Intelligent monitoring and tamper-proofing method and system for logistics transportation cargo state

Abstract

The invention discloses an intelligent monitoring and tamper-proof method and system for the state of logistics transportation goods, and the method comprises the steps: transmitting a monitoring instruction to a vehicle-mounted monitoring terminal, so as to enable the vehicle-mounted monitoring terminal to monitor a target monitoring object; beidou positioning data and cargo environment parameters reported by the vehicle-mounted monitoring terminal and physical connection state data of an intelligent electronic lock in the vehicle-mounted monitoring terminal are received; generating a real-time moving track of the target monitoring object based on the Beidou positioning data; performing risk analysis to obtain a risk analysis result; generating alarm information based on the risk analysis result, and sending the alarm information to the mobile terminal APP; performing authority management on the intelligent electronic lock and generating authority management data; and generating the electronic evidence chain of the target monitoring object. According to the invention, the reliability of logistics transportation monitoring can be improved.

Description

Technical Field

[0001] This application relates to the field of intelligent monitoring technology, specifically to an intelligent monitoring and anti-tampering method and system for the status of goods in logistics transportation. Background Technology

[0002] With the rapid development of the manufacturing industry, the demand for logistics and transportation of bulk commodities continues to grow. Especially in the contract logistics transportation of high-value goods such as coal, ore, and steel, transportation safety and cargo supervision have become key concerns for the industry. To ensure the safety and reliability of the transportation process, it is necessary to monitor and manage the status of goods throughout the entire process.

[0003] Existing technologies typically employ a combination of GPS positioning terminals and electronic locks for transportation monitoring. GPS positioning terminals are installed on transport vehicles to track their location, while electronic locks are used to lock cargo containers and prevent unauthorized removal of goods. During transportation, the system collects location data through the positioning terminals and uploads it to a monitoring platform, while simultaneously monitoring the on / off status of the electronic locks. An alarm is triggered if any abnormality is detected.

[0004] However, in practical applications, it has been found that the lack of collaborative analysis of multi-dimensional data during transportation makes it difficult for the system to accurately identify and respond promptly to abnormal events in complex scenarios. For example, when a vehicle temporarily stops due to normal traffic control, it is difficult to determine whether there is a risk of cargo swapping based solely on location data; also, in complex road conditions, positioning signals are easily interfered with and drift, affecting the accuracy of trajectory monitoring and reducing the reliability of logistics transportation monitoring. Summary of the Invention

[0005] This application provides an intelligent monitoring and anti-tampering method and system for the status of goods in logistics transportation, which improves the reliability of logistics transportation monitoring.

[0006] The first aspect of this application provides an intelligent monitoring and anti-tampering method for the status of goods in logistics transportation, applied to an intelligent monitoring and anti-tampering platform. The platform includes an on-board monitoring terminal, a mobile app, and a backend management platform. The method includes: sending a monitoring command to the on-board monitoring terminal to enable the on-board monitoring terminal to monitor a target object; receiving BeiDou positioning data, cargo environmental parameters, and physical connection status data of a smart electronic lock reported by the on-board monitoring terminal; generating a real-time running trajectory of the target object based on the BeiDou positioning data; and processing the real-time running trajectory, cargo environmental parameters, and physical connection status data. A risk analysis is performed to obtain risk analysis results, including trajectory deviation risk, cargo environment risk, and physical connection status anomaly risk. Based on the risk analysis results, alarm information is generated and sent to the mobile APP. When the risk analysis results indicate the existence of the physical connection status anomaly risk, and the physical connection status anomaly risk meets preset electronic lock anomaly conditions, access control is implemented for the smart electronic lock, and access control data is generated. The BeiDou positioning data, cargo environment parameters, physical connection status data, real-time operating trajectory, risk analysis results, and alarm information are encrypted to generate an electronic evidence chain for the target monitoring object.

[0007] Optionally, the vehicle-mounted monitoring terminal includes a core control unit, a Beidou high-precision positioning module, a multi-sensor acquisition module, a 4G / 5G communication module, a Bluetooth near-field interaction module, and a smart electronic lock. Sending monitoring commands to the vehicle-mounted monitoring terminal to enable it to monitor the target object specifically includes: sending an initialization command to the vehicle-mounted monitoring terminal to start program services and configure operating parameters, including the backend management platform address, the Bluetooth near-field interaction module serial port number, the smart electronic lock input / output ports, and the multi-sensor acquisition module input / output ports; and sending monitoring commands to the vehicle-mounted monitoring terminal via the 4G / 5G communication module to enable it to monitor the target object. The vehicle monitoring terminal issues monitoring commands to enable command parsing; receives Bluetooth command detection results from the mobile APP reported by the vehicle monitoring terminal; configures the data reporting time interval of the vehicle monitoring terminal; receives vehicle monitoring data reported by the vehicle monitoring terminal, the vehicle monitoring data including Beidou positioning data from the Beidou high-precision positioning module, switch status change information, and data collected by the first multi-sensor; the vehicle monitoring data is reported according to the reporting time interval or based on a preset anomaly trigger; and issues unlock / lock commands or operating parameter update commands to the vehicle monitoring terminal through the 4G / 5G communication module.

[0008] Optionally, risk analysis is performed on the real-time operating trajectory, the cargo environmental parameters, and the physical connection status data to obtain risk analysis results. Specifically, this includes: calculating the deviation between the real-time operating trajectory and the preset transportation route; if the deviation is greater than a preset deviation threshold, generating the trajectory deviation risk; generating the cargo environmental risk when the cargo environmental parameters meet preset environmental risk conditions; calculating the difference between the physical connection status data and preset level reference data to obtain the level difference; generating the physical connection status anomaly risk when the level difference is greater than a preset difference threshold; and obtaining the risk analysis results based on the trajectory deviation risk, the cargo environmental risk, and the physical connection status anomaly risk.

[0009] Optionally, before obtaining the risk analysis results, the method further includes: when the lock cylinder rotation angle data in the physical connection status data is greater than a preset rotation threshold, acquiring the unlocking command record of the smart electronic lock; determining whether there is a valid unlocking command corresponding to the lock cylinder rotation angle data in the unlocking command record; if there is no valid unlocking command corresponding to the lock cylinder rotation angle data, determining that a forced lock destruction event has occurred, and determining the time period corresponding to the lock cylinder rotation angle data as the destruction time period of the forced lock destruction event; acquiring the vibration frequency of the cargo compartment of the target monitoring object within the destruction time period; if the vibration frequency of the cargo compartment is greater than a preset frequency threshold within the destruction time period, and the duration of the time when the vibration frequency of the cargo compartment is greater than the preset frequency threshold is greater than a preset duration, generating the physical connection status abnormal risk.

[0010] Optionally, the smart electronic lock is subject to access control, and access control data is generated. Specifically, this includes: generating an access freeze command and sending the command to the vehicle monitoring terminal to freeze the smart electronic lock's operating permissions; receiving an unfreezing request from the mobile app, the request containing user identity information; verifying the user identity information, and generating a one-time dynamic key and sending it to the mobile app upon successful verification, the dynamic key being used by the mobile app to send an unlocking command to the smart electronic lock; and obtaining the access control data based on the access freeze command, the unfreezing request record, the user identity verification information, and the one-time dynamic key's key generation record.

[0011] Optionally, the method further includes: responding to an initialization startup request sent by the mobile app, sending runtime environment configuration parameters and core service initialization data to the mobile app; responding to a user login authentication request sent by the mobile app, verifying user account and password information, and returning the authentication result; responding to a Bluetooth connection establishment request sent by the mobile app, wherein the Bluetooth connection establishment request is a connection establishment request with the Bluetooth near-field interaction module of the vehicle monitoring terminal within a preset range; responding to a smart electronic lock operation permission verification request sent by the mobile app, performing permission verification based on the currently logged-in account: when the permission verification is successful, sending runtime environment configuration parameters and core service initialization data to the mobile app. The PP sends an interface activation command to enable the unlock / lock operation buttons on the mobile APP; when the permission verification fails, it sends an interface restriction command to the mobile APP to disable the smart electronic lock control buttons; in response to the permission status synchronization request sent by the mobile APP in each preset period, it sends the permission verification result for each preset period to the mobile APP; it receives user lock / unlock operation information reported by the mobile APP and verifies the legality of the user lock / unlock operation information; it receives lock / unlock control command records sent by the mobile APP to the vehicle monitoring terminal through the Bluetooth near-field interaction module.

[0012] Optionally, the method further includes: sending an initialization start command to the vehicle-mounted monitoring terminal; sending a port reference setting command to the vehicle-mounted monitoring terminal to enable the vehicle-mounted monitoring terminal to set and record the initial level reference value of the smart electronic lock; issuing a switch status polling command to the vehicle-mounted monitoring terminal to enable the vehicle-mounted monitoring terminal to monitor the switch status of the smart electronic lock; receiving the locking status information of the smart electronic lock reported by the vehicle-mounted monitoring terminal: when the locking status information is an unlocked state, continuing to receive switch status polling data; when the locking status information is a locked state, issuing a port detection command to the vehicle-mounted monitoring terminal; receiving the real-time level status data of the smart electronic lock reported by the vehicle-mounted monitoring terminal; calculating the level difference between the real-time level status data and the initial level reference value: when the level difference is less than a preset level threshold, continuing to receive switch status polling data; when the level difference is greater than or equal to the preset level threshold, confirming an abnormal disconnection event; and receiving the abnormal disconnection event reported by the vehicle-mounted monitoring terminal through the 4G / 5G communication module.

[0013] Optionally, the BeiDou positioning data, cargo environmental parameters, physical connection status data, real-time operating trajectory, risk analysis results, and alarm information are encrypted to generate an electronic evidence chain for the target monitoring object. Specifically, this includes: extracting environmental features from the cargo environmental parameters and generating an environmental state fingerprint based on these features; performing an XOR operation on the environmental state fingerprint and the physical connection status data to obtain the XOR result, and generating a data integrity check code based on the XOR result; dividing the real-time operating trajectory into multiple continuous sub-trajectories according to a preset time window; calculating the spatiotemporal feature values ​​of the sub-trajectories, and calculating the... The process involves: determining the degree of deviation between the spatiotemporal feature values ​​and a preset trajectory model; assessing the credibility of the risk analysis results based on the degree of deviation; associating the credibility assessment results with the alarm information to generate evidence rating data; constructing an evidence data package, which includes evidence rating data and a data integrity check code; acquiring the hardware fingerprint of the smart electronic lock and generating an encryption key based on the hardware fingerprint; encrypting the evidence data package using the encryption key to obtain an encrypted evidence data package; storing the encrypted evidence data package on a blockchain network and generating the electronic evidence chain based on a preset blockchain consensus mechanism.

[0014] Secondly, embodiments of this application provide an intelligent monitoring and anti-tampering system for the status of goods in logistics transportation. The intelligent monitoring and anti-tampering system for the status of goods in logistics transportation includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the intelligent monitoring and anti-tampering system for the status of goods in logistics transportation to perform the method described in the first aspect and any possible implementation thereof.

[0015] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on an intelligent monitoring and anti-tampering system for the status of goods in logistics transportation, cause the intelligent monitoring and anti-tampering system for the status of goods in logistics transportation to perform the method described in the first aspect and any possible implementation thereof.

[0016] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: 1. The system sends monitoring commands to the vehicle-mounted monitoring terminal through the backend management platform and receives BeiDou positioning data, cargo environmental parameters, and physical connection status data of the smart electronic locks, achieving unified collection of multi-dimensional data. Based on this, it generates the real-time running trajectory of the target monitored object using BeiDou positioning data and comprehensively analyzes the real-time running trajectory, cargo environmental parameters, and physical connection status data to obtain risk analysis results including trajectory deviation risk, cargo environmental risk, and physical connection status anomaly risk. This collaborative analysis mechanism of multi-dimensional data, combined with physical connection status data, determines whether there is a risk of cargo swapping, while effectively solving the trajectory monitoring problem under complex road conditions by utilizing the high precision of BeiDou positioning. When the system detects a risk, it promptly generates alarm information and pushes it to the mobile APP for rapid response. Especially when an abnormal physical connection status occurs, the system automatically manages the access permissions of the smart electronic locks, further enhancing security. Simultaneously, the system generates an electronic evidence chain of the target monitored object based on the multi-dimensional data collected throughout the process, providing a reliable basis for subsequent event tracing and improving the reliability of logistics transportation monitoring.

[0017] 2. By integrating a core control unit, a Beidou high-precision positioning module, a multi-sensor acquisition module, a 4G / 5G communication module, a Bluetooth near-field interaction module, and a smart electronic lock into the vehicle-mounted monitoring terminal, a complete terminal data acquisition system was constructed. Operating parameters, including the backend management platform address and the input / output ports of each functional module, were configured via initialization commands to ensure the normal operation of the terminal equipment. During data acquisition, the system uses the 4G / 5G communication module to send and parse monitoring commands, while simultaneously receiving Bluetooth command detection results from the mobile app, information on the on / off status changes of the smart electronic lock, and data collected from the first multi-sensor, achieving unified acquisition of multi-source data. By configuring the data reporting interval, the system can report vehicle monitoring data at fixed intervals or trigger reporting when an anomaly is detected, improving the flexibility and real-time performance of data transmission. This multi-module collaborative data acquisition and transmission mechanism not only ensures the integrity and accuracy of monitoring data but also enhances the system's adaptability and reliability in complex scenarios.

[0018] 3. By establishing a multi-level access control mechanism for smart electronic locks, the security of logistics transportation is effectively improved. When the system detects an abnormal risk in the physical connection status, it immediately freezes the operation permissions of the smart electronic lock by sending an access freeze command to the vehicle monitoring terminal, preventing unauthorized unlocking operations. When it is necessary to unfreeze the status, the system requires the mobile APP to submit an unfreezing application containing user identity information, ensuring the legitimacy of the operator through strict identity verification. After successful verification, the system generates a one-time dynamic key and sends it to the mobile APP. This unlocking mechanism based on temporary authorization avoids the risk of leakage and theft of traditional fixed keys. It solves the problem of identifying and preventing the risk of goods swapping in complex scenarios, improving the security and controllability of the logistics transportation process. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the system architecture of an embodiment of an intelligent monitoring and anti-tampering method for the status of goods in logistics transportation or an intelligent monitoring and anti-tampering system for the status of goods in logistics transportation, which applies the present application. Figure 2 This is a flowchart illustrating an intelligent monitoring and anti-tampering method for the status of goods in logistics transportation according to an embodiment of this application. Figure 3 This is a flowchart illustrating the execution steps of the vehicle-mounted monitoring terminal in this embodiment of the application; Figure 4 This is a flowchart illustrating how the vehicle-mounted monitoring terminal uploads vehicle-mounted monitoring data to the backend management platform, as described in this application embodiment. Figure 5 This is a schematic diagram of the process by which a mobile APP sends an unlock or lock command to a vehicle monitoring terminal via a Bluetooth near-field interaction module in an embodiment of this application. Figure 6 This is a schematic diagram of the process by which an abnormal disconnection event occurs in the smart electronic lock in this application embodiment, and the event is reported to the back-end management platform via the 4G / 5G communication module. Figure 7 This is a schematic diagram of the process by which the multi-sensor acquisition module reports an abnormal event to the back-end management platform via the 4G / 5G communication module in an embodiment of this application. Figure 8 This is a schematic diagram of the structure of the electronic device in the embodiments of this application.

[0020] Explanation of reference numerals in the attached figures: 201, Central Processing Unit; 202, Read-Only Memory; 203, Random Access Memory; 204, Bus; 205, Input / Output Interface; 206, Input Section; 207, Output Section; 208, Storage Section; 209, Communication Section; 210, Driver; 211, Removable Media. Detailed Implementation

[0021] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0022] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. In the description of the embodiments of this application, the term "multiple" means two or more. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features.

[0023] Figure 1 The diagram illustrates a system architecture of an embodiment of an intelligent monitoring and anti-tampering method or system for monitoring and anti-tampering the status of goods in logistics transportation, which can be applied to this application.

[0024] As the positioning core of the entire intelligent monitoring and anti-tampering system, the BeiDou satellite continuously provides high-precision positioning signals to the vehicle-mounted monitoring terminal through its satellite navigation system. The BeiDou high-precision positioning module inside the vehicle-mounted monitoring terminal receives these signals, thereby acquiring key location data such as the real-time timestamp, latitude and longitude coordinates, and speed of the transport vehicle. The vehicle-mounted monitoring terminal is the core hardware device deployed on the transport vehicle, responsible for front-end data acquisition, preliminary processing, and data transmission. It integrates a BeiDou high-precision positioning module, intelligent electronic locks, a multi-sensor acquisition module, a core control unit, a Bluetooth near-field interaction module, and a 4G / 5G communication module. It can monitor the location of goods, environmental parameters, and lock status in real time, and report key data and abnormal alarms to the back-end management platform through local processing and remote communication, and execute various instructions issued by the platform. The BeiDou high-precision positioning module is responsible for receiving signals from the BeiDou satellite to obtain the current transport vehicle's timestamp, geographical latitude and longitude coordinates, and real-time speed with high precision.

[0025] The intelligent electronic lock employs a dual physical and electronic security mechanism, primarily used for the locking and management of containers or cargo compartments. It not only unlocks and locks based on authorized commands from the backend or mobile app, but also incorporates a status detection unit and security monitoring loop. This allows it to monitor its physical connection status in real time (e.g., whether the locking rope has been cut or illegally pulled out), and immediately reports any anomalies to the core control unit. A multi-sensor acquisition module collects environmental parameters during cargo transportation in real time, including but not limited to temperature and humidity inside the cargo compartment, vibration intensity of the cargo, and the opening and closing status of the cargo compartment. This data is used by the core control unit to determine whether the cargo faces environmental risks (e.g., excessive temperature), abnormal vibration, or unauthorized opening.

[0026] The core control unit coordinates the operation of all integrated modules. It is responsible for receiving and processing data from the Beidou high-precision positioning module, smart electronic lock, and multi-sensor acquisition module; parsing and executing instructions sent by the back-end management platform or mobile APP; making preliminary judgments and reporting of abnormal events detected locally; and transmitting all relevant data and alarm information to the back-end management platform through the 4G / 5G communication module.

[0027] The Bluetooth near-field communication module is used to establish short-range wireless communication between the vehicle monitoring terminal and the mobile APP. It is primarily responsible for receiving unlock / lock commands sent by the mobile APP, thereby controlling the smart electronic lock in a near-field environment, and executing user commands after successful authorization verification.

[0028] The 4G / 5G communication module is a crucial channel for remote data transmission and command reception between the vehicle-mounted monitoring terminal and the back-end management platform. It ensures that the vehicle-mounted monitoring terminal can report the collected BeiDou positioning data, cargo environmental parameters, smart electronic lock status data, and various alarm information to the back-end management platform in real time and stably, and receive monitoring commands and operating parameter updates from the back-end.

[0029] The mobile app provides users with a convenient interface, enabling cargo owners, carriers, and other stakeholders to monitor and manage the system anytime, anywhere. As the user's entry point, the mobile app establishes two-way communication with the backend platform via an encrypted channel. Users can initiate unlock / lock requests, view real-time tracks, receive alarm information, and query historical records through the app. Upon receiving user requests, the backend platform performs permission verification, data retrieval, or command distribution, and pushes the execution results or feedback information to the app in real time. The app features user permission management, real-time display of smart electronic lock status and cargo environmental parameters, and reception and display of various alarm information. It also connects to the vehicle monitoring terminal via a Bluetooth near-field communication module for remote or near-field control of the smart electronic locks.

[0030] The backend management platform, deployed on a cloud server, serves as the central hub and decision-making unit for the entire intelligent monitoring and anti-tampering system. It is responsible for receiving and aggregating multi-source data uploaded from all vehicle-mounted monitoring terminals, performing data analysis, generating real-time operational trajectories, and conducting risk analysis on the trajectories, cargo environment, and physical connection status of the locks to identify anomalies. Based on the risk analysis results, the platform generates alarm information and pushes it to the mobile app. Simultaneously, it manages the operation permissions of the smart electronic locks and ultimately integrates all key data and event records to generate an immutable electronic evidence chain, providing strong evidence for dispute resolution.

[0031] Figure 2 This is a flowchart illustrating an intelligent monitoring and anti-tampering method for the status of goods in logistics transportation, as described in an embodiment of this application.

[0032] Please see Figure 2 This application embodiment discloses an intelligent monitoring and anti-tampering method for the status of goods in logistics transportation. The intelligent monitoring and anti-tampering platform includes an on-board monitoring terminal, a mobile APP, and a back-end management platform. The method includes: S101. Send the monitoring command to the vehicle-mounted monitoring terminal so that the vehicle-mounted monitoring terminal can monitor the target monitoring object; Step S101, as the starting point of the entire monitoring process, is mainly used to initialize the monitoring and control of the target object. Specifically, it may include the following steps: sending an initialization command to the vehicle-mounted monitoring terminal to enable the terminal to start its program service and configure operating parameters, including the backend management platform address, Bluetooth near-field interaction module serial port number, smart electronic lock input / output port, and multi-sensor acquisition module input / output port; sending monitoring commands to the vehicle-mounted monitoring terminal via the 4G / 5G communication module to enable command parsing; receiving the Bluetooth command detection results reported by the vehicle-mounted monitoring terminal from the mobile APP; and receiving the smart electronic lock input / output port reported by the vehicle-mounted monitoring terminal. The system includes: displaying information on the on / off status changes of the electronic lock; receiving first multi-sensor data reported by the vehicle-mounted monitoring terminal; configuring the data reporting interval of the vehicle-mounted monitoring terminal; receiving vehicle-mounted monitoring data reported by the vehicle-mounted monitoring terminal, the vehicle-mounted monitoring data including BeiDou positioning data from the BeiDou high-precision positioning module, the on / off status change information, and the first multi-sensor data, the vehicle-mounted monitoring data being reported according to the reporting interval or based on a preset anomaly trigger; and sending unlock / lock commands or operating parameter update commands to the vehicle-mounted monitoring terminal via the 4G / 5G communication module. The vehicle-mounted monitoring terminal includes a core control unit, a BeiDou high-precision positioning module, a multi-sensor acquisition module, a 4G / 5G communication module, a Bluetooth near-field interaction module, and an intelligent electronic lock.

[0033] Figure 3 This is a flowchart illustrating the execution steps of the vehicle-mounted monitoring terminal in this embodiment of the application. The following is a summary of the steps. Figure 3 The above steps will be explained in detail.

[0034] Monitoring commands are generated by the backend management platform based on transportation tasks and security policies. These commands are used to activate and manage various functions of the vehicle-mounted monitoring terminal. Commands include initialization, parameter configuration, data acquisition, lock control, and status queries, and are typically generated automatically by the system or issued manually before the transportation task begins. Commands are transmitted to the terminal in encrypted form via a 4G / 5G module and parsed and executed by the core control unit. This enables remote control of modules such as positioning, communication, and locks, ensuring full-process monitoring and anomaly response capabilities during transportation.

[0035] After receiving the monitoring command from the background, the vehicle-mounted monitoring terminal initiates the program service, loads core modules such as positioning, sensing, communication, and locking, and enters a standby state. The system completes resource initialization, communication link testing, and module status checks to ensure that subsequent commands can be parsed and executed normally, providing basic support for data acquisition and remote control.

[0036] The core control unit enters the initialization phase for operating parameters. This step involves loading a preset parameter table or receiving parameter configurations from the backend platform to set the serial port number, input / output ports, and communication addresses for each functional module. Operating parameters include the server address of the backend management platform (for data reporting and command reception), the serial port number of the Bluetooth near-field interaction module (for communication with the app), the input / output ports of the smart electronic lock (for controlling lock opening and closing actions and reading status levels), and the I / O ports of the multi-sensor acquisition module (for reading data such as temperature, humidity, and vibration). Through this parameter initialization step, the system establishes communication bridges between modules, enabling the vehicle terminal to perform basic monitoring tasks. For example, configuring the correct serial port number ensures that the Bluetooth module can normally access the Bluetooth command channel; otherwise, subsequent unlocking command parsing will fail.

[0037] After parameter initialization, the core control unit continuously listens for control commands sent by the backend management platform via the 4G / 5G communication module. During this process, the terminal periodically polls the communication module's receive buffer to determine if any remote commands are pending. If a command is detected, the command parsing process begins immediately; otherwise, the next step of Bluetooth command listening is executed. This step establishes a real-time control channel between the backend and the terminal while ensuring the priority of remote control. For example, the backend can issue commands such as updating parameters or locking the device en route; the terminal will prioritize parsing and executing these commands to achieve dynamic control.

[0038] If no background command is detected, the core control unit will invoke the Bluetooth near-field interaction module to access the Bluetooth communication channel of the mobile app. By listening to Bluetooth broadcasts or pairing channels, it will determine if there are any user-initiated local operation commands. If a Bluetooth command is detected, the command parsing process will begin; otherwise, the next monitoring step will continue. This step is significant because it allows on-site personnel to control the locks via the app in environments without a public network. Bluetooth communication features low power consumption and near-field security, making it suitable for use in enclosed transportation scenarios. For example, after arriving at the destination, the driver can send an unlocking request via the app's Bluetooth channel, and the terminal will respond immediately.

[0039] If the Bluetooth command is also not detected, the system continues to determine if the on / off state of the smart electronic lock has changed. This detection relies on a closed circuit of conductive steel wire in the smart electronic lock's circuitry. This circuit breaks when the lock is cut, damaged, or illegally opened, and the control unit can identify the fault by reading the change in the voltage level of the lock's input port. This step ensures that the system can immediately detect and trigger a reporting mechanism when unauthorized physical intervention (such as forced entry) occurs. For example, if the lock accidentally disconnects, the system will identify it as an abnormal risk and immediately report the data.

[0040] Next, the system determines whether there are any anomalies in the first multi-sensor data collected by the multi-sensor acquisition module. This first multi-sensor data includes information on the temperature, humidity, vibration intensity, and open / closed status of the cargo container's environment, comprehensively reflecting changes in the physical environment of the cargo during transportation. This module monitors the temperature, humidity, vibration intensity, and container open / closed status of the cargo environment in real time, comparing these data with the system's built-in safety thresholds to determine if any issues such as exceeding limits or unauthorized opening have occurred. The system's built-in safety thresholds are parameters preset based on transportation standards, industry regulations, and historical transportation data for different types of cargo, used to determine whether the environment is within a safe range.

[0041] If none of the above anomalies occur, the system will enter the data reporting time judgment logic to determine whether the timed reporting conditions are met. This mechanism records the timestamp of the last data report and compares it with the current time to determine whether the set reporting interval (e.g., 5 minutes) has been exceeded. The reporting interval is preset by the backend management platform based on the monitoring accuracy requirements of the transportation task and network resource optimization strategies, and can be dynamically configured by issuing monitoring commands to the vehicle monitoring terminal. If the interval is met, the system will execute the data reporting process; if not, it will restart from the backend command listening and enter the next cycle. This step ensures that even if no anomalies occur, the system can periodically upload status data, maintaining continuous awareness of the transportation status by the backend.

[0042] When an instruction needs to be executed, the core control unit enters the instruction parsing process. This process involves bitwise judgment of the function code in the instruction data packet to identify whether the instruction type is "unlock" or "lock". If it is this type of control instruction, the system prepares to execute the locking action; if the judgment result is not, the system will jump to the "update operating parameters" step. In this step, the core control unit extracts the parameter field content from the instruction packet and updates the current operating parameters, including but not limited to the background management platform address, Bluetooth serial port binding information, sensor input / output port mapping, and data reporting interval. The parameter update process usually does not require a system restart, can be completed while the system is running, and takes effect immediately. After the update is completed, the system will automatically return to the background instruction listening stage of the main loop to continue waiting for the next round of instructions or data acquisition events. The instruction parsing logic is implemented by looking up the instruction code in a table and verifying data integrity to ensure the accuracy and security of instruction execution.

[0043] Upon recognizing an unlock or lock command, the core control unit will drive the smart electronic lock module to execute the corresponding operation. This operation controls the energization of the lock's electromagnet to open and close the lock cylinder, while simultaneously monitoring the feedback circuit level in real time to determine the success of the operation. This step ensures that lock operations controlled by the backend or app are accurately executed and their status recorded. For example, if the backend authorizes an unlock command, the terminal executes the power-on unlock action, reads the lock status to confirm whether the lock has been successfully unlocked, and if it fails, it retryes or reports an error.

[0044] If the parsed instruction is a parameter update instruction, the system will enter the parameter update process. This process overwrites the original parameter table and reloads the module configuration to achieve functions such as server address changes, reporting interval adjustments, and sensor port remapping. This function supports remote maintenance and dynamic adjustment of terminal configurations during transportation, improving system flexibility and stability. For example, the backend can adjust the data reporting frequency en route to meet monitoring needs during high-risk periods on specific road sections.

[0045] When the system determines that data reporting is required, the core control unit will package the current BeiDou high-precision positioning data, the status of the smart electronic lock, and data from the multi-sensor acquisition modules, and report it to the backend management platform via the 4G / 5G communication module. The data packet structure adopts a structured JSON format, and includes metadata such as timestamp, device ID, data type, and signature fields.

[0046] Figure 4 This is a flowchart of the process of the vehicle monitoring terminal uploading vehicle monitoring data to the backend management platform in this embodiment of the application. The following is a combination of... Figure 4 This document explains the process of uploading vehicle monitoring data from the vehicle monitoring terminal to the backend management platform.

[0047] like Figure 4 As shown, after receiving the initialization start command, the core control unit of the vehicle monitoring terminal first completes system initialization and initiates the data reporting process. The system then acquires data from the Beidou high-precision positioning module and verifies the validity of the positioning data. If the data is invalid, it is re-acquired; if the data is valid, it continues to parse information such as timestamp, latitude and longitude, and vehicle speed. Next, the system sequentially acquires the physical connection status information of the smart electronic lock and environmental monitoring data from multi-sensor acquisition modules (such as temperature, humidity, vibration, and door magnets). After completing data acquisition, the system checks the network status of the 4G / 5G communication module. If the network is unavailable, the current data is temporarily stored in a local cache, and the system continuously checks whether the network recovers; if the network is normal, the currently acquired positioning information, lock status, environmental parameters, and data to be sent in the cache are packaged together and reported to the backend management platform through the communication module, achieving stable, efficient, and traceable transmission of key data during transportation.

[0048] S102. Receive Beidou positioning data, cargo environmental parameters and physical connection status data of the smart electronic lock in the vehicle monitoring terminal reported by the vehicle monitoring terminal. The vehicle-mounted monitoring terminal acquires real-time positioning data such as latitude, longitude, speed, and timestamps via the BeiDou positioning module and uploads it to the backend platform via a 4G / 5G module to generate transportation trajectories. A multi-sensor acquisition module periodically collects environmental parameters such as temperature, humidity, and vibration, and uploads them along with time information. The physical connection status of the smart electronic lock is monitored via a digital input port; an anomaly generates a low-level or no-signal status, which the system uses to determine if the lock has been damaged and trigger an alarm. All of the above data constitutes the core information for cargo status monitoring, providing support for subsequent risk analysis.

[0049] S103. Generate the real-time running trajectory of the target monitoring object based on the BeiDou positioning data; The backend management platform, based on the BeiDou positioning data periodically reported by the vehicle-mounted monitoring terminal, organizes and splices latitude and longitude information in chronological order to generate the real-time running trajectory of the monitored object. The system performs data quality control through rules such as distance between trajectory points, speed, and time intervals, eliminating outliers to ensure trajectory continuity and accuracy. This trajectory reflects changes in position, dwell time, and path deviation during transportation, serving as a crucial foundation for subsequent risk analysis and the generation of electronic evidence chains.

[0050] S104. Perform risk analysis on the real-time running trajectory, the cargo environmental parameters and the physical connection status data to obtain risk analysis results. The risk analysis results include trajectory deviation risk, cargo environmental risk and physical connection status abnormality risk. Step S104 identifies potential safety risks such as trajectory deviation, environmental loss of control, or lock damage during transportation, thereby providing a basis for decision-making in subsequent alarm generation, access control, and electronic evidence chain construction. Specifically, this may include the following steps: calculating the deviation between the real-time operating trajectory and the preset transportation route; if the deviation exceeds a preset deviation threshold, generating the trajectory deviation risk; generating the cargo environmental risk when the cargo environmental parameters meet environmental risk conditions; calculating the difference between the physical connection status data and preset level reference data to obtain the level difference degree; generating the physical connection status anomaly risk when the level difference degree exceeds a preset difference threshold; and obtaining the risk analysis result based on the trajectory deviation risk, the cargo environmental risk, and the physical connection status anomaly risk.

[0051] During trajectory deviation risk analysis, the system first calls the continuous sequence of location points in the real-time running trajectory and loads the preset transportation route associated with the transportation task. The preset transportation route is a standard path set by the backend management platform during the task generation stage, containing multiple key latitude and longitude control points, and constructed into a complete transportation channel model in the form of directed line segments. The system calculates the shortest distance between each location point in the real-time trajectory and the preset route to obtain a deviation sequence, and combines this with the matching status of the current location of the transported object with the route to determine whether there is a significant deviation. If any value in the deviation is greater than the trajectory deviation threshold, such as exceeding 200 meters, the system determines that the current location has deviated from the transportation route, generates a trajectory deviation risk result, and records this result along with a timestamp and deviation distance to provide a basis for subsequent alarm triggering and trajectory backtracking. For example, when a transport vehicle has three consecutive trajectory points exceeding the preset boundary outside a designated closed area in the city, the system will determine that there is detour or unauthorized path behavior, forming a trajectory deviation risk indicator.

[0052] During the identification of environmental risks for goods, the system reads environmental parameter data reported by multi-sensor acquisition modules, mainly including key indicators such as temperature, humidity, vibration amplitude, and light intensity. The backend platform calls the corresponding environmental risk rule set, i.e., the preset environmental risk conditions, based on the type of transported goods. These preset environmental risk conditions are pre-set by the backend management platform according to the type of transported goods and their safety requirements, and include the safety threshold range and joint judgment conditions for each parameter. The system compares each set of received environmental parameters with the corresponding risk conditions. If any parameter exceeds the safe range, or if multiple parameters combine to form a dangerous state (e.g., high temperature accompanied by severe vibration), a cargo environmental risk identifier is generated. This process is implemented through logical judgment and threshold matching algorithms, and the risk type, corresponding parameter value, and acquisition time are recorded. When identifying risks related to abnormal physical connection status, the system first calls the physical connection status data of the smart electronic lock reported by the vehicle monitoring terminal. This data is read and uploaded in real time by the terminal's internal level acquisition circuit, reflecting whether the lock is in an electrically closed state. The platform calculates the difference between this level data and the preset level reference data to obtain the level difference degree and determines whether the difference degree exceeds the set threshold. If the difference exceeds a threshold, such as a sudden change from a normal high level to a low level or no signal, the system will determine that the lock may be disconnected, the circuit is damaged, or there has been illegal tampering, generating a risk of abnormal physical connection. This judgment mechanism is based on the principle of voltage level change, using the level change when the lock circuit is disconnected as the trigger for abnormal events. For example, if the lock's voltage level signal is 0V for three consecutive acquisition cycles during transportation, the system will consider that the lock has been forcibly disconnected, immediately mark it as a safety risk, and record the abnormal location.

[0053] Optionally, the generation of physical connection status abnormality risk may also include the following steps: when the lock cylinder rotation angle data in the physical connection status data is greater than a preset rotation threshold, the unlocking command record of the smart electronic lock is obtained; Determine whether there is a valid unlocking command in the unlocking command record that corresponds to the lock cylinder rotation angle data; If there is no valid unlocking command corresponding to the lock cylinder rotation angle data, it is determined that a forced lock destruction event has occurred, and the time period corresponding to the lock cylinder rotation angle data is determined as the destruction time period of the forced lock destruction event; The vibration frequency of the cargo storage body of the target monitoring object is obtained within the damage time period. If the vibration frequency of the cargo storage body is greater than a preset frequency threshold within the damage time period, and the duration for which the vibration frequency of the cargo storage body is greater than the preset frequency threshold is greater than a preset duration, the abnormal risk of the physical connection status is generated.

[0054] In this embodiment, when the lock cylinder rotation angle data detected in the physical connection status data exceeds a preset rotation threshold, the system will initiate the lock abnormal behavior identification process. The lock cylinder rotation angle is collected in real time by an angular displacement sensor integrated inside the smart electronic lock. This sensor, based on the Hall effect or rotary potentiometer principle, converts the rotation amplitude of the lock cylinder during the opening process into quantifiable angle data. The preset rotation threshold is a critical value set by the backend platform based on the minimum angle required for normal lock opening, usually in degrees. For example, a typical mechanical lock cylinder needs to rotate 90° to legally unlock, so the threshold can be set to 80° to identify whether there is unauthorized forced rotation behavior. By comparing the lock cylinder rotation angle with this threshold in real time, the system determines whether the current lock behavior may constitute an illegal operation. If the threshold is exceeded, it is considered that there is a risk of unlocking behavior, and further verification is needed to determine whether it is a legal operation.

[0055] If the lock cylinder rotation angle exceeds a threshold, the system then retrieves the unlocking command record of the smart electronic lock to determine whether the physical action corresponds to a valid unlocking command. The unlocking command record is a digital command data packet generated by the backend platform and sent to the vehicle monitoring terminal via Bluetooth or 4G / 5G communication. It includes information such as the sending time, bound user, target device number, and operation permissions. Upon receiving the lock cylinder rotation event, the system matches the event time with the locally cached unlocking command time window. If a corresponding command exists within the set valid time range (e.g., ±10 seconds) before and after the rotation, and the command is legitimate, complete, and passes permission verification, it is considered a valid unlock. This verification step effectively distinguishes between legitimate operations and potential sabotage, preventing misjudgments. For example, if the driver sends an unlocking request via the app and successfully issues the command, the system considers it a legitimate operation; otherwise, if no command is found, the system proceeds to the next step.

[0056] If the system does not find a valid unlocking command within the time period corresponding to the lock cylinder rotation angle data, it can be determined that a forced lock-breaking event has occurred. In this case, the system marks the time point when the lock cylinder rotation angle exceeds the threshold, along with the pre-set buffer time period (e.g., 5 seconds before and after), as the destruction time period for subsequent multi-source data joint analysis. The logical basis of this step is that a smart lock cylinder must rely on a system-authorized unlocking command to operate normally. If physical rotation occurs without this command, it is highly likely caused by destructive means such as prying or twisting. Recording the destruction time period not only helps in subsequent analysis to determine if other synchronous anomalies exist, such as cylinder vibration or circuit disconnection, but also serves as a key time anchor point in the electronic evidence chain. For example, if the system records that the lock cylinder suddenly rotates more than 120° at a certain moment, and there are no user operations or platform authorization records before or after, it can be preliminarily identified as an illegal opening event.

[0057] After determining the time period of damage, the system further acquires the vibration frequency of the cargo compartment of the target monitored object within that time period to enhance the accuracy of abnormal behavior identification. The cargo compartment vibration frequency is collected by a triaxial accelerometer installed inside the vehicle terminal or at a critical structural location in the cargo box. This sensor, based on MEMS (Micro-Electro-Mechanical Systems) technology, calculates the vibration frequency (Hz) per unit time by measuring the acceleration changes of an object in three directions. The system filters, integrates, and extracts the frequency from the sensor data within the damage time period to obtain the average and maximum vibration frequencies for that period, and compares them with a preset frequency threshold set in the platform. This threshold is typically set in conjunction with the cargo box structure, transportation environment, and normal operating conditions; for example, the vibration frequency of a typical cargo box should not exceed 5Hz during normal transportation. If the actual frequency exceeds the threshold, and the time exceeding the threshold lasts for more than a preset duration (e.g., 3 consecutive seconds), the system can determine that there was a significant impact or violent shaking within that damage time period, further confirming the occurrence of physical damage. By jointly analyzing abnormal lock cylinder rotation and abnormal vibration frequency, the system can effectively avoid misjudgment based on a single signal, improving the accuracy and reliability of risk identification. For example, in a transportation task, if the lock cylinder rotates to 110° without any unlocking command, and the vibration frequency reaches 8Hz for 4 seconds within 5 seconds, the system will generate a risk of abnormal physical connection status and upload it to the backend platform to trigger an alarm or further action.

[0058] The risks of trajectory deviation, cargo environment, and abnormal physical connection status together constitute the risk analysis results of the comprehensive safety assessment during transportation, providing a basis for decision-making in subsequent alarm triggering, access control, and the construction of electronic evidence chains.

[0059] S105. Generate alarm information based on the risk analysis results, and send the alarm information to the mobile APP; After receiving the risk analysis results output in step S104, the backend management platform first identifies and classifies the risk types. Each risk type is configured with a corresponding alarm template and response level. For example, trajectory deviation risk is associated with the "route deviation" alarm type, cargo environmental risk triggers the "environmental over-limit" alarm type, and physical connection status abnormality risk corresponds to the "lock abnormality" alarm type. The system calls the corresponding template according to the risk type and fills the alarm template with the core elements of the risk event, including risk time, risk location, risk level, risk description, relevant data screenshots or trajectory fragments, to form structured alarm information.

[0060] Once generated, the system synchronously sends the alarm information to the mobile app bound to the transportation task via a push notification engine. This app establishes a secure connection with the backend management platform via HTTPS and uses a push subscription mechanism to monitor the backend platform's anomaly event channel in real time. As soon as the backend system generates an alarm, it sends it to the app via the push channel. Upon receiving the alarm data, the app triggers its local alarm module to perform display operations, including pop-up notifications, sound alerts, or vibration feedback, ensuring users are informed of risk events immediately.

[0061] S106. When the risk analysis result indicates that there is a risk of abnormal physical connection status, and the risk of abnormal physical connection status meets the preset abnormal conditions of electronic lock, the smart electronic lock is subject to access control, and access control data is generated. Step S106 involves freezing, controlling, or restoring lock permissions in a timely manner under high-risk conditions such as potential unauthorized opening, power failure, or unauthorized operation of the lock to prevent damage or loss of goods during transportation due to failure of physical protection. Specifically, this may include the following steps: generating a permission freeze command and sending it to the vehicle monitoring terminal to freeze the operation permissions of the smart electronic lock; receiving an unfreezing request from the mobile app, the unfreezing request containing user identity information; verifying the user identity information, and generating a one-time dynamic key and sending it to the mobile app when verification is successful, the one-time dynamic key being used by the mobile app to send an unlocking command to the smart electronic lock; and obtaining the permission management data based on the permission freeze command, the unfreezing request record, the user identity verification information, and the key generation record of the one-time dynamic key.

[0062] When risk analysis indicates a risk of abnormal physical connection status, the system will further perform condition matching judgment on the anomaly. Specifically, it will compare the current abnormal state with preset electronic lock anomaly conditions. If these conditions are met, the lock is considered to have serious abnormal behavior, requiring a higher-level warning response process. The abnormal physical connection status risk refers to behaviors detected during monitoring, such as unauthorized opening, communication interruption, abnormal lock cylinder rotation, and abnormal lock body voltage. The system compares these abnormal states with preset electronic lock anomaly conditions item by item. These preset conditions are set by the platform based on historical fault modes and security policies, such as "lock opened unauthorized three times consecutively," "lock cylinder rotation angle exceeds the threshold and lasts for more than 30 seconds," or "lock communication interruption exceeds 5 minutes." Once the current abnormal state meets any preset condition, the system determines that the lock has a substantial risk and increases the weight of the event through a credibility assessment mechanism. Subsequently, it will be prioritized for alarm notification, encrypted evidence generation, and blockchain uploading processes to ensure that the physical anomaly can be quickly identified, tracked, and evidenced. This mechanism enhances the system's ability to accurately identify and respond to critical security components through condition-triggered matching.

[0063] In the access control process, the backend management platform first generates an access freeze command. This command instructs the vehicle monitoring terminal to suspend local control over the smart electronic lock. The freeze command includes parameters such as the lock number, freeze type, freeze timestamp, and associated risk event number. The system sends this command to the vehicle monitoring terminal via the 4G / 5G communication module, and the core control unit executes the access freeze operation. This prevents the Bluetooth near-field communication module or local button from issuing unlocking commands to the smart electronic lock, thereby putting the lock into a controlled state and stopping it from responding to unauthorized commands.

[0064] When permissions are frozen, the backend system simultaneously displays the frozen status in the mobile app and opens an unfreezing request portal, allowing authorized users to submit unfreezing requests. When a user initiates an unfreezing operation, the mobile app automatically collects the user's identity information, including user ID, bound mobile phone number, biometric information or dynamic password authentication results, and encapsulates the unfreezing request into a structured request message and sends it to the backend platform. After receiving the unfreezing request, the backend system calls the identity verification module to determine the legality of the user's identity information. The determination method may include database comparison, authentication system verification, or multi-factor authentication. After successful verification, the system generates a one-time dynamic key for the user. This key is generated based on a timestamp, user ID, lock number, and internal encryption seed, and has the characteristics of single-use validity and non-replayability. The system sends the key to the mobile app through a secure channel. The user can use this key to send an unlocking command to the smart electronic lock via the Bluetooth near-field interaction module to temporarily restore unlocking permissions.

[0065] To ensure the auditability and traceability of the access control process, the system generates detailed data records throughout the entire freezing, unfreezing, and identity verification process, forming access control data. This data includes access freeze command records, unfreezing application records, user identity information verification data, one-time dynamic key generation records, and lock response status feedback, etc., and is uniformly stored in the background evidence chain database, forming a complete security control chain linked to the transportation task.

[0066] S107. Encrypt the BeiDou positioning data, cargo environmental parameters, physical connection status data, real-time operation trajectory, risk analysis results, and alarm information, and generate an electronic evidence chain for the target monitoring object.

[0067] To ensure the authenticity, integrity, and traceability of the monitoring data, this embodiment, after completing the real-time operation trajectory, cargo environmental parameters, physical connection status data, and risk analysis of the target monitoring object, further generates an electronic evidence chain through encryption processing and a trustworthy assessment mechanism. Specifically, the process may include the following steps: extracting environmental features from the cargo environmental parameters and generating an environmental state fingerprint based on these features; performing an XOR operation on the environmental state fingerprint and the physical connection state data to obtain the XOR result, and generating a data integrity check code based on the XOR result; dividing the real-time running trajectory into multiple continuous running sub-trajectories according to a preset time window; calculating the spatiotemporal feature values ​​of the running sub-trajectories and calculating the deviation between the spatiotemporal feature values ​​and a preset trajectory model; evaluating the credibility of the risk analysis results based on the deviation, and obtaining a credibility evaluation result; associating the credibility evaluation result with the alarm information to generate evidence rating data; constructing an evidence data package, which includes evidence rating data and a data integrity check code; acquiring the hardware fingerprint of the smart electronic lock and generating an encryption key based on the hardware fingerprint; encrypting the evidence data package based on the encryption key to obtain an encrypted evidence data package; storing the encrypted evidence data package in a blockchain network and generating the electronic evidence chain based on a preset blockchain consensus mechanism.

[0068] In the specific implementation process, the system extracts features from cargo environmental parameters to construct foundational fingerprint data for data integrity verification. Cargo environmental parameters include physical quantities such as temperature, humidity, light intensity, and vibration frequency, which are reported in real-time by multi-sensor acquisition modules. The system extracts key features such as maximum, minimum, mean, variance, and instantaneous fluctuation rate through sliding window processing and statistical analysis methods, forming a set of multi-dimensional numerical vectors called environmental features. Subsequently, the system uses a hash function (such as SHA-256) to perform a digest calculation on this environmental feature vector, generating a fixed-length, high-entropy, collision-resistant environmental state fingerprint, serving as a unique identifier of the current transportation environment state. This fingerprint not only compresses the original data volume but can also be used for subsequent integrity verification and data encryption processing. For example, if the temperature is 26℃, the humidity is 45%, and the vibration frequency is 3Hz within a certain monitoring period, the system encodes these features to generate a fingerprint such as a9f3d5...c78e.

[0069] Based on the generated environmental state fingerprint, the system further performs an XOR operation with the physical connection state data reported by the smart electronic lock. The physical connection state data mainly includes the lock's current voltage level, switch status indicator, and lock cylinder rotation angle, represented in binary format. The system performs a bitwise XOR operation on the binary representation of the environmental state fingerprint and the physical connection state data to obtain a new intermediate result, implicitly binding the environment and physical state in this way. XOR operations are lightweight, secure, and reversible, effectively enhancing the inherent coupling between data and preventing the forgery of single data items. Subsequently, the system uses the XOR result to generate a data integrity check code, commonly using methods such as CRC32 and HMAC-SHA512. This check code will be used as the basis for integrity verification in subsequent data packet construction. If the verification fails, the system will determine that the data may have been tampered with. For example, an XOR result of 01101100... will generate a check code of de3a9c...f27d.

[0070] After data binding and verification code generation, the system performs structured processing on the real-time trajectory of the monitored target. This trajectory consists of latitude, longitude, speed, and timestamps periodically reported by the BeiDou high-precision positioning module. The system divides the trajectory data into multiple continuous sub-trajectories according to a preset time window (e.g., every 5 minutes), thereby obtaining more granular trajectory behavior units. The division process is achieved by sorting by timestamps and aggregating through a sliding window, ensuring that each trajectory segment has a similar time span and point density. This approach provides a computational foundation for subsequent anomaly detection and trajectory modeling. For example, 08:00–08:05 is a sub-trajectory segment containing approximately 30 coordinate points.

[0071] For each sub-trajectory, the system calculates its spatiotemporal characteristic values, including average speed, rate of change of heading angle, trajectory curvature, and dwell time. These features are extracted from the trajectory point set using mathematical methods (such as vector angle calculation and finite difference method). The system compares these features with a pre-built trajectory model. The pre-built trajectory model is a segmented trajectory feature template trained using clustering analysis (such as K-Means) and pattern recognition algorithms based on historical normal transportation trajectory samples. Each type of transportation task (such as cold chain and dangerous goods transportation) has a corresponding model, which contains the statistical boundaries and behavioral patterns of typical trajectories. The system uses methods such as Dynamic Time Warping (DTW) or Euclidean distance to compare the current sub-trajectory with the target model and outputs a deviation value to assess whether the trajectory deviates from expectations. For example, if the average speed of the current sub-trajectory is 60 km / h, but the model reference value is 50 km / h, the deviation is 0.7, and the system will mark it as a moderate deviation.

[0072] Based on the aforementioned deviation values, the system further evaluates the credibility of the risk analysis results for all sub-trajectories. The evaluation process comprehensively considers the trajectory deviation value, the duration of the anomaly, the frequency of the anomaly, and whether it is synchronized with other risks (such as lock malfunctions), using a weighted scoring mechanism to generate a credibility score from 0 to 100. A higher score indicates a more reliable risk event. The system can set credibility levels (e.g., high, medium, low) based on the evaluation results, providing a basis for subsequent alarm handling strategies. For example, if the trajectory deviation value continuously exceeds 0.8 for a duration of 15 minutes, the system's credibility score is 92, and it is marked as high credibility.

[0073] After the assessment is completed, the system integrates the credibility assessment results with the alarm information to generate evidence rating data. The alarm information includes alarm type, time, location, and device ID. The system maps the assessment results to the corresponding alarms based on the timestamp and device identifier, and adds a rating field. At the structural level, the credibility score is written as metadata into the alarm information structure, forming a unified data object called "evidence rating data." For example, the original trajectory deviation alarm becomes after merging: "Track Deviation | Credibility 92 | High Risk | 08:05 | Device ID: ELOCK001". This rating data can be used for subsequent intelligent sorting, priority processing, or judicial evidence preservation.

[0074] After structured integration, the system constructs an evidence data package together with the evidence rating data and integrity check codes. The evidence data package is encapsulated in JSON or CBOR format and contains fields such as a unique evidence ID, timestamp, device identifier, alarm details, credibility score, and integrity check code. This data package is the smallest encrypted unit of the electronic evidence chain, characterized by its clear structure, verifiability, and traceability. The data package is constructed on a backend server or in a trusted execution environment. The system assigns a unique index to each data package and records processing logs for subsequent auditing.

[0075] To enhance data security, the system further acquires the hardware fingerprint of the smart electronic lock and generates an encryption key based on it. The hardware fingerprint refers to unique identification information read from within the lock (such as chip serial number, MAC address, voltage characteristics), which is then used to generate a feature digest using a hash function (such as SHA-1). The system uses a key derivation function (such as PBKDF2) to encrypt this digest, generating a set of symmetric encryption keys for subsequent encryption of evidence data packets. This method ensures that each device has a unique key, preventing unauthorized decryption of data across devices. For example, if the lock ID is "ELK-2023-XYZ", the generated key would be 0xa48f...c9d1.

[0076] Subsequently, the system uses the generated encryption key to perform symmetric encryption on the evidence data packet, resulting in an unreadable encrypted evidence data packet. The encryption process employs national cryptographic algorithms compatible with AES-256 or ChaCha20 to ensure the confidentiality and tamper resistance of the data during transmission and storage. After encryption, the data packet size increases slightly, and the system marks the encryption algorithm version and the device ID using the key as metadata written into the encryption header for subsequent verification and decryption. For example, the original data packet is 1024 bytes, and the encrypted packet is 1152 bytes, including the key version and lock fingerprint information.

[0077] Finally, the system stores the encrypted evidence data packet in the blockchain network and generates an electronic evidence chain based on a preset blockchain consensus mechanism. In this embodiment, the blockchain network adopts a consortium blockchain structure, such as a private chain built on Hyperledger Fabric, with participating nodes including transportation companies, regulatory agencies, and judicial organs. The consensus mechanism uses the RAFT algorithm, which features low latency and high consistency, making it suitable for edge computing and real-time evidence storage scenarios. The system encapsulates the encrypted data packet into on-chain transaction content and broadcasts it to multiple nodes in the blockchain network. Successful on-chain processing is considered achieved after multiple endorsing nodes confirm and write it into a block. The on-chain process generates information such as block hashes, timestamps, and transaction IDs, forming a unique and tamper-proof electronic evidence chain. For example, after an encrypted packet representing a high-credibility trajectory deviation event is uploaded to the blockchain, the system records its block hash as 0x7cbe...91f2, and all information about the event can be queried, verified, and retrieved at any time on the platform using the evidence ID.

[0078] A method for intelligent monitoring and anti-tampering of cargo status in logistics transportation, the method further includes the following steps: responding to an initialization start request sent by a mobile APP, sending runtime environment configuration parameters and core service initialization data to the mobile APP; responding to a user login authentication request sent by the mobile APP, verifying user account and password information, and returning the authentication result; responding to a Bluetooth connection establishment request sent by the mobile APP, the Bluetooth connection establishment request being a connection establishment request with the Bluetooth near-field interaction module of the vehicle monitoring terminal within a preset range; responding to a smart electronic lock operation permission verification request sent by the mobile APP, performing permission verification based on the currently logged-in account: when the permission is granted... During verification, an interface activation command is sent to the mobile app to enable the unlock / lock operation buttons. If the permission verification fails, an interface restriction command is sent to the mobile app to disable the smart electronic lock control buttons. In response to the permission status synchronization request sent by the mobile app in each preset period, the permission verification results for each preset period are sent to the mobile app. User lock / unlock operation information reported by the mobile app is received, and the legality of the user lock / unlock operation information is verified. Lock / unlock control command records sent by the mobile app to the vehicle monitoring terminal through the Bluetooth near-field interaction module are received.

[0079] Figure 5 This is a schematic diagram illustrating the process of a mobile app sending unlock or lock commands to a vehicle monitoring terminal via a Bluetooth near-field communication module in an embodiment of this application. The following is a description of the process. Figure 5 The above steps will be explained in detail.

[0080] When the mobile app launches, the system responds to an initialization request, sending configuration parameters and service data related to the transportation task, including platform address, task information, and Bluetooth communication settings. After parsing, the app loads core modules such as permission management and Bluetooth communication, completing the runtime environment initialization and ensuring the normal operation of subsequent interactions with the vehicle terminal.

[0081] After initialization, users must complete identity authentication via the mobile app. Upon receiving the login authentication request, the system verifies the account and password information. Successful authentication is based on a comparison of the user's account information with encrypted credentials in the backend user permission database. If a match is found, a time-limited login token is generated and returned to the app, signifying successful authentication. This login token will serve as the user's sole credential for permission verification and operation authorization in subsequent operations, avoiding security and user experience issues caused by frequent password entry. If authentication fails, the user is prompted to re-enter the password or request a password retrieval. This authentication mechanism ensures that the operation of the smart electronic lock is initiated only by authorized personnel, protecting the authorization boundaries of transportation security control.

[0082] After identity authentication, the mobile app needs to establish a Bluetooth communication connection with the vehicle monitoring terminal. The system responds to the app's Bluetooth connection request by activating the broadcast scanning function of the Bluetooth near-field communication module to discover vehicle monitoring terminal devices within a preset range. Upon receiving the device broadcast information, the mobile app filters and matches based on device identifiers, connecting only to the vehicle terminal bound to the current transportation task. Once the connection is established, a stable low-power Bluetooth communication channel is formed between the app and the vehicle monitoring terminal, supporting subsequent lock / unlock command interactions and status synchronization. This connection process employs a pairing authentication mechanism to ensure that the connected device is a trusted device, preventing unauthorized devices from accessing the control link. For example, if a transport vehicle enters a warehouse area, the app will automatically identify and connect to the corresponding vehicle terminal within Bluetooth range, preparing to execute subsequent lock / unlock operations.

[0083] After a Bluetooth connection is established, the mobile app proactively initiates a smart electronic lock operation permission verification request. The system performs real-time permission matching based on the currently logged-in account information and the permission database to determine if the user has the necessary operating permissions for the current lock. This permission verification rule is typically set based on the transportation task role; for example, the driver may only have permission to unlock the lock en route, while the administrator can perform all operations. Upon successful verification, the backend system sends an interface activation command to the app, unlocking and enabling the "unlock" or "lock" buttons on the app interface, allowing the user to perform actual control operations. If the verification fails, an interface restriction command is sent, disabling the operation buttons and displaying a permission restriction prompt to prevent accidental or unauthorized operation. The real-time nature of this permission verification mechanism ensures that control actions are always within the authorized scope, avoiding security vulnerabilities caused by expired permissions. For example, before the driver operates the lock mid-journey, the system will verify in real-time whether they have the authorization to operate for the current time period, thereby dynamically controlling permission boundaries.

[0084] After the permission status is established, the app periodically sends permission status synchronization requests to the backend to maintain the real-time validity of current operation permissions. Upon receiving the synchronization request, the backend system re-verifies the validity of the login token and the permission status, and sends the verification result back to the app, updating the interface status. This synchronization mechanism typically occurs every 30 seconds or 1 minute, ensuring that if the permission status changes, such as when a user's permissions are temporarily revoked by a backend administrator, the app can promptly identify and revoke their operation permissions. This method enables dynamic permission management and real-time interface linkage, improving system security and responsiveness. For example, if a risk alarm occurs during transportation, the management platform can immediately freeze the relevant user permissions, and the app can recognize the frozen status and automatically disable control buttons in the next synchronization cycle.

[0085] Once permission verification is successful and the interface is activated, the mobile app will listen for user actions to unlock or lock the lock. This listening module captures user clicks through an event-triggered mechanism and reads information such as the operation type, timestamp, and current lock status to form a complete operation command intent. After capturing the operation event, the system immediately performs a preliminary local verification of the operation's legitimacy, including whether it is within a valid time period, whether a Bluetooth connection is available, and whether the lock is not in a frozen state, ensuring that the preconditions for the operation are met. This listening behavior provides the triggering basis for subsequent command generation and sending, ensuring the immediacy of the operation and the consistency of the response. For example, after the user clicks the "unlock" button, the system will complete the legitimacy verification and prepare to generate control commands within milliseconds.

[0086] After confirming the legitimacy of the user's operation, the mobile app sends an unlock or lock control command to the vehicle monitoring terminal via the previously established Bluetooth near-field interaction module. This command is encapsulated using the standard Bluetooth serial communication protocol and includes the operation type, user ID, timestamp, and digital signature. Upon receiving the command, the vehicle monitoring terminal's core control unit parses it and drives the corresponding execution module of the smart electronic lock to complete the physical unlock or lock action. Simultaneously, the execution result and command content are packaged and sent back to the backend management platform, forming a complete operation record. Through the coordinated implementation of these steps, the mobile app and the vehicle monitoring terminal achieve a complete interactive process from initialization to authorization verification to operation execution, improving both the security and ease of use of the lock control.

[0087] Optionally, a method for intelligent monitoring and anti-tampering of the status of goods in logistics transportation, the method further includes the following steps: sending an initialization start command to the vehicle-mounted monitoring terminal; sending a port reference setting command to the vehicle-mounted monitoring terminal to enable the vehicle-mounted monitoring terminal to set and record the initial level reference value of the intelligent electronic lock; sending a switch status polling command to the vehicle-mounted monitoring terminal to enable the vehicle-mounted monitoring terminal to monitor the switch status of the intelligent electronic lock; receiving the locking status information of the intelligent electronic lock reported by the vehicle-mounted monitoring terminal: when the locking status information is an unlocked state, continue... Continue receiving switch status polling data; when the lock status information is locked, send a port detection command to the vehicle monitoring terminal; receive real-time level status data of the smart electronic lock reported by the vehicle monitoring terminal; calculate the level difference between the real-time level status data and the initial level reference value; when the level difference is less than a preset level threshold, continue receiving switch status polling data; when the level difference is greater than or equal to the preset level threshold, confirm that an abnormal disconnection event has occurred; receive the abnormal disconnection event reported by the vehicle monitoring terminal through the 4G / 5G communication module.

[0088] Figure 6 This is a schematic diagram illustrating the process of reporting an abnormal disconnection event of the smart electronic lock to the backend management platform via the 4G / 5G communication module in this embodiment of the application. The following is a detailed explanation. Figure 6 The above steps will be explained in detail.

[0089] Before abnormal disconnection monitoring begins, the system sends an initialization start command to the vehicle monitoring terminal, waking up the core control unit and loading the lock monitoring-related modules. The command includes the task number, port configuration, and reporting parameters. After completing self-test and interface activation, the terminal enters standby mode to ensure that the lock monitoring function operates normally according to the unified configuration.

[0090] After initialization, the system needs to send a port reference setting command to the vehicle monitoring terminal to set and record the initial level reference value of the smart electronic lock. The purpose of this operation is to establish a judgment benchmark for subsequent level detection, enabling precise perception of the physical connection status from the hardware interface layer. Specifically, the core control unit reads the digital level of the smart electronic lock in its initial locked state through the GPIO (General Purpose Input / Output) interface and records it as the reference value. This level reference value is typically a stable high or low level, indicating that the lock's electronic control circuit is in a normal closed or open state. The system caches this data in the vehicle's local storage and simultaneously uploads a copy to the background for task binding. By setting the reference value, subsequent quantitative judgment of potential abnormal states of the lock can be achieved. For example, if the reference value is high (3.3V), and a subsequent low level (0V) is detected, it can be determined as an open circuit or short circuit.

[0091] To ensure real-time monitoring of the lock status, the vehicle-mounted monitoring terminal initiates a polling operation on the smart electronic lock's open / closed status after initialization. This polling process involves the core control unit periodically reading the lock's status pins and determining if it is currently locked. The polling cycle can be configured according to the importance of the transportation task; for example, high-value goods can be polled once every 1 second, while ordinary goods can be polled once every 5 seconds. The polling mechanism works by continuously reading the status value and comparing it with the previous reading to determine if there has been a status change. If the lock status is detected as "unlocked," the system continues the next round of polling until the status changes to "locked," thus entering the next stage of the level verification process. This step enables real-time monitoring of the lock's closed state, providing a prerequisite for subsequent judgment of open events. For example, if the lock fails to fully close during transportation due to bumps, the polling mechanism will continuously detect the "unlocked" state, and the system will not mistakenly judge it as an abnormal open event.

[0092] When the status polling result is "locked," the system immediately performs real-time detection of the smart electronic lock port to confirm the current lock connection status. This operation involves the core control unit rereading the input and output level status of the lock interface and using the result as the current real-time level status data. This detection typically employs a high-precision ADC (analog-to-digital converter) module combined with a digital filtering algorithm to eliminate the influence of momentary jitter or interference signals, ensuring the accuracy and stability of the collected data. This detection result will serve as a comparison object for subsequent consistency checks, identifying any abnormal changes in the physical connection status. Through this step, a quantitative mapping of the current lock status can be established, providing a direct reference for judging the risk of disconnection. For example, if a level of 2.8V is detected after a lock is engaged, while the previously set benchmark is 3.3V, the system will proceed to the next step to calculate the difference.

[0093] After acquiring real-time voltage level data, the system performs a consistency check against the voltage level reference value recorded during the initialization phase to identify any port status anomalies. Its core principle is to calculate the voltage level difference—the difference between the current voltage level and the reference voltage level—and compare it to a preset voltage level threshold. This preset threshold is determined through analysis and statistical analysis of the voltage level fluctuation range of the smart electronic lock's ports under normal operating conditions. Typically, this is achieved by repeatedly testing the stable output voltage of the lock's ports under various environmental conditions (such as temperature, humidity, electromagnetic interference, and vehicle vibration) to obtain its typical fluctuation range. A certain safety margin coefficient is then added to this range to ultimately determine a voltage difference limit that can tolerate normal minor fluctuations while effectively identifying abnormal states. This voltage difference serves as the basis for voltage level consistency verification. When the voltage level difference is less than this threshold, the system considers the connection status normal and returns to the polling process to continue monitoring. When the difference is greater than or equal to the threshold, the system confirms an abnormal disconnection event. This threshold is typically set between 0.3V and 0.5V, which can tolerate normal deviations caused by equipment aging while effectively identifying physical disconnection or destructive behavior under abnormal conditions. For example, if the reference level is 3.3V and the current detection is 2.6V, the difference is 0.7V, which exceeds the preset upper limit, and the system will immediately determine that there is a risk of disconnection.

[0094] Once an abnormal disconnection event is confirmed in the smart electronic lock, the core control unit will immediately perform a data reporting operation, proactively reporting the event data to the backend management platform via the 4G / 5G communication module. The reported content includes the event occurrence time, the detected real-time voltage level, the voltage reference value, the difference calculation result, the lock status, the vehicle's current location, and relevant onboard sensor status information. To improve data integrity and security, the reported data is encapsulated in structured JSON format and includes a device number and encrypted signature, ensuring the backend can verify and trace the data source. Upon receiving the reported data, the backend platform will trigger a series of response actions, such as pushing alarms to the mobile app, freezing current lock permissions, generating an electronic evidence chain, and recording the event log, achieving closed-loop processing of abnormal events. For example, in a transportation task, if the lock detects a sudden drop in high voltage level during transit, after the system reports it, the backend will immediately lock the vehicle's current operating permissions and notify supervisory personnel for handling. Through these steps, the system achieves a complete technical closed loop for the smart electronic lock, from physical connection initialization, continuous monitoring, status judgment to anomaly identification and data reporting.

[0095] Figure 7 This is a schematic diagram illustrating the process by which the multi-sensor acquisition module reports an abnormal event to the backend management platform via the 4G / 5G communication module in an embodiment of this application.

[0096] The system performs initialization startup operations, activates the anomaly monitoring service, and completes the initial configuration of the sensor detection process. Subsequently, the core control unit enters the monitoring loop, periodically calling the multi-sensor acquisition module to obtain real-time status data during cargo transportation, covering key parameters such as the temperature, humidity, vibration intensity, and open / closed status of the cargo container. After acquiring the data, the system sequentially assesses various potential risks: first, it checks whether the cargo container has been illegally opened; if an anomaly is detected, it immediately proceeds to the data reporting stage. If normal, it continues to check for abnormal displacement of the cargo; if cargo displacement is detected, it immediately triggers a report. If the position is normal, it further checks the temperature threshold; if the temperature exceeds a preset safety value, it also triggers an anomaly report. If the temperature is within the normal range, it continues to check whether the humidity exceeds the limit; if it exceeds the humidity threshold, it triggers a report. If all the above assessments are normal, the system returns to the sensor data acquisition step and continues with the next round of monitoring. When any of the above conditions are deemed abnormal, the core control unit will immediately and proactively report the abnormality type, abnormal value, and current location information to the backend management platform via the 4G / 5G communication module, enabling real-time early warning and dynamic risk response for the cargo transportation environment. This process ensures comprehensive and real-time monitoring of critical transportation status and completes closed-loop data reporting as soon as an abnormality occurs.

[0097] Please see Figure 8 This is a schematic diagram of the structure of the electronic device in the embodiments of this application.

[0098] It should be noted that, Figure 8 The structure of the intelligent monitoring and anti-tampering system for the status of goods in logistics transportation shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0099] like Figure 8 As shown, an intelligent monitoring and anti-tampering system for the status of goods in logistics transportation includes a central processing unit 201, which can perform various appropriate actions and processes according to a program stored in a read-only memory 202 or a program loaded from a storage section 208 into a random access memory 203, such as executing the methods described in the above embodiments. The random access memory 203 also stores various programs and data required for system operation. The central processing unit 201, the read-only memory 202, and the random access memory 203 are interconnected via a bus 204. An input / output interface 205 is also connected to the bus 204.

[0100] The following components are connected to the input / output interface 205: an input section 206 including audio input devices, push-button switches, etc.; an output section 207 including an LCD display, audio output devices, indicator lights, etc.; a storage section 208 including a hard disk, etc.; and a communication section 209 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 209 performs communication processing via a network such as the Internet. A drive 210 is also connected to the input / output interface 205 as needed. A removable medium 211, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 210 as needed so that computer programs read from it can be installed into the storage section 208 as needed.

[0101] Specifically, the intelligent monitoring and anti-tampering system for the status of goods in logistics transportation according to this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements the intelligent monitoring and anti-tampering method for the status of goods in logistics transportation provided in the above embodiment.

[0102] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the intelligent monitoring and anti-tampering system for the status of goods in logistics transportation described in the above embodiments; or it may exist independently and not be assembled into the intelligent monitoring and anti-tampering system for the status of goods in logistics transportation.

Claims

1. An intelligent monitoring and tamper-proofing method for the status of a logistics transported cargo, characterized in that, The application is applied to an intelligent monitoring and anti-tampering platform, the intelligent monitoring and anti-tampering platform comprises a vehicle-mounted monitoring terminal, a mobile terminal APP and a background management platform, and the method comprises the following steps: sending a monitoring instruction to the vehicle-mounted monitoring terminal, so that the vehicle-mounted monitoring terminal monitors a target monitoring object; receiving Beidou positioning data, cargo environment parameters and physical connection state data of an intelligent electronic lock in the vehicle-mounted monitoring terminal reported by the vehicle-mounted monitoring terminal; generating a real-time running track of the target monitoring object based on the Beidou positioning data; performing risk analysis on the real-time running track, the cargo environment parameters and the physical connection state data to obtain a risk analysis result, wherein the risk analysis result comprises a track deviation risk, a cargo environment risk and a physical connection state abnormality risk; generating an alarm information based on the risk analysis result and sending the alarm information to the mobile terminal APP; when the risk analysis result indicates that the physical connection state abnormality risk exists and the physical connection state abnormality risk meets a preset electronic lock abnormality condition, performing permission management on the intelligent electronic lock and generating permission management data; performing data encryption on the Beidou positioning data, the cargo environment parameters, the physical connection state data, the real-time running track, the risk analysis result and the alarm information and generating an electronic evidence chain of the target monitoring object.

2. The method of claim 1, wherein, The vehicle-mounted monitoring terminal comprises a core control unit, a Beidou high-precision positioning module, a multi-sensor acquisition module, a 4G / 5G communication module, a Bluetooth near-field interaction module and an intelligent electronic lock, and the step of sending a monitoring instruction to the vehicle-mounted monitoring terminal, so that the vehicle-mounted monitoring terminal monitors a target monitoring object, specifically comprises the following steps: sending an initialization instruction to the vehicle-mounted monitoring terminal, so that the vehicle-mounted monitoring terminal starts a program service and configures running parameters, wherein the running parameters comprise a background management platform address, a Bluetooth near-field interaction module serial number, an intelligent electronic lock input / output port and a multi-sensor acquisition module input / output port; downloading a monitoring instruction to the vehicle-mounted monitoring terminal through the 4G / 5G communication module, so that the vehicle-mounted monitoring terminal performs instruction analysis; receiving a Bluetooth instruction detection result of the mobile terminal APP reported by the vehicle-mounted monitoring terminal; configuring a data reporting time interval of the vehicle-mounted monitoring terminal, receiving vehicle-mounted monitoring data reported by the vehicle-mounted monitoring terminal, wherein the vehicle-mounted monitoring data comprises Beidou positioning data of the Beidou high-precision positioning module, the switch state change information and the first multi-sensor acquisition data, and the vehicle-mounted monitoring data is reported according to the reporting time interval or based on a preset abnormality trigger; downloading an open / close lock instruction or a running parameter update instruction to the vehicle-mounted monitoring terminal through the 4G / 5G communication module.

3. The method of claim 1, wherein, The step of performing risk analysis on the real-time running track, the cargo environment parameters and the physical connection state data to obtain a risk analysis result, specifically comprises the following steps: calculating a deviation degree of the real-time running track from a preset transportation route, and generating the track deviation risk if the deviation degree is greater than a preset deviation threshold; generate the cargo environment risk when the cargo environment parameter meets a preset environment risk condition; calculate a difference between the physical connection state data and preset level reference data to obtain a level difference degree, and generate the physical connection state abnormal risk when the level difference degree is greater than a preset difference threshold; obtain the risk analysis result based on the trajectory deviation risk, the cargo environment risk, and the physical connection state abnormal risk.

4. The method of claim 1, wherein, Before the risk analysis result is obtained, the method further includes: when the lock core rotation angle data in the physical connection state data is greater than a preset rotation threshold, obtain an unlocking instruction record of the intelligent electronic lock; determine whether there is a valid unlocking instruction corresponding to the lock core rotation angle data in the unlocking instruction record; if there is no valid unlocking instruction corresponding to the lock core rotation angle data, determine that a forced damage lock event occurs, and determine a damage time period of the forced damage lock event as a time period corresponding to the lock core rotation angle data; obtain a cargo warehouse body vibration frequency of the target monitoring object in the damage time period, and generate the physical connection state abnormal risk when the cargo warehouse body vibration frequency is greater than a preset frequency threshold in the damage time period, and a time length during which the cargo warehouse body vibration frequency is greater than the preset frequency threshold is greater than a preset time length.

5. The method of claim 1, wherein, The method further includes: generate a permission freezing instruction, and send the permission freezing instruction to the vehicle-mounted monitoring terminal to freeze the operation permission of the intelligent electronic lock; receive an unfreezing application sent by the mobile terminal APP, the unfreezing application containing user identity information; verify the user identity information, and generate a one-time dynamic key and send it to the mobile terminal APP when the verification is passed, the one-time dynamic key being used for the mobile terminal APP to send an unlocking instruction to the intelligent electronic lock; obtain the permission management data based on the permission freezing instruction, the unfreezing application record of the unfreezing application, the verification information of the user identity information, and the key generation record of the one-time dynamic key.

6. The method of claim 1, wherein, The method further includes: in response to an initialization start request sent by the mobile terminal APP, send running environment configuration parameters and core service initialization data to the mobile terminal APP; in response to a user login authentication request sent by the mobile terminal APP, verify user account password information, and return an authentication result; in response to a Bluetooth connection establishment request sent by the mobile terminal APP, the Bluetooth connection establishment request being a connection establishment request of a Bluetooth near field interaction module of the vehicle-mounted monitoring terminal within a preset range; in response to an intelligent electronic lock operation permission verification request sent by the mobile terminal APP, perform permission verification according to a currently logged-in account: when the permission verification is passed, send an interface activation instruction to the mobile terminal APP to enable an unlocking / locking operation button of the mobile terminal APP; when the permission verification is not passed, send an interface restriction instruction to the mobile terminal APP to disable an intelligent electronic lock control button of the mobile terminal APP. In response to a permission state synchronization request sent by the mobile terminal APP in each preset period, a permission verification result in each of the preset periods is sent to the mobile terminal APP; Receiving the user lock / unlock operation information reported by the mobile terminal APP, verifying the operation legality of the user lock / unlock operation information; Receiving the lock / unlock control instruction record sent by the mobile terminal APP to the vehicle-mounted monitoring terminal through the Bluetooth near-field interaction module.

7. The method of claim 1, wherein, The method further comprises: Sending an initialization start instruction to the vehicle-mounted monitoring terminal; Sending a port reference setting instruction to the vehicle-mounted monitoring terminal to make the vehicle-mounted monitoring terminal set and record the initial level reference value of the intelligent electronic lock; Sending a lock / unlock state polling instruction to the vehicle-mounted monitoring terminal to make the vehicle-mounted monitoring terminal monitor the lock / unlock state of the intelligent electronic lock; Receiving the lock state information of the intelligent electronic lock reported by the vehicle-mounted monitoring terminal: When the lock state information is in the unlocked state, continue to receive the lock / unlock state polling data; When the lock state information is in the locked state, send a port detection instruction to the vehicle-mounted monitoring terminal; Receiving the real-time level state data of the intelligent electronic lock reported by the vehicle-mounted monitoring terminal; Calculating the level difference between the real-time level state data and the initial level reference value: When the level difference is less than a preset level threshold, continue to receive the lock / unlock state polling data; When the level difference is greater than or equal to the preset level threshold, an abnormal disconnection event is confirmed to have occurred; Receiving the abnormal disconnection event reported by the vehicle-mounted monitoring terminal through the 4G / 5G communication module.

8. The method of claim 1, wherein, The data encryption of the Beidou positioning data, cargo environment parameters, physical connection state data, real-time running trajectory, risk analysis result and the alarm information and the generation of the electronic evidence chain of the target monitoring object specifically comprise: Extracting the environmental characteristics of the cargo environment parameters, and generating an environmental state fingerprint based on the environmental characteristics; XOR operation is performed on the environmental state fingerprint and the physical connection state data to obtain an XOR result, and a data integrity check code is generated based on the XOR result; The real-time running trajectory is divided into a plurality of continuous running sub-trajectories according to a preset time window; The spatio-temporal characteristic value of the running sub-trajectory is calculated, and the deviation degree of the spatio-temporal characteristic value from a preset trajectory model is calculated; Based on the deviation degree, the risk analysis result is evaluated for credibility to obtain a credibility evaluation result; The credibility evaluation result is associated with the alarm information to generate evidence rating data; An evidence data packet is constructed, which contains evidence rating data and a data integrity check code; A hardware fingerprint of the intelligent electronic lock is obtained, and an encryption key is generated based on the hardware fingerprint; The evidence data packet is encrypted based on the encryption key to obtain an encrypted evidence data packet; The encrypted evidence data packet is stored in a blockchain network, and the electronic evidence chain is generated based on a preset blockchain consensus mechanism.

9. An intelligent monitoring and tamper-proofing system for logistics transportation cargo status, characterized in that, The intelligent monitoring and tamper-proofing system for logistics transportation cargo status comprises one or more processors and a memory; the memory is coupled with the one or more processors, the memory is used for storing computer program codes, the computer program codes comprise computer instructions, and the one or more processors invoke the computer instructions to enable the intelligent monitoring and tamper-proofing system for logistics transportation cargo status to perform the method in any one of claims 1-8.

10. A computer-readable storage medium comprising instructions, characterized in that, The instructions, when running on the intelligent monitoring and tamper-proofing system for logistics transportation cargo status, enable the intelligent monitoring and tamper-proofing system for logistics transportation cargo status to perform the method in any one of claims 1-8.

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