Order automation management system based on geomagnetic detection

Abstract

The invention discloses an automatic order management system based on geomagnetic detection, and relates to the field of intelligent transportation, and the system comprises an anti-interference geomagnetic sensing unit which is used for outputting a stable vehicle existence state signal through an environment magnetic field disturbance suppression technology; the multi-source cooperative arbitration engine is used for fusing the geomagnetic state signal and space-time coordinate data of the video inspection equipment, and triggering order life cycle operation only when dual verification is consistent; the distributed fault-tolerant processing unit is used for starting a multi-mode rechecking process for the data conflict event and freezing an abnormal order; and the edge data chain type storage unit is used for generating a data chain which cannot be tampered according to an event time sequence in a weak network environment. According to the scheme, a geomagnetic system is upgraded from an isolated sensor to an intelligent terminal with environmental immunity, data autonomy, accurate decision and lifelong maintenance-free capability, and a high-reliability technical base is provided for the urban parking Internet of Things.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation, and in particular to an automatic order management system based on geomagnetic detection. Background Art

[0002] As the core sensing method for roadside parking management, geomagnetic detection technology has been widely used in vehicle entry and exit status recognition and order automation management. Its basic principle is to use high-sensitivity magnetic sensors to capture signal changes caused by vehicle disturbance of the earth's magnetic field to trigger order creation and termination. The current system architecture usually includes geomagnetic sensor nodes, wireless transmission modules and cloud-based order management platforms. As smart cities increase the efficiency of parking management, geomagnetic systems need to simultaneously solve environmental adaptability and multi-source data collaboration problems to achieve high-precision order life cycle management. However, existing technologies are limited by the physical bottlenecks of single-point detection modes, and face challenges such as interference from adjacent parking spaces and signal drift in complex urban roadside scenarios. There is an urgent need to improve reliability through algorithm optimization and architecture upgrades.

[0003] The current order management system based on geomagnetism has the following core defects: 1. A single geomagnetic sensor is easily interfered by the superimposed magnetic field of vehicles in adjacent parking spaces, resulting in a high false detection rate. 2. Geomagnetism relies on wireless transmission such as NB-IoT. Signal attenuation in underground garages or densely populated urban areas causes a data packet loss rate of over 15%. The disordered timing of events leads to order status conflicts. The traditional retransmission mechanism cannot guarantee data integrity, and operation and maintenance personnel are required to adjust the equipment on site. 3. The existing system lacks an adaptive abnormal arbitration mechanism. When geomagnetic and video inspection data conflict, the toll collector needs to manually review and correct the order. 4. The continuous working power consumption of the geomagnetic sensor is 1.2mA, and the battery life is less than 2 years; and external events such as construction machinery vibration and metal manhole cover displacement cause the equipment to frequently report false alarms, increasing the average annual maintenance cost by 37%. Therefore, based on the above difficulties, the present invention proposes an automated order management system based on geomagnetic detection. Summary of the Invention

[0004] Purpose of the Invention In order to solve the above problems, the purpose of the present invention is to provide an automated order management system based on geomagnetic detection, aiming to eliminate false triggering caused by interference from adjacent parking spaces and electromagnetic noise, establish an orderly storage and conflict self-healing mechanism for events in a weak network environment, ensure the atomicity of order status changes, and integrate multi-source arbitration and intelligent fault-tolerant logic to completely replace manual order correction operations.

[0005] Technical Solution To achieve the above objectives, the present invention provides an automated order management system based on geomagnetic detection. The system's geomagnetic sensor integrates a spectrum layering filter unit to separate vehicle magnetic field characteristics from low-frequency industrial frequency environmental noise. The engine receives geomagnetic status signals and video coordinates, performs three-level arbitration for anomaly detection, and triggers order creation and termination only when the three-level verification is consistent. Chain storage is used to ensure event orderliness in weak network conditions. Conflicting events trigger neighboring geomagnetic cross-verification and video re-acquisition. If invalid, the order is frozen and the user is guided to confirm. The sampling frequency is also dynamically switched based on the vehicle's presence status, effectively extending battery life. This solution upgrades the geomagnetic system from an isolated sensor to an intelligent terminal with environmental immunity, data autonomy, accurate decision-making, and lifelong maintenance-free capabilities, providing a highly reliable technical foundation for the city-level parking Internet of Things.

[0006] In a first aspect, the present invention provides an automated order management system based on geomagnetic detection, comprising: Anti-interference geomagnetic sensor unit, used to output a stable vehicle presence status signal through environmental magnetic field disturbance suppression technology; A multi-source collaborative arbitration engine is used to integrate geomagnetic state signals with the spatiotemporal coordinate data of video inspection equipment, triggering order lifecycle operations only when the dual verification is consistent; Distributed fault-tolerant processing unit, used to initiate a multimodal review process for data conflict events and freeze abnormal orders; Edge data chain storage unit, used to generate tamper-proof data chains according to event time sequence in weak network environments; The event chain storage conflict self-healing unit is used to trigger the self-healing process through the dual-factor conditions of relative time difference mutation and anchor point verification.

[0007] Furthermore, the anti-interference geomagnetic sensing unit integrates a dynamic noise suppression function, which separates low-frequency environmental disturbances from vehicle magnetic field characteristics and suppresses power-frequency electromagnetic interference to output a stable signal that meets a preset signal-to-noise ratio threshold.

[0008] Furthermore, the multi-source collaborative arbitration engine performs hierarchical verification, including time window matching between geomagnetic events and video recognition events, spatial consistency verification between video coordinates and target parking space geofences, and a statistical anomaly detection model built based on historical behavioral data. Orders that deviate from the normal distribution are automatically marked as risky and frozen, and high-risk orders need to be verified and unfrozen.

[0009] Furthermore, the distributed fault-tolerant processing unit activates a multimodal review process when arbitration fails, including controlling the video device to recapture the target parking space image and calling the cross-verification status of the geomagnetic sensors of adjacent parking spaces; if arbitration is still not possible, the order is frozen and the sound and light are activated to guide the car owner to actively confirm.

[0010] Furthermore, the chain nodes of the data chain include state hash values ​​to implement integrity verification of offline data.

[0011] Furthermore, the edge data chain storage unit is provided with a conflict self-healing mechanism, which applies for cloud data synchronization when hash verification fails and triggers adaptive calibration of geomagnetic sensor parameters.

[0012] Furthermore, the system is connected to a dynamic billing strategy executor, which matches regional rate rules based on the spatiotemporal attributes of orders to ensure atomic synchronization of rate switching and geomagnetic state change events.

[0013] Furthermore, it also includes an energy consumption adaptive scheduling module, which dynamically switches the sampling frequency according to the geomagnetic state and enters an ultra-low power consumption mode after the vehicle leaves.

[0014] Furthermore, the system integrates an external event coordination interface, connects to the municipal construction management system, and automatically shields geomagnetic signals and switches to a backup detection mode during construction.

[0015] Furthermore, it also includes a spectrum layered dynamic filtering unit, which processes the magnetic field signal by dividing the frequency bands and determines the effective vehicle event based on the dynamic energy ratio threshold.

[0016] Furthermore, the spectrum layered dynamic filtering unit determines the effective signal through a dynamic energy ratio threshold, and the formula is:

[0017] Where, is the dynamic energy ratio threshold; is the vehicle band energy; is the noise band energy; is the temperature compensation coefficient.

[0018] This autonomous data integrity system ensures absolute time sequence through hash anchor chaining. Dual-factor conflict detection accurately identifies weak network out-of-order and malicious tampering, triggering a multi-level self-healing process to eliminate order status errors caused by data asynchrony in traditional systems. This empowers edge devices with data self-healing capabilities, achieving a paradigm shift in intelligent fault tolerance.

[0019] In a second aspect, the present invention further provides a method for automated order management based on geomagnetic detection, the method being based on the system described in the first aspect, comprising: The original magnetic field signal is collected by the geomagnetic sensor, decomposed into three characteristic frequency bands, and the dynamic energy ratio of the vehicle frequency band energy to the noise frequency band energy is calculated to generate vehicle events; Receive geomagnetic vehicle events and license plate coordinates and timestamps reported by video inspection equipment, perform three-level hierarchical verification, and create or terminate parking orders only when the three-level verification is consistent; In a weak network environment, an event chain structure is constructed in time sequence, and the sudden change in the time difference between adjacent events is monitored in real time. When the conditions are met, a self-healing process is triggered, which includes discarding conflicting events, synchronizing the previous authoritative data with the cloud, resampling and calibrating the geomagnetic field, and reconstructing the event chain. The sampling frequency is dynamically adjusted based on the vehicle presence status obtained through real-time geomagnetic feedback, and the energy consumption strategy is updated synchronously after the order is terminated.

[0020] In a third aspect, the present invention also provides a computer device, comprising a management platform and a memory, wherein the management platform is connected to the memory, the memory is used to store computer programs, and the management platform is used to execute the computer programs stored in the memory, so that the computer device executes the aforementioned order automation management method based on geomagnetic detection.

[0021] In a fourth aspect, the present invention further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a management platform, the aforementioned method for automated order management based on geomagnetic detection is implemented.

[0022] This invention uses spectrum layered dynamic filtering technology to separate vehicle magnetic field characteristics from environmental noise, achieving full-temperature range anti-interference detection; constructs event chain storage and a dual-factor conflict self-healing mechanism to ensure data timing and integrity in weak network environments; deploys a three-level arbitration engine that integrates geomagnetic status, video coordinates, and historical behavior models to perform hierarchical verification; dynamically switches sampling frequencies based on vehicle presence status to achieve lifelong maintenance-free energy management. This solution reduces environmental noise false alarms to zero, and the accuracy of magnetic field feature extraction approaches physical limits; achieves system-level self-healing from event out-of-order and tampering attacks, and eliminates data loss in weak networks; multi-source arbitration suppresses the order status error rate to a negligible level, completely replacing manual intervention; and adaptive energy consumption scheduling allows geomagnetic equipment to exceed the chemical limits of batteries. It upgrades the geomagnetic system from an isolated sensor to an intelligent terminal with environmental immunity, data autonomy, accurate decision-making, and lifelong maintenance-free capabilities, providing a highly reliable technical foundation for the city-level parking Internet of Things.

[0023] Beneficial effects By implementing the above-mentioned automated order management system based on geomagnetic detection provided by the present invention, the following technical effects are achieved: (1) This application is based on a multimodal decision-making architecture based on spatiotemporal alignment, integrating geomagnetic state, video coordinates, and historical behavior models to perform hierarchical verification. Primary spatiotemporal window matching eliminates interference from device response delays, secondary geofence verification blocks cross-berth binding errors, and final statistical distribution analysis identifies abnormal orders. These three levels of verification form a logical closed loop, bringing the reliability of order creation and termination decisions close to the theoretical limit, completely replacing manual arbitration.

[0024] (2) A state-driven energy consumption control model is introduced to dynamically switch the sampling frequency based on the presence of vehicles as measured by real-time geomagnetic feedback. When no vehicles are present, the system enters micro-power monitoring mode. The sampling frequency is instantly increased to the full sampling rate upon vehicle entry, and is then delayed and reduced to avoid misjudgment after the vehicle leaves. This mechanism overcomes the limitations of battery life on deployment density, enabling zero-maintenance operation throughout the system's lifecycle.

[0025] (3) Through frequency domain feature decoupling and adaptive noise suppression, the interference of environmental magnetic field disturbances on geomagnetic detection is completely eliminated. It decomposes the original signal into characteristic frequency bands, implements enhancement in the vehicle magnetic field characteristic band, and performs dynamic filtering in the noise frequency band. This decouples the detection results from the ambient temperature, humidity, and electromagnetic field strength, achieving signal stability under all operating conditions and laying the physical foundation for high-precision order management.

[0026] (4) Build an autonomous system for data integrity, ensuring the absolute time sequence of events through hash anchor chain association. Dual-factor conflict detection accurately identifies weak network disorder and malicious tampering, triggering a multi-level self-healing process to fundamentally resolve the order status confusion caused by data asynchrony in traditional systems. This empowers edge devices with data self-healing capabilities, achieving a paradigm shift in intelligent fault tolerance. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to make the above-mentioned automatic order management system based on geomagnetic detection of the present invention more obvious and easy to understand, the following is a brief introduction to the drawings required for use in the specific implementation of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A schematic diagram showing a multi-source three-level arbitration engine; Figure 2 The flowchart of the present application method is shown. DETAILED DESCRIPTION

[0029] Example 1: This paper provides an automated order management system based on geomagnetic detection, including: an anti-interference geomagnetic sensor unit that outputs a stable vehicle presence signal using environmental magnetic field disturbance suppression technology; a multi-source collaborative arbitration engine that integrates geomagnetic status signals with spatiotemporal coordinate data from video inspection equipment, triggering order lifecycle operations only when the two are verified to be consistent; a distributed fault-tolerant processing unit that initiates a multimodal review process for data conflict events and freezes abnormal orders; an edge data chain storage unit that generates an unalterable data chain based on event time sequence in weak network environments; and an event chain storage conflict self-healing unit that triggers the self-healing process based on a dual-factor condition of relative time difference mutation and anchor point verification. Details are as follows.

[0030] The anti-interference geomagnetic sensing unit integrates a dynamic noise suppression function, which separates low-frequency environmental disturbances from vehicle magnetic field characteristics and suppresses power-frequency electromagnetic interference to output a stable signal that meets a preset signal-to-noise ratio threshold.

[0031] The multi-source collaborative arbitration engine is as follows Figure 1 As shown, hierarchical verification is performed, including time window matching between geomagnetic events and video recognition events, spatial consistency verification between video coordinates and target parking space geofences, and a statistical anomaly detection model built based on historical behavioral data. Orders that deviate from the normal distribution are automatically marked as risky and frozen, and high-risk orders need to be verified and unfrozen.

[0032] The distributed fault-tolerant processing unit activates a multimodal review process when arbitration fails, including controlling the video device to recapture the target parking space image and calling the geomagnetic sensor cross-verification status of the adjacent parking space; if arbitration is still not possible, the order is frozen and the sound and light are activated to guide the car owner to actively confirm.

[0033] The chain nodes of the data chain contain state hash values ​​to implement integrity verification of offline data.

[0034] The edge data chain storage unit is provided with a conflict self-healing mechanism. When hash verification fails, it applies for cloud data synchronization and triggers adaptive calibration of geomagnetic sensor parameters.

[0035] The system is connected to a dynamic billing strategy executor, which matches regional rate rules based on the spatiotemporal attributes of orders to ensure atomic synchronization of rate switching and geomagnetic state change events.

[0036] It also includes an energy consumption adaptive scheduling module that dynamically switches the sampling frequency according to the geomagnetic state and enters an ultra-low power consumption mode after the vehicle leaves.

[0037] The system integrates an external event coordination interface, connects to the municipal construction management system, and automatically shields geomagnetic signals and switches to a backup detection mode during construction.

[0038] A method for automated order management based on geomagnetic detection is also provided. The method flow is as follows: Figure 2 As shown, it includes: collecting original magnetic field signals through geomagnetic sensors, decomposing magnetic field signals into three characteristic frequency bands, and calculating the dynamic energy ratio of vehicle frequency band energy to noise frequency band energy to generate vehicle events; receiving geomagnetic vehicle events and license plate coordinates and timestamps reported by video inspection equipment, performing three-level hierarchical verification, and creating or terminating parking orders only when the three-level verification is consistent; constructing an event chain structure in time sequence under a weak network environment, monitoring the sudden change in time difference between adjacent events in real time, and when the conditions are met, triggering a self-healing process of discarding conflicting events, synchronizing previous authoritative data to the cloud, geomagnetic resampling calibration, and event chain reconstruction; dynamically adjusting the sampling frequency according to the vehicle presence status fed back by real-time geomagnetism, and synchronously updating the energy consumption strategy after the order is terminated.

[0039] Example 2: On the basis of the above embodiments, a frequency-band adaptive filtering architecture is proposed to address the problem of geomagnetic signals being interfered with by environmental noise.

[0040] The described architecture decomposes the magnetic field signal into three characteristic frequency bands: Low frequency band (0-5Hz): temperature drift, mechanical vibration noise, Kalman predictive filtering; Power frequency band (48-52Hz): Power grid, elevator electromagnetic interference, adaptive notch filtering; Vehicle characteristic band (10-30Hz): Metal body disturbance, bandpass enhancement.

[0041] The effective signal is determined by the dynamic energy ratio threshold, the formula is:

[0042] Where, is the dynamic energy ratio threshold; is the vehicle band energy; is the noise band energy; is the temperature compensation coefficient.

[0043] when Vehicle events are triggered when the vehicle is in the correct state, avoiding misjudgment caused by fixed thresholds.

[0044] The geomagnetic sensor integrates three parallel ADC sampling channels; The low-frequency noise suppression algorithm is:

[0045] Where, for The optimal estimate of the state at that moment; is the state transfer matrix; for Estimated state value at the moment; is the Kalman gain matrix; for The actual value measured by the sensor at each moment; is the observation matrix.

[0046] The power frequency notch formula is:

[0047] Where, for Time filter output; for Input signal at all times; is the notch center frequency; At discrete time points The original magnetic field signal sampling value; For the moment.

[0048] Verification showed that while achieving a similar average error as the above-mentioned embodiment, the false alarm rate dropped from 7.2% to 0.5%, and the impact of temperature drift was reduced by 98%. The results demonstrate that this mechanism completely eliminates false triggering caused by power-frequency electromagnetic interference and low-frequency mechanical vibration, achieving industrial-grade reliability standards for geomagnetic signal output stability. It also maintains vehicle magnetic field feature extraction accuracy in extreme temperature scenarios, overcoming signal attenuation caused by thermal drift in traditional solutions. The frequency band energy ratio threshold dynamically regulates sampling power consumption, enabling the geomagnetic sensor to enter near-zero power consumption mode even when the vehicle is not present.

[0049] Example 3: On the basis of the aforementioned embodiments, in order to solve the problems of data loss and time sequence disorder in a weak network environment, an event chain storage conflict self-healing mechanism is constructed based on an ordered event chain of cryptographic anchor points.

[0050] Each event contains a triple of state, timestamp, and hash anchor; The hash anchor is generated by encrypting the content of the previous event:

[0051] Where, Hash anchor for the current event; It is the state of the previous event; The timestamp of the previous event; Hash anchor for the previous event.

[0052] Identify conflicts by detecting relative time difference mutations:

[0053] Where, is the time difference variation; The timestamp of the current event; Timestamp of the previous event.

[0054] When both satisfy and The self-healing process is triggered.

[0055] The storage structure is: Initial time ; Subsequent events .

[0056] For example, the sequence of events is: ; ; ; Receive conflict in weak network environment: .

[0057] Time difference change: ; Hash Verification: expected ; Actual reception ; Trigger condition judgment: ; Only exceptions are logged and self-healing is not triggered.

[0058] The effect of the event chain storage conflict self-healing mechanism is shown in Table 1.

[0059] Table 1. Summary of the effects of the event chain storage conflict self-healing mechanism Test scenario Traditional solution Event chain storage conflict self-healing mechanism Effect Single-event hash error Order loss rate: 18.7% Order loss rate 0.2% Reduced by 99% Continuous timestamp transitions Data confusion rate 42.3% The self-healing success rate is 98.5%. Correction efficiency increased by 36 times Weak network data packets out of order Manual intervention frequency: 3.2 times / day Automatic repair rate 100% Zero manual intervention Malicious clock tampering The evasion rate is 12.1% Attack interception rate 99.9% Economic benefits increased by 22% As shown in the experimental table, the dual-condition trigger mechanism prevents false positives from single anomalies, geomagnetic resampling and calibration time is less than 200ms, and the chain structure ensures that events cannot be tampered with. This mechanism's hash anchor chain association ensures absolute ordering of events, eliminating the chronic problem of packet out-of-order and loss in weak network environments. Dual-factor conflict detection accurately identifies malicious tampering and device failures, and the self-healing process automatically restores data consistency. A multi-level self-healing strategy eliminates manual on-site intervention, ensuring a maintenance-free system throughout its lifecycle.

[0060] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media containing computer-usable program code.

[0061] The present invention can provide computer program instructions to a management platform of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the management platform of the computer or other programmable data processing device produce a device for implementing the system.

[0062] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device that implements the functions of the system.

[0063] These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions of the described system.

Claims

1. An automated order management system based on geomagnetic detection, characterized in that: include: Anti-interference geomagnetic sensor unit, used to output a stable vehicle presence status signal through environmental magnetic field disturbance suppression technology; A multi-source collaborative arbitration engine is used to integrate geomagnetic state signals with the spatiotemporal coordinate data of video inspection equipment, triggering order lifecycle operations only when the dual verification is consistent; Distributed fault-tolerant processing unit, used to initiate a multimodal review process for data conflict events and freeze abnormal orders; Edge data chain storage unit, used to generate tamper-proof data chains according to event time sequence in weak network environments; The event chain storage conflict self-healing unit is used to trigger the self-healing process through the dual-factor condition of relative time difference mutation and anchor point verification; The spectrum layered dynamic filtering unit is used to process the magnetic field signal by dividing the frequency bands and determine the valid vehicle events based on the dynamic energy ratio threshold.

2. The system according to claim 1, wherein: The anti-interference geomagnetic sensing unit integrates a dynamic noise suppression function, which separates low-frequency environmental disturbances from vehicle magnetic field characteristics and suppresses power-frequency electromagnetic interference to output a stable signal that meets a preset signal-to-noise ratio threshold.

3. The system according to claim 1, wherein: The multi-source collaborative arbitration engine performs hierarchical verification, including time window matching of geomagnetic events and video recognition events, spatial consistency verification of video coordinates and target parking space geofences, and a statistical anomaly detection model built based on historical behavioral data. It automatically marks risks and freezes orders that deviate from the normal distribution.

4. The system according to claim 1, wherein: The distributed fault-tolerant processing unit activates a multimodal review process when arbitration fails, including controlling the video device to recapture the target parking space image and calling the geomagnetic sensor cross-verification status of the adjacent parking space; If arbitration is still not possible, the order will be frozen and the sound and light will be activated to guide the car owner to actively confirm.

5. The system according to claim 1, wherein: The chain nodes of the data chain contain state hash values ​​to implement integrity verification of offline data.

6. The system according to claim 5, characterized in that: The edge data chain storage unit is provided with a conflict self-healing mechanism. When the hash verification fails, it applies for cloud data synchronization and triggers the adaptive calibration of the geomagnetic sensor parameters.

7. The system according to claim 1, wherein: The system is connected to a dynamic charging policy executor, which matches regional rate rules based on the spatiotemporal attributes of orders.

8. The system according to claim 1, wherein: The spectrum layered dynamic filtering unit determines the effective signal through the dynamic energy ratio threshold, the formula is: Where, is the dynamic energy ratio threshold; is the vehicle band energy; is the noise band energy; is the temperature compensation coefficient.

9. The system according to claim 1, wherein: It also includes an energy consumption adaptive scheduling module that dynamically switches the sampling frequency according to the geomagnetic state and enters an ultra-low power consumption mode after the vehicle leaves.

10. An automated order management method based on geomagnetic detection, characterized by: The method is implemented based on the system according to any one of claims 1 to 9: The method comprises: The original magnetic field signal is collected by the geomagnetic sensor, decomposed into three characteristic frequency bands, and the dynamic energy ratio of the vehicle frequency band energy to the noise frequency band energy is calculated to generate vehicle events; Receive geomagnetic vehicle events and license plate coordinates and timestamps reported by video inspection equipment, perform three-level hierarchical verification, and create or terminate parking orders only when the three-level verification is consistent; In a weak network environment, an event chain structure is constructed in time sequence, and the sudden change in the time difference between adjacent events is monitored in real time. When the conditions are met, a self-healing process is triggered, which includes discarding conflicting events, synchronizing the previous authoritative data with the cloud, resampling and calibrating the geomagnetic field, and reconstructing the event chain. The sampling frequency is dynamically adjusted based on the vehicle presence status obtained through real-time geomagnetic feedback, and the energy consumption strategy is updated synchronously after the order is terminated.

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