Parking inspection equipment with positioning and deviation rectifying functions

Abstract

The invention discloses parking space inspection equipment with positioning and deviation correcting functions, and the equipment comprises a parking space state collection module which periodically shoots the images of parking spaces in a parking lot; the data fusion and preliminary analysis module is responsible for fusing geomagnetic sensor data and camera images; the parking optimization and path recommendation module is used for recommending the optimal parking position and path; the abnormal condition detection and alarm module is used for sending alarm information to the management system through the wireless communication module; and the data recording and statistical analysis module is used for recording parking data of each vehicle and generating a parking space use report. Through the integrated system design, efficient cooperation of parking space state detection, parking optimization and abnormity monitoring is achieved. Cooperative work of the camera and the geomagnetic sensor ensures accuracy and real-time performance of parking space state detection, and by combining a target detection algorithm and a multi-source data fusion technology, misjudgment and missing detection are effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent parking management, and specifically relates to a working method of a berth detection and inspection device based on a traffic-saving design. The efficient detection of the berth state is realized through the collaborative work of a geomagnetic sensor and a camera. Combining the inspection mode, positioning deviation correction and order error correction functions, the management efficiency of the parking lot and the stability of the equipment operation are improved. Background Art

[0002] With the acceleration of the urbanization process, the problem of parking difficulty has become increasingly prominent. The traditional parking lot management method relies on manual inspection and simple sensor detection, which has problems such as low efficiency, high cost and easy errors. Manual inspection not only consumes a large amount of manpower, but also easily leads to inaccurate data records due to human negligence, thus affecting the overall management efficiency of the parking lot. In addition, although the traditional sensor detection methods (such as geomagnetic sensors, ultrasonic sensors, etc.) can achieve automated management to a certain extent, independent sensors need to be installed for each parking space, resulting in high construction costs, difficult maintenance, and relatively serious damage to the road.

[0003] Although the existing intelligent parking management systems have improved the management efficiency to a certain extent, there are still many deficiencies in data collection, processing, analysis and equipment maintenance. For example, the existing systems usually rely on a single type of sensor or camera for data collection, and it is difficult to comprehensively and accurately reflect the real-time state of the parking spaces. Especially in a complex parking lot environment, the limitations of a single sensor are more obvious, and misjudgment or missed detection is likely to occur. In addition, the existing systems often lack efficient algorithm support in data processing and analysis, resulting in slow data processing speed and inaccurate analysis results, and it is difficult to meet the needs of real-time management. Low utilization rate of parking spaces: In the traditional parking space management mode of parking lots, it is difficult to timely detect the idle state of parking spaces, resulting in vehicles frequently making unnecessary searches, leading to low parking efficiency. Especially during high-demand periods, the mobility of vehicles in the parking lot is poor, and the parking spaces cannot be effectively utilized. Imprecise parking path planning: The traditional parking management system usually cannot real-time feedback the relationship between the current position of the vehicle and the parking space, resulting in imprecise parking path planning, which in turn increases the parking time of the driver and wastes the resources of the vehicle owner and the parking lot. Summary of the Invention

[0004] The purpose of the present invention is to provide a working method of a berth detection and inspection device based on a traffic-saving design. Through the collaborative work of a geomagnetic sensor and a camera, combining the inspection mode, positioning deviation correction and order error correction functions, the management efficiency of the parking lot and the stability of the equipment operation are improved. The present invention adopts the following technical solutions:

[0005] A berth inspection device with positioning and deviation correction capabilities. This device improves the efficiency of parking space management through the collaborative work of multiple modules, including: a parking space status acquisition module that periodically captures images of parking spaces in the parking lot and detects changes in the magnetic field of the parking spaces through a geomagnetic sensor to determine whether the parking spaces are occupied; a data fusion and preliminary analysis module that is responsible for fusing the geomagnetic sensor data and camera images, performing precise identification through object detection algorithms, determining the occupancy status of the parking spaces, and generating a berth map; a parking optimization and route recommendation module that calculates the optimal parking route and berth allocation strategy based on the real-time berth map, vehicle flow, and driver's requirements, and recommends the best parking position and route; and an abnormal situation detection and alarm module that sends alarm information to the management system through a wireless communication module and displays abnormal situations on the monitoring interface; a data recording and statistical analysis module that is used to record the parking data of each vehicle, perform statistical analysis based on historical data, generate a parking space usage report, and help the parking lot operator optimize the charging strategy and improve the utilization rate of parking spaces.

[0006] A positioning and deviation correction method applied to the above-mentioned berth inspection device with positioning and deviation correction capabilities, characterized in that: the method includes the following steps:

[0007] Step S1: Real-time acquisition of parking space status. The device acquires real-time status data of parking spaces in the parking lot through an integrated camera and geomagnetic sensor. Step S2: Data fusion and preliminary analysis. The acquired parking space images and the data of the geomagnetic sensor are fused and analyzed through a processing unit. Step S3: Parking optimization and route recommendation. The processing unit calculates the optimal parking route and berth allocation strategy using an optimization algorithm based on the real-time berth map and the vehicle flow situation in the parking lot. Step S4: Abnormal situation detection and alarm. The device monitors abnormal situations in the parking lot in real time, including vehicles not parking in the designated berths and berths being occupied by obstacles. Step S5: Data recording and statistical analysis. The parking data of each vehicle is stored in a local or cloud database, and the utilization rate of parking spaces at different time periods is analyzed based on historical data to generate a detailed parking space usage report. Step S6: Device health monitoring and remote maintenance. Regularly detect the working status of the camera, geomagnetic sensor, and wireless communication module, and automatically attempt to recover or generate a fault report when an abnormality is found.

[0008] Through an integrated system design, the device of the present invention realizes the efficient coordination of parking space status detection, parking optimization, and abnormal monitoring. The collaborative work of cameras and geomagnetic sensors ensures the accuracy and real-time nature of parking space status detection. Combining object detection algorithms and multi-source data fusion technologies effectively reduces misjudgments and missed detections. At the same time, the device monitors abnormal situations (such as illegal parking and obstacle occupancy) in real time, confirms the abnormality through image recognition and data analysis, and sends alarm information to the management system, supporting a hierarchical alarm mechanism to ensure the safe operation of the parking lot.

[0009] Preferably, the camera periodically captures images covering multiple parking spaces, and the geomagnetic sensor detects changes in the magnetic field of the parking space. The two are combined to determine whether the parking space is occupied. The images collected by the camera are processed by an object detection algorithm to accurately identify the vehicle position and status, mark the free and occupied parking space status, and generate a parking space map.

[0010] Furthermore, when an abnormality is detected, the alarm information is sent to the management system through the wireless communication module, and the abnormal situation is displayed in real time on the monitoring interface of the management center to prompt the staff to handle it in a timely manner. Based on historical data analysis of the parking space utilization rate at different times, a detailed parking space usage report is generated, including the usage of parking spaces during peak and off-peak hours, providing a basis for the parking lot operator to optimize the charging strategy and improve the parking space utilization rate.

[0011] Preferably, for the data fusion: the image data collected by the camera and the detection data of the geomagnetic sensor are fused and processed. The geomagnetic sensor data G i is used to quickly screen potential occupied parking spaces; G i = f(P i ) = P i · geomagnetic sensor reading where the function f(P i ) will be dynamically updated based on the parking space status P i and the sensor data. The purpose of this step is to screen out potentially occupied parking spaces and reduce the computational workload of subsequent image processing. Process the images collected by the camera, use an object detection algorithm to identify the status of the parking space, and set the function of the parking space position and status in the image: S(P i ) = YOLO model recognition(I i ), i = 1, 2,..., N where I i is the image input data of the i-th parking space, and the function S(P i ) is used to return the status of the parking space. Each parking space in the image is marked and classified according to the object recognized by the model; Set the objective function, with the objective value being the minimization. The goal is the optimization strategy for the parking path and parking space allocation. This value range represents the comprehensive cost of the entire optimization problem, and the minimum value represents the optimal parking path and parking space allocation strategy. The calculation formula of the objective function is as follows: Among them, D i represents the distance between the i-th parking space and the parking lot exit or charging pile; T i represents the time required to park at the i-th parking space, and this time is related to the traffic flow and the status of the parking space; L i represents the size of the parking space; S represents the size requirement of the vehicle, and α, β, γ are all adjustment factors corresponding to each item, controlling the weights of various factors in the optimization process; the exponential decay term e -λV : As the traffic flow V increases, the system's optimization requirement for the parking path decreases, reflecting the inhibitory effect of traffic flow on path selection.

[0012] Advantages of the present invention: By real-time collecting the status of parking spaces and traffic flow data, combined with intelligent analysis and optimization algorithms for the status of parking spaces, it can accurately predict the available parking spaces in the parking lot and promptly inform the driver, thereby reducing the vehicle's search time in the parking lot and significantly improving the utilization efficiency of parking spaces. Optimize the parking path and parking space allocation: Based on the vehicle's current location, real-time traffic flow in the parking lot, and personalized needs (such as being close to the exit or charging pile, etc.), the present invention can recommend the optimal parking path and parking space allocation strategy, avoiding unnecessary detours by the driver and enhancing the parking efficiency and the owner's usage experience. Description of the Drawings

[0013] Figure 1 is the working flow chart of the device in the embodiment;

[0014] Figure 2 is the system module schematic diagram of the device in the embodiment. Detailed Embodiments

[0015] The technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0016] Embodiment 1. This embodiment provides a berth inspection device with positioning and deviation correction. This device improves the efficiency of parking space management through the collaborative work of multiple modules, including: a parking space status acquisition module, which periodically captures images of parking spaces in the parking lot and detects the magnetic field changes of the parking spaces through geomagnetic sensors to determine whether the parking spaces are occupied. It should be noted that the parking space status acquisition module includes two acquisition units, specifically a camera acquisition unit and a geomagnetic sensor acquisition unit. The geomagnetic sensor is installed under the parking space to detect magnetic field changes in real time and quickly determine the occupancy status of the parking space. The camera acquisition unit can be installed on the inspection vehicle for inspection shooting. It preferentially filters out the occupied parking spaces based on the data of the geomagnetic sensor, and then further confirms the specific position of the vehicle based on the images captured by the inspection vehicle.

[0017] This device also includes: a data fusion and preliminary analysis module, which is responsible for fusing the geomagnetic sensor data and the camera images, performing precise identification through target detection algorithms, determining the occupancy status of the parking spaces, and generating a berth map; a parking optimization and path recommendation module, which calculates the optimal parking route and berth allocation strategy according to the real-time berth map, vehicle flow, and the driver's needs, and recommends the best parking position and path; and an abnormal situation detection and alarm module, which sends alarm information to the management system through a wireless communication module and displays abnormal situations on the monitoring interface; a data recording and statistical analysis module, which is used to record the parking data of each vehicle, perform statistical analysis based on historical data, generate a parking space usage report, and help the parking lot operator optimize the charging strategy and improve the utilization rate of parking spaces. A working method of a berth detection and inspection device based on a traffic-saving design aims to achieve the efficient detection of berth status through the collaborative work of geomagnetic sensors and cameras, and improve the management efficiency of the parking lot and the stability of the device operation by combining the inspection mode, positioning and deviation correction, and order error correction functions.

[0018] A positioning and deviation correction method for a berth inspection device with positioning and deviation correction improves the efficiency of parking space management through the collaborative work of multiple modules. The specific steps are as follows: Step S1: Real-time acquisition of parking space status. The device acquires the real-time status data of parking spaces in the parking lot through the integrated camera and geomagnetic sensor. The camera periodically captures images covering multiple berths, and the geomagnetic sensor detects the magnetic field changes of the parking spaces. The two are combined to determine whether the parking spaces are occupied. The camera adopts an optimized low-power design to ensure clarity and shooting frequency, and minimize energy consumption on the premise of meeting actual needs, providing basic support for subsequent data analysis. Step S2: Data Fusion and Preliminary Analysis. The collected parking space images and the data from the geomagnetic sensors are fused and analyzed by the processing unit. The geomagnetic sensor data is used to quickly screen the parking spaces where vehicles may exist, reducing the amount of image processing calculations. Subsequently, the images captured by the camera are processed using an object detection algorithm (such as the YOLO model) to accurately identify the vehicle position and status, mark the free and occupied parking space status, and generate a berth map. Step S3: Parking Optimization and Route Recommendation. The processing unit calculates the optimal parking route and berth allocation strategy using an optimization algorithm based on the real-time berth map and the vehicle flow situation in the parking lot. Combining the vehicle size and parking requirements of the driver, it recommends the best parking position and route to the user to optimize the parking efficiency. Step S4: Abnormal Situation Detection and Alarm. The device monitors the abnormal situations in the parking lot in real time, including vehicles not parking in the designated berths and berths being occupied by obstacles. When an abnormality is detected, the alarm information is sent to the management system through the wireless communication module, and the abnormal situation is displayed in real time on the monitoring interface of the management center to prompt the staff to handle it in a timely manner. Step S5: Data Recording and Statistical Analysis. The system stores the parking data of each vehicle (such as license plate number, parking time, berth position) in a local or cloud database. Based on historical data analysis, the parking space utilization rate at different times is analyzed, and a detailed parking space usage report is generated, including the usage of parking spaces during peak and off-peak hours, providing a basis for the parking lot operator to optimize the charging strategy and improve the berth utilization rate. Step S6: Equipment Health Monitoring and Remote Maintenance. The device has a self-diagnosis function and can regularly detect the working status of the camera, geomagnetic sensor, and wireless communication module. When an abnormality is found, it will automatically try to recover or generate a fault report. The device also supports remote upgrade. When a software version update is detected, the device will automatically complete the upgrade during low-traffic periods to ensure it maintains the best operating state.

[0019] Regarding the above Step S1, the device works in cooperation with the integrated camera and geomagnetic sensor to collect the status data of the parking spaces in the parking lot in real time. The camera periodically captures images covering multiple berths at fixed time intervals, and adopts a low-power design to optimize energy consumption. At the same time, the monitoring blind spots are reduced by installing cameras at multiple angles.

[0020] The geomagnetic sensor is installed under the parking space, which can detect the magnetic field change in real time, quickly judge the occupancy status of the parking space, and features low power consumption and high stability. After the data of the camera and the geomagnetic sensor are synchronously collected, they are transmitted to the processing unit through the wireless communication module and preprocessed to reduce the data transmission volume. The geomagnetic sensor data is used to preliminarily screen the parking spaces where vehicles may exist, and the camera images are further used to verify the parking space status through the object detection algorithm, and finally determine whether the parking space is occupied. The collected data is temporarily stored in the local storage unit, and the important data is uploaded to the cloud for backup to ensure data security and traceability. Through this step, the device can efficiently and accurately collect the parking space status data in real time, provide reliable support for subsequent processing, and at the same time, the low power consumption and traffic-saving design ensure the long-term stable operation of the device.

[0021] Specifically, the camera can also be installed on the inspection vehicle for inspection and shooting. By combining the joint determination of image recognition and geomagnetic induction information, the occupied parking spaces are filtered out preferentially according to the data of the geomagnetic sensor, and then the specific position of the vehicle is further confirmed based on image recognition. If the position of the vehicle in the image deviates from the geomagnetic induction data, the relative position between the parking spaces is used to judge which parking space the vehicle in the image matches. For example, a position tolerance range is set. When the inspection vehicle captures a vehicle, if the relative position of the parking space is within the set tolerance range and the geomagnetic sensor reports that there is a vehicle in the adjacent parking space, the vehicle can be marked as being in the correct parking space.

[0022] For the above step S2, the device fuses and preliminarily analyzes the collected parking space images and geomagnetic sensor data to accurately judge the parking space status. The geomagnetic sensor data is used to quickly screen the parking spaces where vehicles may exist, reducing the computational amount of image processing, while the camera images accurately identify the vehicle position and status through the object detection algorithm (such as the YOLO model) to verify the preliminary judgment of the geomagnetic sensor. The device adopts a multi-source data fusion algorithm to comprehensively analyze the geomagnetic sensor and image data, eliminate the possibility of misjudgment, and generate a real-time berth map, clearly marking the occupancy status of each parking space and vehicle information. At the same time, the device conducts simple statistical analysis on the parking space status data, such as calculating the number of available parking spaces and the occupancy rate, providing real-time reference for the operation and management of the parking lot. Through this step, the device can efficiently and accurately judge the parking space status, provide reliable data support for subsequent parking optimization, path recommendation and anomaly detection, and at the same time reduce the possibility of misjudgment and missed detection.

[0023] For the above step S3, specifically, it includes:

[0024] S301: Set the parking space status variable P i , where i = 1, 2,..., N, representing the status of the i-th parking space in the parking lot: Data fusion: The image data collected by the camera is fused with the detection data of the geomagnetic sensor. i Used to quickly screen potentially occupied parking spaces; G i =f(P i )=P i · Geomagnetic sensor readings Among them, the function f(P i ) will be based on the parking space status P i The sensor data is dynamically updated. The purpose of this step is to filter out the parking spaces that may be occupied and reduce the amount of computation for subsequent image processing. S302: Process the image captured by the camera and use the target detection algorithm to identify the status of the parking space (free or occupied). Set the function of the parking space position and status in the image: S(P i )=YOLO model recognition(I i ), i=1,2,...,N Among them, I i is the image input data of the i-th parking space, function S(P i ) is used to return the status of the parking space (occupied / free). Each parking space in the image is labeled and classified according to the objects recognized by the model. S303: Set the objective function, taking into account factors such as the distance to the parking space, flow rate, and parking demand. First, define the characteristics of each parking space: D i Represents the distance between the i-th parking space and the parking lot exit or charging pile. T i It represents the time required to park at the i-th parking space, which is related to the traffic flow and parking space status. L i Indicates the dimensions of the parking space (such as width and length). S represents the vehicle size requirements (such as vehicle length, vehicle width, etc.). The specific formula is as follows: The first term α·D i : A weighted combination of the distance to the parking space and the parking space occupancy. A distant and occupied parking space is not conducive to the optimization of path selection. The second term β·T i : Weighted parking time. Long-term parking will affect traffic flow and parking space utilization efficiency. The third item The impact of parking space size. The smaller the parking space, the more difficult it is to park the vehicle. α, β, and γ are adjustment factors for each item, which control the weight of each factor in the optimization process. Exponential decay term e -λV:As the traffic volume V increases, the system's optimization requirement for the parking path decreases, reflecting the inhibitory effect of traffic volume on path selection.

[0025] Regarding the above-mentioned step S4, the device monitors the abnormal situations in the parking lot in real time to ensure the normal operation of the parking lot and the safe parking of vehicles. The device detects possible abnormal situations through the collaborative work of cameras and geomagnetic sensors, such as vehicles not parking in the designated berths, berths being occupied by obstacles, vehicles occupying a parking space for a long time without moving, etc. When an abnormality is detected, the device further confirms the type and severity of the abnormality through image recognition and data analysis. For example, if the camera finds that a certain parking space is occupied by an obstacle, the device combines the data of the geomagnetic sensor to judge whether it is a false alarm, and analyzes the usage of this parking space through historical data to confirm whether it is a long-term occupation or a temporary parking. Once the abnormality is confirmed, the device sends an alarm message to the parking lot management system through the wireless communication module, and the specific location and type of the abnormal situation are displayed in real time on the monitoring interface of the management center, prompting the staff to handle it in time. The alarm message includes the number of the abnormal parking space, the type of abnormality (such as illegal parking, obstacle occupation, etc.) and the recommended handling measures. In addition, the device also supports a hierarchical alarm mechanism, and different handling methods are adopted according to the severity of the abnormality. For example, minor abnormalities are only logged, while serious abnormalities immediately notify the management staff and trigger an audible and visual alarm. Through this step, the device can effectively improve the supervision efficiency of the parking lot, reduce management chaos and potential safety hazards caused by abnormal situations.

[0026] Regarding the above-mentioned step S5, the device systematically records and statistically analyzes the parking data in the parking lot to provide data support for the operation and management of the parking lot. The device stores the parking data of each vehicle (such as license plate number, parking time, berth location, parking duration, etc.) in a local or cloud database to ensure the integrity and traceability of the data. Based on these data, the device can generate detailed parking space usage reports, including the utilization rate of parking spaces at different times, the usage of parking spaces during peak and off-peak hours, the average parking duration of vehicles, etc. For example, the device can analyze the peak parking hours of each day, the most popular parking space areas, and the long-term idle parking spaces, helping the operator optimize the parking space allocation and charging strategy. In addition, the device also supports the statistical analysis of abnormal parking behaviors, such as the number of illegal parking times, the vehicle information of vehicles occupying a parking space for a long time, etc., providing a basis for management decisions. The device can also predict future parking demands by combining historical data, helping the parking lot make early resource allocation and planning. Through data visualization tools, the device displays the analysis results in the form of charts or reports, facilitating the management staff to intuitively understand the operation status of the parking lot. Through this step, the device not only improves the management efficiency of the parking lot, but also provides scientific data support for the operator, contributing to the intelligent upgrade and sustainable development of the parking lot.

[0027] In this embodiment, by integrating multiple innovative functions such as positioning and deviation correction technology, traffic-saving berth detection and inspection, etc., a set of intelligent and high-performance berth inspection equipment is created, realizing the full-process optimization from real-time monitoring of parking space status, accurate positioning of abnormal situations to self-diagnosis of equipment health, greatly improving the management efficiency of the parking lot and the stability of equipment operation, and having broad application prospects and promotion value.

[0028] Although this embodiment focuses on the parking lot scenario, the relevant technical principles and architectures can be extended to large vehicle parking and management places such as logistics parks, port terminals, etc. through adaptive adjustment. Through customized development, the equipment can meet the special needs of different fields. For example, it can realize vehicle scheduling management in the cargo loading and unloading area of the logistics park, or optimize the parking and path planning of container transport vehicles in the port terminal, further expanding the application boundary of the technology.

Claims

1. A berth inspection device with positioning and deviation correction, characterized in that: The device improves parking space management efficiency through the collaborative work of multiple modules, including: a parking space status acquisition module that periodically captures images of parking spaces in the parking lot and uses geomagnetic sensors to detect changes in the magnetic field of the parking spaces to determine whether the parking spaces are occupied; The data fusion and preliminary analysis module is responsible for fusing geomagnetic sensor data and camera images, accurately identifying the parking space through the target detection algorithm, determining the occupancy status of the parking space, and generating a parking map. The parking optimization and route recommendation module calculates the optimal parking route and parking allocation strategy based on the real-time parking map, vehicle flow, and driver needs, and recommends the best parking location and route; As well as the abnormal situation detection and alarm module, which sends alarm information to the management system through the wireless communication module and displays abnormal situations on the monitoring interface; the data recording and statistical analysis module is used to record the parking data of each vehicle, perform statistical analysis based on historical data, and generate parking space usage reports to help parking lot operators optimize charging strategies and improve parking space utilization.

2. A positioning and deviation correction method for a berth inspection device with positioning and deviation correction as described in claim 1, characterized in that: The method comprises the following steps: Step S1: Real-time acquisition of parking space status. The device collects real-time status data of parking spaces in the parking lot through integrated cameras and geomagnetic sensors. Step S2: Data fusion and preliminary analysis: the collected parking space image and the data of the geomagnetic sensor are fused and analyzed by the processing unit. Step S3: Parking optimization and route recommendation: the processing unit uses an optimization algorithm to calculate the optimal parking route and parking allocation strategy based on the real-time parking map and parking lot vehicle flow conditions. Step S4: abnormal situation detection and alarm, the equipment monitors abnormal situations in the parking lot in real time, including vehicles not parking at designated parking spaces and parking spaces being occupied by obstacles. Step S5: Data recording and statistical analysis: the parking data of each vehicle is stored in a local or cloud database, and the parking space utilization rate in different time periods is analyzed based on historical data to generate a detailed parking space usage report. Step S6: Equipment health monitoring and remote maintenance: regularly check the working status of the camera, geomagnetic sensor and wireless communication module, and automatically try to recover or generate a fault report when an abnormality is found.

3. A positioning and deviation correction method for berth inspection equipment with positioning and deviation correction according to claim 2, characterized in that: In step S1, the camera periodically captures images covering multiple parking spaces, and the geomagnetic sensor detects changes in the magnetic field of the parking spaces. The two are combined to determine whether the parking spaces are occupied. The images captured by the camera are processed by a target detection algorithm to accurately identify the position and status of the vehicle, mark the idle and occupied parking spaces, and generate a parking map.

4. A positioning and deviation correction method for berth inspection equipment with positioning and deviation correction according to claim 3, characterized in that: When an abnormality is detected, the alarm information is sent to the management system through the wireless communication module, and the abnormal situation is displayed in real time on the monitoring interface of the management center, prompting the staff to deal with it in time.

5. A positioning and deviation correction method for berth inspection equipment with positioning and deviation correction according to claim 4, characterized in that: Based on historical data, the parking space utilization rate in different time periods is analyzed to generate detailed parking space utilization reports, including the usage of parking spaces during peak hours and off-peak hours, providing parking lot operators with a basis for optimizing charging strategies and improving parking space utilization rates.

6. A positioning and deviation correction method for berth inspection equipment with positioning and deviation correction according to claim 5, characterized in that: Data fusion: The image data collected by the camera is fused with the detection data of the geomagnetic sensor. i Used to quickly screen potentially occupied parking spaces; G i =f(P i )=P i · Geomagnetic sensor readings Among them, the function f(P i ) will be based on the parking space status P i and sensor data are dynamically updated. The purpose of this step is to filter out parking spaces that may be occupied and reduce the computational complexity of subsequent image processing.

7. A positioning and deviation correction method for berth inspection equipment with positioning and deviation correction according to claim 6, characterized in that: The optimization algorithm specifically includes: Process the image captured by the camera, use the target detection algorithm to identify the status of the parking space, and set the function of the parking space position and status in the image: S(P i )=YOLO model recognition(I i ), i=1,2,...,N Among them, I i is the image input data of the i-th parking space, function S(P i ) is used to return the status of the parking space. Each parking space in the image is marked and classified according to the target recognized by the model; Set the objective function, the objective value is to minimize the optimization strategy of parking path and parking space allocation. This value range represents the comprehensive cost of the entire optimization problem, and the minimum value represents the optimal parking path and parking space allocation strategy.

8. A positioning and deviation correction method for berth inspection equipment with positioning and deviation correction according to claim 6, characterized in that: The calculation formula of the objective function is: Among them, D i represents the distance between the i-th parking space and the parking lot exit or charging pile; T i represents the time required to park at the i-th parking space, which is related to the flow rate and parking space status; L i indicates the size of the parking space; S represents the size requirement of the vehicle; α, β, and γ are adjustment factors corresponding to each item, which control the weight of each factor in the optimization process; the exponential decay term e -λV : As the traffic volume V increases, the system's demand for optimizing parking paths decreases, reflecting the inhibitory effect of traffic volume on path selection.

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