminals in various locations on campus. When students enter the corresponding campus location with their mobile terminals, the mobile terminals can establish a connection with the Bluetooth beacons in the corresponding locations and transmit arrival signals to the data server. When the mobile terminal is abnormally offline, all the arrival signals currently acquired in the data server are retrieved, and it is determined whether there is an arrival signal generated by the abnormally offline mobile terminal; When there is an arrival signal generated by an abnormally offline mobile terminal in the data server, the place where the arrival signal is transmitted is marked as the active location place, and the active location data is generated based on the coordinate position of the active location place and transmitted to the data server; when there is no arrival signal generated by an abnormally offline mobile terminal in the data server, the coordinate estimation strategy is executed to generate estimated active location data and transmit it to the data server.

[0006] In some embodiments, after the customized APP in the mobile terminal is started, it will automatically call the built-in positioning module and sensor interface to obtain the real-time activity trajectory, stay duration and path information of students on campus. After collecting raw data such as location and activity time, the APP will first perform local data preprocessing, including data formatting, timestamp synchronization and brief abnormal data filtering. When the mobile terminal is in a network connection state, the APP will encrypt the collected data and upload it to the data server in real time through the HTTPS / SSL secure communication protocol.

[0007] In some embodiments, each Bluetooth beacon will be fixedly arranged in a corresponding campus location, and the geographic coordinates and location number information of the location will be pre-recorded. When the mobile terminal carried by the student enters the area where the Bluetooth beacon is arranged, the customized APP automatically performs Bluetooth scanning and detects the surrounding beacon broadcast information, and establishes a connection with the preset area information based on the beacon identifier.

[0008] In some embodiments, the coordinate estimation strategy includes setting an acceptable offline time. When the mobile terminal is abnormally offline, the specific coordinates of the mobile terminal on campus at the time of offline are recorded, the coordinates are marked as the disconnected position, and timing is performed. When the total timing time does not exceed the acceptable offline time and the mobile terminal is online again normally, the coordinates of the mobile terminal when it is online again normally are obtained, the coordinates are marked as the connected position, the shortest path between the connected position and the disconnected position is obtained, and the path is generated as the moving path of the estimated active position of the mobile terminal during the offline time, and it is transmitted to the data server.

[0009] In some embodiments, after obtaining the geographic coordinate information between the disconnected location and the connected location, the shortest path between the two is calculated based on the geographic data and traffic route data within the campus. According to the calculation results of the shortest path algorithm, the path is discretized into several key location points, and an estimated arrival time is attached to each location point. A complete predicted trajectory is formed according to the time series, and this estimated movement trajectory is encapsulated as estimated activity location data.

[0010] In some embodiments, when a mobile terminal is abnormally offline, if the terminal captures a Bluetooth beacon arrival signal, the corresponding location coordinates of the captured signal are used to directly generate activity location data. Specifically, a predicted trajectory is generated based on the shortest path between the captured location coordinates and the disconnection location, and corresponding estimated activity location data is generated.

[0011] In some embodiments, when executing the coordinate estimation strategy, if the mobile terminal is abnormally offline and timing is performed, and the total timing duration exceeds the acceptable offline time, the synchronization terminal existing near the corresponding mobile terminal within the preset period is obtained, and the activity location data of the synchronization terminal is synchronized to the activity location data of the corresponding offline mobile terminal in the data server based on the activity location data of the synchronization terminal, that is, the activity location data of the offline mobile terminal is used with the activity location data of the synchronization terminal.

[0012] In some embodiments, a specific method of setting a preset period includes: when a mobile terminal is abnormally offline, marking the specific coordinates and specific time of the mobile terminal on campus when it is offline, marking the marked specific time as the offline time point, the preset period is a time period of 30-60 minutes before the offline time point, and within the time period, searching the data server to see whether there are other mobile terminals whose activity location data matches the activity location data of the offline mobile terminal; when there are other mobile terminals whose activity location data matches the activity location data of the offline mobile terminal, marking the mobile terminal as a peer terminal, and determining whether it is a synchronous terminal; Obtain the student information of the peer terminal and the corresponding student information of the abnormally offline mobile terminal, match the student information of the peer terminal with that of the offline terminal, and if the peer terminal is matched and the student holding the offline terminal is in the same class, mark the peer terminal as a synchronous terminal.

[0013] The present invention also provides the following technical solution: a university data collection system based on campus scenes, comprising: The data collection module uses a customized APP in the mobile terminal to collect students' activity location data on campus in real time. When the mobile terminal is online, the activity location data is transmitted to the data server in real time via the network; The location beacon module includes Bluetooth beacons deployed in various locations on campus that can be interconnected with mobile terminals. When students carry their mobile terminals into the corresponding campus locations, the mobile terminals can establish a connection with the Bluetooth beacons in the corresponding locations and transmit arrival signals to the data server; An offline response module, which includes, when the mobile terminal is abnormally offline, retrieving all the arrival signals currently acquired in the data server and determining whether there is an arrival signal generated by the abnormally offline mobile terminal; A data processing module includes, when there is an arrival signal generated by an abnormally offline mobile terminal in the data server, marking the place where the arrival signal is transmitted as an activity location place, and generating activity location data based on the coordinate position of the activity location place and transmitting it to the data server; and when there is no arrival signal generated by the abnormally offline mobile terminal in the data server, executing a coordinate estimation strategy to generate estimated activity location data and transmitting it to the data server.

[0014] The present invention further provides a computer-readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the above-mentioned university data collection method based on campus scenarios.

[0015] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects: Firstly, the present invention deploys Bluetooth beacons in various places on campus, so that each area has fixed geographic coordinate information. After students carry mobile terminals, they can automatically trigger Bluetooth scanning and identify beacon arrival signals when entering a specific area, and upload data such as beacon number, time and signal strength to the server. Firstly, the data can be supplemented and corrected when the mobile terminal transmission is normal, thereby further improving the overall positioning accuracy; secondly, when the mobile terminal is abnormally offline, even if the network is interrupted, the device can still capture the arrival signal through Bluetooth, ensuring that the activity location data in key places is recorded, thereby avoiding large data loss.

[0016] Secondly, when the mobile terminal is abnormally offline, the system of the present invention first determines whether there is any activity location data directly generated based on the Bluetooth beacon location through the stored arrival signal; if the arrival signal cannot be obtained, the preset coordinate estimation strategy is adopted to calculate the estimated trajectory during the offline period based on the shortest path between the disconnected position and the connected position.

[0017] Third, through the shortest path algorithm and estimation strategy, the present invention can use historical positioning and environmental data to reconstruct trajectories, restore student activity trajectories, and improve data continuity and integrity even when data collection is interrupted; and the introduction of synchronous terminal data utilizes the characteristics of group behavior on campus, further improving data completion through data comparison between peer students, ensuring that offline terminals can still obtain reference to nearby real activity data. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of the method flow of the present invention; Figure 2 Schematic diagram of the system module of the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] It is to be understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element may be one, while in another embodiment, the number of the elements may be multiple, and the term "one" should not be understood as a limitation on the quantity.

[0021] The present invention provides a method for collecting university data based on campus scenes, such as Figure 1 As shown, the method includes the following steps: Step 1: Use a customized APP in the mobile terminal to collect students' activity location data on campus in real time. When the mobile terminal is online normally, the activity location data is transmitted to the data server in real time through the network. It should be noted that after the customized APP in the mobile terminal is started, it will automatically call the built-in positioning module (such as GPS, WLAN positioning, base station positioning, etc.) and sensor interface to obtain students' real-time activity trajectory, stay duration and path information on campus. After collecting raw data such as location and activity time, the APP will first perform local data preprocessing, including data formatting, timestamp synchronization and brief abnormal data filtering (such as positioning mutations, wrong coordinate elimination, etc.). When the mobile terminal is in a network connection state, the APP will encrypt the collected data and upload it to the data server in real time through the HTTPS / SSL secure communication protocol to ensure the security and integrity of the data transmission process.

[0022] Step 2: Deploy Bluetooth beacons that can connect to mobile terminals in various locations on campus (smart classrooms, smart dormitories, libraries, laboratories, etc.). When students bring their mobile terminals to the corresponding campus locations, the mobile terminals can establish a connection with the Bluetooth beacons in the corresponding locations and transmit the arrival signal to the data server. Specifically, each Bluetooth beacon will be fixed in the corresponding campus location and pre-entered with the location's geographic coordinates and location number. When a student's mobile terminal enters the area where the Bluetooth beacon is deployed, the customized app automatically performs Bluetooth scanning and detects the surrounding beacon broadcast information. It then establishes a connection with the preset area information based on the beacon's identifier. After successfully scanning a beacon, the mobile terminal generates an arrival signal, which includes: - Beacon number, acquisition time and signal strength (RSSI) for subsequent correction of positioning accuracy; -The unique identifier of the current mobile terminal (such as student ID or encrypted ID), which is used by the back-end to associate and determine the data source; -Other auxiliary information, such as device status identification, location information verification data, etc.

[0023] The beacon arrival signal is also locally encrypted and uploaded to the data server in real time via the network as another data source for mobile terminal behavior data.

[0024] Step 3: When the mobile terminal is abnormally offline, all the arrival signals currently acquired in the data server are retrieved, and it is determined whether there is an arrival signal generated by the abnormally offline mobile terminal; Step 4: When there is an arrival signal generated by an abnormally offline mobile terminal in the data server, the place where the arrival signal is transmitted is marked as the activity location place, and the activity location data is generated based on the coordinate position of the activity location place and transmitted to the data server; and when there is no arrival signal generated by an abnormally offline mobile terminal in the data server, the coordinate estimation strategy is executed to generate estimated activity location data and transmit it to the data server.

[0025] The coordinate estimation strategy includes setting an acceptable offline time. When the mobile terminal is abnormally offline, the specific coordinates of the mobile terminal on campus at the time of offline are recorded, the coordinates are marked as the disconnection position, and timing is performed. When the total timing time does not exceed the acceptable offline time and the mobile terminal is online again normally, the coordinates of the mobile terminal when it is online again are obtained, the coordinates are marked as the connection position, the shortest path between the connection position and the disconnection position is obtained, and the path is generated as the moving path of the estimated active position of the mobile terminal during the offline time, and it is transmitted to the data server.

[0026] Specifically, after obtaining the geographic coordinates between the disconnected and connected locations, the shortest path between them is calculated based on the campus geographic data and route data. Based on the results of the shortest path algorithm, the path is discretized into several key locations, and an estimated arrival time is attached to each location. A complete predicted trajectory is formed according to the time series. This estimated movement trajectory is encapsulated as estimated activity location data. The data package should include: - Geographic coordinates of the initial disconnection location, connection location, and intermediate key points; -Time series information (including disconnection and connection times, and estimated arrival times of key nodes on the path); -The total duration of the offline period and the estimated algorithm identification are used to facilitate subsequent data matching and quality assessment.

[0027] On the other hand, when the mobile terminal is abnormally offline, if the terminal captures the arrival signal of the Bluetooth beacon, the corresponding location coordinates of the captured signal are used to directly generate activity location data. Specifically, the predicted trajectory is generated based on the shortest path between the captured location coordinates and the disconnection location, and the corresponding estimated activity location data is generated.

[0028] When executing the coordinate estimation strategy, if the mobile terminal is abnormally offline and timing is performed, and the total timing duration exceeds the acceptable offline time, the synchronization terminals existing near the corresponding mobile terminal within the preset period are obtained, and the activity location data of the synchronization terminals is synchronized to the activity location data of the corresponding mobile terminal that has moved offline in the data server based on the activity location data of the synchronization terminals, that is, the activity location data of the offline mobile terminal is replaced by the activity location data of the synchronization terminals. By sorting and comparing the behavior data of peer terminals within the preset period, the system can capture other terminals that match the activity location data of the offline terminal, and thus use these synchronization data to ensure that the information during the missing period is supplemented. Secondly, the synchronization terminals are introduced, that is, terminals that hold similar behavior data at the same time and similar locations, and their data is used to synchronize and complete the activity trajectory of the offline terminal. This method fully relies on real mobile data and can match data across terminals, enhancing the integrity and accuracy of data collection.

[0029] The specific method of setting the preset period includes: when a mobile terminal is abnormally offline, marking the specific coordinates and specific time of the mobile terminal's location on campus at the time of offline, and marking the marked specific time as the offline time point. The preset period is a time period of 30-60 minutes before the offline time point. During this time period, the data server is searched to see whether there are other mobile terminals whose activity location data matches the offline mobile terminal. When there are other mobile terminals whose activity location data matches the offline mobile terminal's, the mobile terminal is marked as a peer terminal, and it is determined whether it is a synchronized terminal. Specifically, the student information of the peer terminal is obtained, and the corresponding student information of the abnormally offline mobile terminal is obtained. The peer terminal and the student information of the offline terminal are matched. If a peer terminal is found to be in the same class as the student holding the offline terminal, the peer terminal is marked as a synchronized terminal. In this way, it is easy to filter out terminals that are active in the same time period, similar path, or area from a large amount of data. Secondly, the data of the peer terminal can not only prove the actual activities of students within the preset time, but also further filter out terminals in the same class by matching student identity information. This helps improve the accuracy of data comparison and ensures that the selected peer terminal data is more representative and authentic. Next, the system analyzes the activity records of these peer terminals to determine whether they meet the conditions for synchronization terminals, and then uses them as the basis for data completion of offline terminals.

[0030] Once an abnormally offline mobile terminal is matched with a synchronization terminal, the student's offline status may be caused by a power outage, signal anomaly, or other factors. However, due to the presence of accompanying students, the student's activity location data can be synchronized. This overwrites existing synchronization terminal data, minimizing information loss due to device failure or signal interruption. Overall, this solution fully leverages historical data, time windows, and student affiliation information. Through multi-dimensional data matching and intelligent judgment, it ensures the continuity and integrity of activity location data in the event of abnormal offline conditions.

[0031] It should be noted that after executing the coordinate estimation strategy, if the mobile terminal is abnormally offline and timing is performed, and the total timing time exceeds the acceptable offline time, and the synchronization terminal nearby the corresponding mobile terminal cannot be obtained within the preset period, it indicates that there are no students nearby when the student's mobile terminal is offline. In this case, the mobile terminal will be marked as an abnormal terminal, triggering a safety warning mechanism. The safety warning mechanism includes sending alarm information to the campus security management center, dormitory manager or counselor to remind relevant personnel to pay attention to the situation of this student. If necessary, the system can also be configured to send SMS, email or push messages within the APP to notify the student or his parents to verify whether there is an emergency or equipment failure. Real-time warnings not only help to detect abnormal situations in a timely manner, but also allow manual intervention when necessary to confirm whether the student is in a safe and isolated state or whether there is an abnormality in the device.

[0032] In general, the present invention aims to design a data collection method for colleges and universities based on campus scenarios. In order to solve the problem that data collection cannot be carried out normally when the mobile terminal is interrupted due to unstable signals, lack of power, etc., the present invention deploys Bluetooth beacons in various places on campus, so that each area has fixed geographic coordinate information. After students carry mobile terminals, they can automatically trigger Bluetooth scanning and identify beacon arrival signals when entering a specific area, and upload data such as beacon number, time and signal strength to the server. First, the data can be supplemented and corrected when the mobile terminal transmission is normal, further improving the overall positioning accuracy; second, when the mobile terminal is abnormally offline, even if the network is interrupted, the device can still capture the arrival signal through Bluetooth to ensure that the activity location data in key places is recorded, thereby avoiding large data omissions. When the mobile terminal is abnormally offline, the system first determines whether there is activity location data directly generated based on the Bluetooth beacon location through the stored arrival signal; if the arrival signal cannot be obtained, the preset coordinate estimation strategy is adopted to calculate the estimated trajectory during the offline period based on the shortest path between the disconnected location and the connected location. Furthermore, when the offline time exceeds a preset threshold and no nearby synchronized terminals can be found within a preset period, indicating no nearby student data, the system marks the terminal as abnormal and triggers a safety alert. The benefits and functions of this design are primarily reflected in the following: Using a shortest path algorithm and prediction strategy, historical positioning and environmental data can be used to reconstruct student activity trajectories even during data collection interruptions, improving data continuity and integrity. The inclusion of synchronized terminal data leverages the characteristics of group behavior on campus and further improves data completion by comparing data between peers, ensuring that offline terminals still have a reference to nearby activity data. If these strategies fail, the system automatically marks the terminal as abnormal, triggering an alert and promptly notifying campus security management, counselors, or parents, ensuring rapid intervention in the event of student accidents or device failures. Overall, this design not only provides strong data self-healing and fault tolerance, but also significantly enhances security monitoring through a multi-layered response mechanism, effectively filling the information gaps that can occur when mobile terminals are offline unexpectedly, while also establishing a comprehensive backup mechanism for security alerts and emergency intervention.

[0033] The present invention provides a university data collection system based on campus scenes, such as Figure 2 Shown, including: The data collection module uses a customized APP in the mobile terminal to collect students' activity location data on campus in real time. When the mobile terminal is online, the activity location data is transmitted to the data server in real time via the network; The location beacon module includes Bluetooth beacons deployed in various locations on campus that can be interconnected with mobile terminals. When students carry their mobile terminals into the corresponding campus locations, the mobile terminals can establish a connection with the Bluetooth beacons in the corresponding locations and transmit arrival signals to the data server; An offline response module, which includes, when the mobile terminal is abnormally offline, retrieving all the arrival signals currently acquired in the data server and determining whether there is an arrival signal generated by the abnormally offline mobile terminal; A data processing module includes, when there is an arrival signal generated by an abnormally offline mobile terminal in the data server, marking the place where the arrival signal is transmitted as an activity location place, and generating activity location data based on the coordinate position of the activity location place and transmitting it to the data server; and when there is no arrival signal generated by the abnormally offline mobile terminal in the data server, executing a coordinate estimation strategy to generate estimated activity location data and transmitting it to the data server.

[0034] In the embodiments disclosed herein, the processes described above with reference to the flowcharts can be implemented as computer software programs. The embodiments disclosed herein include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for executing the method illustrated in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component and / or installed from removable media. When the computer program is executed by a central processing unit, the functions defined in the methods of this application are performed. It should be noted that the computer-readable medium referred to herein can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination thereof. More specific examples of computer-readable storage media can include, but are not limited to, an electrical connection having one or more wire segments, a portable computer disk, a hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. Furthermore, in this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, electrical, optical, RF, or any suitable combination thereof.

[0035] The flow charts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0036] Those skilled in the art should understand that the above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered by the scope of protection of the present application.

Claims

1. A data collection method for colleges and universities based on campus scenes, characterized in that: The method comprises the following steps: Use a customized APP in the mobile terminal to collect students' activity location data on campus in real time. When the mobile terminal is online, the activity location data is transmitted to the data server in real time through the network; Deploy Bluetooth beacons that can connect to mobile terminals in various locations on campus. When students enter the corresponding campus location with their mobile terminals, the mobile terminals can establish a connection with the Bluetooth beacons in the corresponding locations and transmit arrival signals to the data server. When the mobile terminal is abnormally offline, all the arrival signals currently acquired in the data server are retrieved, and it is determined whether there is an arrival signal generated by the abnormally offline mobile terminal; When there is an arrival signal generated by an abnormally offline mobile terminal in the data server, the place where the arrival signal is transmitted is marked as the active location place, and the active location data is generated based on the coordinate position of the active location place and transmitted to the data server; when there is no arrival signal generated by an abnormally offline mobile terminal in the data server, the coordinate estimation strategy is executed to generate estimated active location data and transmit it to the data server.

2. The campus scene-based university data collection method according to claim 1 is characterized in that: After the customized APP in the mobile terminal is started, it will automatically call the built-in positioning module and sensor interface to obtain the students' real-time activity trajectory, stay duration and path information on campus. After collecting raw data such as location and activity time, the APP will first perform local data preprocessing, including data formatting, timestamp synchronization and brief abnormal data filtering. When the mobile terminal is in a network connection state, the APP will encrypt the collected data and upload it to the data server in real time through the HTTPS / SSL secure communication protocol.

3. The campus scene-based university data collection method according to claim 2 is characterized in that: Each Bluetooth beacon will be fixedly placed in the corresponding campus location, and the geographic coordinates and location number information of the location will be pre-recorded. When the mobile terminal carried by the student enters the area where the Bluetooth beacon is placed, the customized APP automatically performs Bluetooth scanning and detects the surrounding beacon broadcast information, and establishes a connection with the preset area information based on the beacon identifier.

4. The campus scene-based university data collection method according to claim 3 is characterized in that: The coordinate estimation strategy includes setting an acceptable offline time. When the mobile terminal is abnormally offline, the specific coordinates of the mobile terminal on campus at the time of offline are recorded, the coordinates are marked as the disconnection position, and timing is performed. When the total timing time does not exceed the acceptable offline time and the mobile terminal is online again normally, the coordinates of the mobile terminal when it is online again are obtained, the coordinates are marked as the connection position, the shortest path between the connection position and the disconnection position is obtained, and the path is generated as the moving path of the estimated active position of the mobile terminal during the offline time, and it is transmitted to the data server.

5. The campus scene-based university data collection method according to claim 4 is characterized in that: After obtaining the geographic coordinate information between the disconnected location and the connected location, the shortest path between the two is calculated based on the campus geographic data and the route data. According to the calculation results of the shortest path algorithm, the path is discretized into several key location points, and an estimated arrival time is attached to each location point. A complete predicted trajectory is formed according to the time series, and this estimated movement trajectory is encapsulated as estimated activity location data.

6. The campus scene-based university data collection method according to claim 5 is characterized in that: When a mobile terminal is abnormally offline, if the terminal captures the arrival signal of a Bluetooth beacon, the corresponding location coordinates of the captured signal are used to directly generate activity location data. Specifically, the predicted trajectory is generated based on the shortest path between the captured location coordinates and the disconnection location, and the corresponding estimated activity location data is generated.

7. The campus scene-based university data collection method according to claim 6 is characterized in that: When executing the coordinate estimation strategy, if the mobile terminal is abnormally offline and timing is performed, and the total timing duration exceeds the acceptable offline time, the synchronization terminal existing near the corresponding mobile terminal within the preset period is obtained, and the activity location data of the synchronization terminal is synchronized to the activity location data of the corresponding offline mobile terminal in the data server based on the activity location data of the synchronization terminal, that is, the activity location data of the offline mobile terminal uses the activity location data of the synchronization terminal.

8. The campus scene-based university data collection method according to claim 7 is characterized in that: The specific method of setting the preset period includes: when the mobile terminal is abnormally offline, marking the specific coordinates and specific time of the mobile terminal's location on campus when it is offline, marking the marked specific time as the offline time point, the preset period is a time period of 30-60 minutes before the offline time point, and within the time period, searching the data server to see whether there are other mobile terminals whose activity location data matches the offline mobile terminal's. When there are other mobile terminals whose activity location data matches the offline mobile terminal's, marking the mobile terminal as a peer terminal and determining whether it is a synchronized terminal; Obtain the student information of the peer terminal and the corresponding student information of the abnormally offline mobile terminal, match the student information of the peer terminal with that of the offline terminal, and if the peer terminal is matched and the student holding the offline terminal is in the same class, mark the peer terminal as a synchronous terminal.

9. A university data collection system based on campus scenes, characterized in that: A method for collecting university data based on a campus scenario according to any one of claims 1 to 8, comprising: The data collection module uses a customized APP in the mobile terminal to collect students' activity location data on campus in real time. When the mobile terminal is online, the activity location data is transmitted to the data server in real time via the network; The location beacon module includes Bluetooth beacons deployed in various locations on campus that can be interconnected with mobile terminals. When students carry their mobile terminals into the corresponding campus locations, the mobile terminals can establish a connection with the Bluetooth beacons in the corresponding locations and transmit arrival signals to the data server; An offline response module, which includes, when the mobile terminal is abnormally offline, retrieving all the arrival signals currently acquired in the data server and determining whether there is an arrival signal generated by the abnormally offline mobile terminal; A data processing module includes, when there is an arrival signal generated by an abnormally offline mobile terminal in the data server, marking the place where the arrival signal is transmitted as an activity location place, and generating activity location data based on the coordinate position of the activity location place and transmitting it to the data server; and when there is no arrival signal generated by the abnormally offline mobile terminal in the data server, executing a coordinate estimation strategy to generate estimated activity location data and transmitting it to the data server.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the university data collection method based on a campus scenario as described in any one of claims 1 to 8.

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