Unmanned parking lot management system and method based on big data

Abstract

The invention discloses an unmanned parking lot management system and method based on big data, and the system comprises an access management unit which is used for recording the information of vehicles entering and exiting a parking lot, and the information of the vehicles comprises license plate information; the distribution unit is used for distributing a parking space for the vehicle entering the parking lot based on the unique number of each parking space so as to determine the parking space number of the vehicle, and binding the parking space number with a license plate; the parking space management unit is used for identifying license plate information and controlling opening and closing of parking spaces; under the condition that the recognized license plate information is consistent with the license plate information bound with the number of the parking space entering the parking space, the parking space is controlled to be opened; the user interaction unit is used for receiving target shop information input by a user and sending the target shop information to the distribution unit, so that the distribution unit distributes parking spaces in an area closer to a target shop for a vehicle; the exit guiding unit is used for providing exit guidance for the vehicle in real time according to the road condition of the road around the parking lot.

Description

Technical Field

[0001] The present application relates to the field of smart parking technology, and in particular to an unmanned parking lot management system and method based on big data. Background Art

[0002] With the acceleration of urbanization and the surge in the number of cars, urban parking problems have become increasingly prominent. Traditional parking lot management methods have many shortcomings, such as low parking efficiency, unreasonable parking space allocation, poor user experience, frequent safety issues, and low resource utilization. These problems not only increase urban traffic congestion, but also affect the daily life and work efficiency of citizens. Therefore, there is an urgent need for a new type of parking lot management system to improve parking efficiency, optimize resource allocation, improve user experience, and enhance safety. Such a system needs to be able to process a large amount of parking data, realize intelligent allocation of parking spaces, and provide real-time traffic guidance and safety monitoring to meet the needs of modern urban development. Summary of the invention

[0003] In view of this, the embodiments of the present application provide an unmanned parking lot management system and method based on big data, which helps to improve the operating efficiency of the parking lot, reduce the time users spend looking for parking spaces, and enhance the parking experience; optimize parking space allocation and exit guidance strategies through big data analysis and machine learning; realize intelligent management, reduce labor costs, and improve overall service quality and user satisfaction.

[0004] According to one aspect of the present application, there is provided an unmanned parking lot management system based on big data, comprising:

[0005] A parking space information input unit, used to input and store information of each parking space in the parking lot;

[0006] a numbering unit, connected to the parking space information input unit, for assigning a unique number to each parking space;

[0007] An entry and exit management unit, used to record information about vehicles entering and leaving the parking lot, the vehicle information including license plate information;

[0008] an allocating unit connected to the numbering unit, for allocating parking spaces for vehicles entering the parking lot based on the unique number of each parking space, so as to determine the parking space number of the vehicle, and to bind the parking space number to the license plate;

[0009] A parking space management unit is connected to the allocation unit and is used to identify the license plate information and control the opening and closing of the parking space; wherein, when a vehicle enters the parking space, the license plate information of the vehicle is identified, and when the identified license plate information is consistent with the license plate information bound to the parking space number of the vehicle entering the parking space, the parking space is controlled to be opened;

[0010] A user interaction unit connected to the allocation unit, configured to receive target store information input by a user, and send the target store information to the allocation unit, so that the allocation unit allocates a parking space in an area closer to the target store to the vehicle;

[0011] The exit guidance unit is used to provide exit guidance to vehicles in real time according to the road conditions around the parking lot;

[0012] The big data processing unit is used to clean, integrate and analyze parking lot data, provide fast and efficient data processing capabilities, support complex data analysis and machine learning tasks, and provide a data basis for the allocation unit and the exit guidance unit.

[0013] According to another aspect of the present application, a method for managing an unmanned parking lot based on big data is provided, which is applied to the above-mentioned unmanned parking lot management system based on big data, and the method includes:

[0014] The parking space information input unit inputs and stores the information of each parking space in the parking lot;

[0015] The numbering unit assigns a unique number to each parking space;

[0016] The entry and exit management unit records the information of vehicles entering and leaving the parking lot, wherein the vehicle information includes license plate information;

[0017] The user interaction unit receives the target store information input by the user, and sends the target store information to the allocation unit, so that the allocation unit allocates a parking space in an area close to the target store to the vehicle;

[0018] The allocating unit allocates a parking space to a vehicle entering the parking lot based on the unique number of each parking space to determine the parking space number of the vehicle and binds the parking space number to the license plate;

[0019] The parking space management unit identifies the license plate information and controls the opening and closing of the parking space; when a vehicle enters the parking space, the license plate information of the vehicle is identified, and when the identified license plate information is consistent with the license plate information bound to the parking space number of the vehicle entering the parking space, the parking space is controlled to be opened;

[0020] The exit guidance unit provides real-time exit guidance to vehicles based on the road conditions around the parking lot.

[0021] According to another aspect of the present application, a storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned unmanned parking lot management method based on big data is implemented.

[0022] According to another aspect of the present application, a computer device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the above-mentioned unmanned parking lot management method based on big data when executing the program.

[0023] By means of the above technical solution, an unmanned parking lot management system and method based on big data is provided in the embodiment of the present application. The unmanned parking lot management system based on big data integrates functional units such as parking space information entry, numbering, entry and exit management, allocation, parking space management, user interaction, exit guidance and big data processing. The system realizes the linkage between license plate recognition and parking space control by entering parking space information, allocating unique numbers, recording vehicle information and intelligently allocating parking spaces; at the same time, the system allocates nearby parking spaces according to the user's target store information, provides exit guidance in real time based on road conditions, and relies on the big data processing unit to provide efficient data processing and analysis capabilities to support complex tasks. The embodiment of the present application helps to improve the efficiency of parking lot operations, reduce the time users spend looking for parking spaces, and enhance the parking experience; optimize parking space allocation and exit guidance strategies through big data analysis and machine learning; realize intelligent management, reduce labor costs, and improve overall service quality and user satisfaction.

[0024] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0026] Figure 1 A schematic diagram of the structure of an unmanned parking lot management system based on big data provided in an embodiment of the present application is shown;

[0027] Figure 2 A schematic diagram of the structure of another unmanned parking lot management system based on big data provided in an embodiment of the present application is shown;

[0028] Figure 3 A schematic diagram of the structure of another unmanned parking lot management system based on big data provided in an embodiment of the present application is shown;

[0029] Figure 4 A structural schematic diagram of another unmanned parking lot management system based on big data provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0030] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0031] In this embodiment, an unmanned parking lot management system based on big data is provided. Figure 1 As shown, the system includes:

[0032] A parking space information entry unit is used to enter and store information about each parking space in the parking lot; a numbering unit is connected to the parking space information entry unit and is used to assign a unique number to each parking space; an entry and exit management unit is used to record information about vehicles entering and exiting the parking lot, wherein the vehicle information includes license plate information; an allocation unit is connected to the numbering unit and is used to allocate a parking space to a vehicle entering the parking lot based on the unique number of each parking space, so as to determine the parking space number of the vehicle and bind the parking space number to the license plate; a parking space management unit is connected to the allocation unit and is used to identify the license plate information and control the opening and closing of the parking space; wherein, when a vehicle enters a parking space, the license plate information of the vehicle is identified and When the recognized license plate information is consistent with the license plate information bound to the parking space number of the entered parking space, the parking space is controlled to be opened; the user interaction unit is connected to the allocation unit, and is used to receive the target store information input by the user, and send the target store information to the allocation unit, so that the allocation unit can allocate a parking space in an area closer to the target store to the vehicle; the exit guidance unit is used to provide exit guidance to the vehicle in real time according to the road conditions of the roads around the parking lot; the big data processing unit is used to clean, integrate and analyze the parking lot data, provide fast and efficient data processing capabilities, support complex data analysis and machine learning tasks, and provide a data basis for the allocation unit and the exit guidance unit.

[0033] The unmanned parking lot management system based on big data provided in the embodiment of the present application not only realizes the automation and intelligence of parking lot management, but also improves the utilization rate of parking spaces, parking efficiency and user experience through the application of big data technology. The parking space information entry unit enters and stores detailed information of each parking space in the parking lot, including but not limited to the location, type (such as ordinary parking spaces, barrier-free parking spaces, charging parking spaces, etc.), size and whether it is equipped with specific facilities (such as charging piles, awnings, etc.) of the parking space. This information provides a data basis for subsequent parking space allocation, user query and parking lot management. The numbering unit is connected to the parking space information entry unit, and the numbering unit assigns a unique number to each parking space. This number is not only convenient for internal management of the system, but also can be clearly displayed on the user interface to help users quickly find the target parking space. The entry and exit management unit is responsible for recording the information of vehicles entering and leaving the parking lot, including license plate information, entry and exit time and vehicle type. Through license plate recognition technology, the system can automatically identify and record vehicle information without manual intervention, greatly improving the traffic efficiency of the entrance and exit of the parking lot. The allocation unit is the core part of the system. It allocates parking spaces to vehicles entering the parking lot based on the unique number of each parking space. During the allocation process, the system will comprehensively consider the real-time parking demand, parking space resources and the target store information entered by the user, and adopt a dynamic parking space allocation algorithm to ensure the efficient use of parking spaces and guide vehicles to parking spaces closer to the target stores as much as possible. After the allocation is completed, the system will bind the parking space number with the license plate information to provide a basis for subsequent parking space management and user inquiries. The parking space management unit realizes intelligent management of parking spaces through license plate recognition technology and parking space locks and other equipment. When a vehicle enters a parking space, the parking space management unit will identify the vehicle's license plate information and compare it with the license plate information bound to the system. If they are consistent, the parking space lock will be controlled to open and allow the vehicle to park; if they are inconsistent, the parking space lock will remain closed to prevent unauthorized vehicles from parking. In addition, the parking space management unit can also monitor the parking space status in real time and transmit the status information to the system server to provide data support for subsequent parking space allocation and scheduling. The user interaction unit provides a rich user interface and interactive functions to facilitate users to query currently available parking spaces, reserve parking spaces, reserve destination parking spaces, and pay parking fees by themselves. Users can easily obtain the required information and complete related operations through mobile phone APP, self-service terminals or signboards in the parking lot. In addition, users can also enter the target store information so that the system can assign them a parking space closer to the target store, further improving the user experience. The exit guidance unit provides real-time exit guidance for vehicles based on the road conditions around the parking lot. Through the map engine and the optimal path planning algorithm, the system can plan the best exit path for the vehicle and guide the owner to quickly find the exit through signboards, APP or in-vehicle navigation.This function not only improves the efficiency of vehicle departure, but also helps to ease the traffic pressure around the parking lot. The big data processing unit is the data processing center of the system, which is responsible for cleaning, integrating, analyzing and storing parking lot data. By using big data technology and machine learning algorithms, the big data processing unit can dig out potential problems and optimization space in the operation of the parking lot, and provide intelligent decision support services for parking lot managers. For example, the system can predict the parking demand trend in the future, adjust the parking space allocation strategy in advance, identify high-frequency illegal parking behaviors and take corresponding management measures, etc. In addition, the big data processing unit also supports complex data analysis and machine learning tasks, providing technical support for the continuous optimization and upgrading of the system. The unmanned parking lot management system based on big data provided in this embodiment realizes the intelligent and efficient management of parking lots through the collaborative work of various units. The use of the system not only improves the utilization rate of parking spaces and parking efficiency, but also significantly improves the user experience and the intelligent level of parking lot management.

[0034] By applying the technical solution of this embodiment, the unmanned parking lot management system based on big data integrates functional units such as parking space information entry, numbering, entry and exit management, allocation, parking space management, user interaction, exit guidance and big data processing. The system realizes the linkage between license plate recognition and parking space control by entering parking space information, assigning unique numbers, recording vehicle information and intelligently allocating parking spaces; at the same time, it allocates nearby parking spaces according to the user's target store information, provides exit guidance in real time based on road conditions, and relies on big data processing units to provide efficient data processing and analysis capabilities to support complex tasks. The embodiment of this application helps to improve the efficiency of parking lot operations, reduce the time users spend looking for parking spaces, and enhance the parking experience; optimize parking space allocation and exit guidance strategies through big data analysis and machine learning; realize intelligent management, reduce labor costs, and improve overall service quality and user satisfaction.

[0035] In the embodiment of the present application, optionally, it also includes: a data acquisition unit, connected to the allocation unit and the entry and exit management unit, for collecting the license plate information and size information of the vehicle; a comparison unit, connected to the data acquisition unit and the parking space information entry unit, for comparing the collected vehicle size information with the parking space information to select a parking space that meets the vehicle size requirements; the allocation unit, connected to the comparison unit, for receiving the parking space information that meets the vehicle size requirements sent by the comparison unit, and allocating a parking space to the vehicle based on the parking space information that meets the vehicle size requirements.

[0036] In this embodiment, the data collection unit is responsible for collecting the license plate information and size information of the vehicle, and the comparison unit compares the vehicle size information with the parking space information to select a parking space that meets the vehicle size requirements; the allocation unit allocates a parking space that meets its size requirements to the vehicle based on the comparison results; at the same time, the nearest parking space is allocated according to the user's target store information, and exit guidance is provided in real time in combination with road conditions, and the big data processing unit provides efficient data processing and analysis capabilities to support complex tasks. The embodiment of the present application can improve the efficiency of parking lot operations, reduce the time users spend looking for suitable parking spaces, and enhance the parking experience. By comparing the vehicle size with the parking space information, it ensures that the allocated parking space can meet the vehicle's parking needs, avoiding the problem of parking space waste and vehicle parking inconvenience.

[0037] In an embodiment of the present application, optionally, it also includes: a road information collection unit, which is used to obtain the road condition information of the roads around the parking lot in real time; the big data processing unit, which is connected to the road information collection unit, is used to clean, integrate and analyze the road condition information of the roads around the parking lot obtained by the road information collection unit, and send the processed road condition information to the exit guidance unit; the exit guidance unit is used to provide exit guidance to the vehicle in real time according to the road condition information to be processed sent by the big data processing unit.

[0038] In this embodiment, the road information collection unit is connected to the exit guidance unit to obtain the road condition information of the roads around the parking lot in real time, connect the smart parking system to the urban traffic management system, and obtain the road condition information in real time, including congested sections, accident warnings, etc., to avoid guiding the vehicle to the area with high traffic pressure, reduce the traffic congestion caused by parking, and use big data analysis and machine learning algorithms to predict the traffic flow around the parking lot, plan the allocation strategy of parking spaces in advance, and ensure that a smooth parking experience can be provided during peak hours. The road information collection unit obtains the road condition information of the roads around the parking lot in real time, and the big data processing unit cleans, integrates and analyzes this information to provide accurate road condition data for the exit guidance unit. The exit guidance unit provides exit guidance for the vehicle in real time based on the processed road condition information. The embodiment of the present application provides accurate road condition information to the exit guidance unit through the collaborative work of the road information collection unit and the big data processing unit, helping the vehicle to quickly find the best exit route and reduce exit congestion.

[0039] In an embodiment of the present application, optionally, it also includes: a data mining unit, connected to the big data processing unit, for mining parking information from historical parking data, wherein the parking information includes at least license plate information of parked vehicles, parking area information, parking time period information, and weather information; a machine learning model unit, connected to the data mining unit, for training a parking space allocation model based on the parking information mined by the data mining unit, wherein the parking space allocation model is deployed in the allocation unit and is used to predict parking demand and optimize parking space allocation strategy.

[0040] In this embodiment, the data mining unit mines parking information from historical parking data, which includes at least the license plate information of the parked vehicle, parking area information, parking time period information, and weather information. The machine learning model unit uses the mined parking information to train the parking space allocation model. The parking space allocation model is deployed in the allocation unit, which can predict parking demand and optimize parking space allocation strategy, further improving the operation efficiency and service quality of the parking lot.

[0041] In the embodiment of the present application, optionally, Figure 2 As shown, the allocation unit includes: a prediction model, which is used to predict the parking demand in the future based on the mined parking information and real-time data, and the real-time data includes real-time weather data and real-time time feature data; a parking space allocation model, with a built-in dynamic parking space allocation algorithm, which is used to dynamically adjust the parking space allocation strategy according to the predicted parking demand and parking space resource situation, and allocate parking spaces based on the parking space allocation strategy; a path planning algorithm, which is used to provide users with the best path planning from the parking lot entrance to the allocated vacant parking space to reduce the time of finding a parking space. The data mining unit is also used to mine the car owner's car model, driving habits, and consumption ability in the historical parking data to build a user portrait; the machine learning model unit is also used to train the parking space allocation model according to the user portrait and the parking information of different car owners, so that the parking space allocation model can dynamically adjust the parking space allocation strategy based on the predicted parking demand, parking space resource situation and user portrait, and allocate parking spaces based on the parking space allocation strategy, so as to provide personalized parking services for different car owners.

[0042] In this embodiment, the data mining unit is connected to the big data processing unit and is used to mine useful information from historical parking data. The system can record and analyze the owner's historical parking data to understand the owner's preferred parking area, parking time period, etc., so that the owner can give priority to recommending the preferred vacant parking space when parking next time, thereby improving the owner's satisfaction and loyalty. Through big data analysis, the owner's user profile is constructed, including vehicle type, driving habits, consumption capacity, etc., to provide more personalized parking services for different types of owners. The machine learning model unit is connected to the data mining unit and is used to train the model based on historical data, predict parking demand and optimize parking space allocation strategy, and provide data support for the allocation unit.

[0043] The allocation unit includes: a dynamic parking space allocation algorithm, which is used to dynamically adjust the parking space allocation strategy according to the real-time parking demand and parking space resource conditions to ensure the efficient use of parking spaces. The dynamic parking space allocation algorithm is usually aimed at maximizing the utilization rate of the parking lot, reducing the waiting time of vehicles, and providing efficient parking services. The objective function can be expressed as minimizing the total waiting time T, where T is the sum of the waiting time of all vehicles. Among them, t iis the waiting time of the i-th vehicle, n is the total number of vehicles entering the parking lot, and the algorithm also needs to consider a series of constraints, such as the availability of parking spaces, the arrival time of vehicles, the type of parking spaces (such as ordinary parking spaces, disabled parking spaces, charging parking spaces), etc. These constraints may be expressed through logical judgments or inequalities. In order to optimize the objective function, linear programming, integer programming, heuristic algorithms (such as genetic algorithms, simulated annealing algorithms, ant colony algorithms), etc. may be used. These algorithms have their own formulas and iterative processes to gradually approach the optimal solution; prediction models, based on historical data and real-time data, predict parking demand in the future to prepare for advance scheduling. Prediction models, especially available parking space prediction models based on big data, usually rely on machine learning algorithms, such as long short-term memory (LSTM) neural networks. These models predict future parking space usage by learning patterns from historical data; LSTM neural network model: The LSTM model processes time series data through a series of gating mechanisms (forget gate, input gate, output gate) to capture long-term dependencies. The model's prediction formula usually involves complex matrix operations and activation functions, but the core idea is to use past data to predict the future. Feature selection: model The input features may include historical parking data (such as parking space occupancy per hour), time features (such as hours, days of the week, holidays), weather data, etc. These features are converted into a format that the model can process through feature engineering; loss function: The loss function used in the model training process (such as mean square error MSE) is used to evaluate the difference between the predicted value and the true value and guide the parameter update of the model; path planning algorithm is used to provide users with the best path planning from the parking lot entrance to the vacant parking space to reduce the time of finding a parking space; the path planning algorithm is used to provide the vehicle with the best path from the parking lot entrance to the vacant parking space, graph theory algorithm: such as Dijkstra algorithm or A* algorithm, these algorithms regard the parking lot as a graph, parking spaces and road intersections as nodes, and roads as edges. The algorithm finds the shortest path by calculating the distance (or cost) between nodes; heuristic function: In the A* algorithm, the heuristic function is used to estimate the optimal path cost from the current node to the target node to improve the search efficiency. The specific form of the heuristic function depends on the specific situation of the problem; path evaluation: The algorithm outputs a series of nodes (i.e., parking spaces and road intersections) that represent the path that the vehicle should pass through. Routes can be evaluated based on factors such as route length, travel time, or cost.

[0044] In the embodiment of the present application, optionally, the data acquisition unit includes: a license plate recognition camera, deployed at the entrance and exit of the parking lot, used to capture the license plate information of vehicles entering and leaving in real time, and identify the license plate number through OCR technology; an environmental sensing device, used to monitor the internal environment of the parking lot, and provide data support for optimizing user experience and energy management; data acquisition software, integrated in the environmental sensing device, responsible for real-time collection of various types of data, and preliminary processing. The parking space management unit includes: a geomagnetic sensor, installed under each parking space, used to detect whether the parking space is occupied, and transmit the status information to the allocation unit in real time; a parking space lock, installed under the parking space, used to control the opening and closing of the parking space according to system instructions; a license plate recognizer, installed on the parking space, used to identify whether the license plate of the vehicle entering the parking space is the license plate information bound to the parking space number.

[0045] In this embodiment, if Figure 3 As shown in the figure, the data collection unit includes: license plate recognition cameras, which are deployed at the entrance and exit of the parking lot to capture the license plate information of vehicles entering and leaving in real time and identify the license plate number through OCR technology; environmental sensing equipment, which is used to monitor the internal environment of the parking lot and provide data support for optimizing user experience and energy management; data collection software, which is integrated into the hardware equipment and is responsible for real-time collection of various types of data and preliminary processing; data transmission protocol, which defines the communication protocol between the data collection equipment and the system server to ensure the security and rapid transmission of data. Figure 4 As shown, the parking space management unit includes: a geomagnetic sensor installed under each parking space, used to detect whether the parking space is occupied and transmit the status information to the system in real time; a parking space lock installed under the parking space, used to control the opening and closing of the parking space according to system instructions; a license plate reader installed on the parking space, used to identify whether the license plate of the vehicle entering the parking space is the license plate of the vehicle assigned by the system.

[0046] In an embodiment of the present application, optionally, the user interaction unit includes a mobile application, which is used to query currently available parking spaces, reserve parking spaces, reserve destination parking spaces, and pay parking fees by self-service.

[0047] In this embodiment, the user interaction unit includes a mobile application, which is used to query currently available parking spaces, reserve parking spaces, reserve destination parking spaces, and pay parking fees by self-service. During use, license plate recognition cameras are deployed at the entrance and exit of the parking lot to capture the license plate information of vehicles entering and leaving in real time, and identify the license plate number through OCR technology. Environmental sensing equipment monitors the internal environment of the parking lot, such as temperature, humidity, light, etc. The data acquisition software is integrated into the hardware equipment, responsible for real-time collection of license plate information, environmental data, etc., and performs preliminary processing. The collected data is safely and quickly transmitted to the system server through the data transmission protocol. The parking space information entry unit enters and stores the information of each parking space in the parking lot, including location, type (ordinary, disabled, charging, etc.), size, etc. The numbering unit assigns a unique number to each parking space. The allocation unit dynamically adjusts the parking space allocation strategy according to real-time parking demand and parking space resource conditions. It takes into account constraints such as parking space availability, vehicle arrival time, and parking space type, and uses optimization algorithms such as linear programming, integer programming, and heuristic algorithms to maximize parking lot utilization and reduce vehicle waiting time. The prediction model is based on historical data and real-time data to predict parking demand in the future and prepare for advance scheduling. It may rely on machine learning algorithms, such as LSTM neural networks. The entry and exit management unit records the information of vehicles entering and leaving the parking lot, including license plate numbers, entry and exit times, etc. When a vehicle enters the parking lot, the geomagnetic sensor of the parking space management unit detects whether the parking space is occupied and transmits the status information to the system in real time. The license plate reader identifies the license plate of the vehicle entering the parking space and compares it with the vehicle license plate assigned by the system. If the match is successful, the parking space lock controls the parking space to open according to the system instructions, allowing the vehicle to park. The user interaction unit provides a mobile application, through which users can query the currently available parking spaces, reserve parking spaces, reserve destination parking spaces, and pay parking fees by themselves. Users enter the target store information into the mobile application, and the application sends the information to the allocation unit. The allocation unit allocates the parking space to an area close to the target store and displays the parking space number of the vehicle. The path planning algorithm provides users with the best path planning from the entrance of the parking lot to the vacant parking space. It may use graph theory algorithms, such as the Dijkstra algorithm or the A* algorithm. The exit guidance unit provides exit guidance for vehicles in real time according to the road conditions around the parking lot.It uses a map engine and optimal path planning algorithm to guide car owners to quickly find the exit through signboards, APP or in-vehicle navigation. The big data processing unit cleans, integrates and analyzes parking lot data to provide fast and efficient data processing capabilities. The data mining unit mines useful information from historical parking data, such as the car owner's preferred parking area, parking time period, etc. The machine learning model unit trains models based on historical data to predict parking demand and optimize parking space allocation strategies. Based on the results of big data analysis, it provides parking lot managers with intelligent decision support services, such as predicting parking demand trends in the future and identifying high-frequency illegal parking behaviors.

[0048] By applying the technical solution of this embodiment, the utilization rate of parking spaces and parking efficiency are improved: through the dynamic parking space allocation algorithm, the parking space allocation strategy is dynamically adjusted according to the real-time parking demand and parking space resource situation to ensure the efficient use of parking spaces and reduce the waiting time of vehicles. The prediction model can predict the parking demand in the future based on historical data and real-time data, prepare for advance scheduling, and further optimize the parking space allocation. Provide personalized parking services: the system can record and analyze the owner's historical parking data, understand the owner's preferred parking area, parking time period, etc., so that the owner's preferred vacant parking space is recommended first when the owner parks next time, improve the owner's satisfaction and loyalty, and build the owner's user profile through big data analysis, including vehicle type, driving habits, consumption ability, etc., to provide more personalized parking services for different types of owners. Reduce the risk of traffic congestion: Real-time acquisition of road conditions information around the parking lot, including congested sections, accident warnings, etc., to avoid directing vehicles to areas with high traffic pressure, use big data analysis and machine learning algorithms to predict the traffic flow around the parking lot, and plan the parking space allocation strategy in advance to ensure a smooth parking experience during peak hours. Optimize user experience: Provide mobile applications to facilitate users to query currently available parking spaces, reserve parking spaces, reserve destination parking spaces, and pay parking fees by themselves. Use AR real-life navigation technology to seamlessly fit navigation routes to real-life roads, so that car owners can quickly find vehicles and exits in complex parking environments. Enhance system intelligence and decision support capabilities: The big data processing unit provides fast and efficient data processing capabilities to support complex data analysis and machine learning tasks. The data mining unit mines useful information from historical parking data to provide a data basis for parking management and decision support. The machine learning model unit trains models based on historical data to provide data support for the allocation unit, further enhancing the intelligence level of the system.

[0049] Further, as Figure 1 The specific implementation of the method, the embodiment of the present application provides an unmanned parking lot management method based on big data, which is applied to the above-mentioned unmanned parking lot management system based on big data, including:

[0050] The parking space information input unit inputs and stores the information of each parking space in the parking lot;

[0051] The numbering unit assigns a unique number to each parking space;

[0052] The entry and exit management unit records the information of vehicles entering and leaving the parking lot, wherein the vehicle information includes license plate information;

[0053] The user interaction unit receives the target store information input by the user, and sends the target store information to the allocation unit, so that the allocation unit allocates a parking space in an area close to the target store to the vehicle;

[0054] The allocating unit allocates a parking space to a vehicle entering the parking lot based on the unique number of each parking space to determine the parking space number of the vehicle and binds the parking space number to the license plate;

[0055] The parking space management unit identifies the license plate information and controls the opening and closing of the parking space; when a vehicle enters the parking space, the license plate information of the vehicle is identified, and when the identified license plate information is consistent with the license plate information bound to the parking space number of the vehicle entering the parking space, the parking space is controlled to be opened;

[0056] The exit guidance unit provides real-time exit guidance to vehicles based on the road conditions around the parking lot.

[0057] It should be noted that the corresponding description of the unmanned parking lot management method based on big data provided in the embodiment of the present application can be referred to Figures 1 to 4 The corresponding description in the method will not be repeated here.

[0058] The embodiment of the present application also provides a computer device, which can be a personal computer, a server, a network device, etc. The computer device includes a bus, a processor, a memory and a communication interface, and can also include an input and output interface and a display device. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store location information. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in each method embodiment are implemented.

[0059] Those skilled in the art will appreciate that the structure of the above-mentioned computer device is only a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components, or combine certain components, or have a different arrangement of components.

[0060] In one embodiment, a computer-readable storage medium is provided. The computer-readable storage medium may be non-volatile or volatile, and stores a computer program thereon. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0061] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0062] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0063] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0064] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0065] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An unmanned parking lot management system based on big data, characterized in that: include: A parking space information input unit, used to input and store information of each parking space in the parking lot; a numbering unit, connected to the parking space information input unit, for assigning a unique number to each parking space; An entry and exit management unit, used to record information about vehicles entering and leaving the parking lot, the vehicle information including license plate information; an allocating unit connected to the numbering unit, for allocating parking spaces for vehicles entering the parking lot based on the unique number of each parking space, so as to determine the parking space number of the vehicle, and to bind the parking space number to the license plate; A parking space management unit is connected to the allocation unit and is used to identify the license plate information and control the opening and closing of the parking space; wherein, when a vehicle enters the parking space, the license plate information of the vehicle is identified, and when the identified license plate information is consistent with the license plate information bound to the parking space number of the vehicle entering the parking space, the parking space is controlled to be opened; A user interaction unit connected to the allocation unit, configured to receive target store information input by a user, and send the target store information to the allocation unit, so that the allocation unit allocates a parking space in an area closer to the target store to the vehicle; The exit guidance unit is used to provide exit guidance to vehicles in real time according to the road conditions around the parking lot; The big data processing unit is used to clean, integrate and analyze parking lot data, provide fast and efficient data processing capabilities, support complex data analysis and machine learning tasks, and provide a data basis for the allocation unit and the exit guidance unit.

2. The unmanned parking lot management system based on big data according to claim 1 is characterized in that: Also includes: A data collection unit, connected to the distribution unit and the entry and exit management unit, for collecting license plate information and size information of the vehicle; A comparison unit, connected to the data collection unit and the parking space information input unit, for comparing the collected vehicle size information with the parking space information to select a parking space that meets the vehicle size requirements; The allocation unit is connected to the comparison unit, and is used to receive the parking space information that meets the vehicle size requirement sent by the comparison unit, and allocate a parking space to the vehicle based on the parking space information that meets the vehicle size requirement.

3. The unmanned parking lot management system based on big data according to claim 1 is characterized in that: Also includes: A road information collection unit is used to obtain the road condition information of the roads around the parking lot in real time; The big data processing unit is connected to the road information collection unit, and is used to clean, integrate and analyze the road condition information of the roads around the parking lot acquired by the road information collection unit, and send the processed road condition information to the exit guidance unit; The exit guidance unit is used to provide exit guidance to the vehicle in real time according to the road condition information to be processed sent by the big data processing unit.

4. The unmanned parking lot management system based on big data according to claim 1 is characterized in that: Also includes: A data mining unit connected to the big data processing unit, used to mine parking information from historical parking data, wherein the parking information at least includes license plate information of parked vehicles, parking area information, parking time period information, and weather information; A machine learning model unit is connected to the data mining unit and is used to train a parking space allocation model according to the parking information mined by the data mining unit. The parking space allocation model is deployed in the allocation unit and is used to predict parking demand and optimize parking space allocation strategy.

5. The unmanned parking lot management system based on big data according to claim 4 is characterized in that: The distribution unit comprises: A prediction model is used to predict parking demand in the future based on the mined parking information and real-time data, wherein the real-time data includes real-time weather data and real-time time feature data; Parking space allocation model, with built-in dynamic parking space allocation algorithm, is used to dynamically adjust the parking space allocation strategy according to the predicted parking demand and parking space resource situation, and allocate parking spaces based on the parking space allocation strategy; The path planning algorithm is used to provide users with the best path planning from the parking lot entrance to the allocated vacant parking space to reduce the time of searching for parking spaces.

6. The unmanned parking lot management system based on big data according to claim 5 is characterized in that: The data mining unit is also used to mine the car model, driving habits, and consumption capacity of the car owner in the historical parking data to build a user portrait; The machine learning model unit is also used to train the parking space allocation model according to the user portrait and the parking information of different car owners, so that the parking space allocation model dynamically adjusts the parking space allocation strategy based on the predicted parking demand, parking space resource conditions and user portrait, and allocates parking spaces based on the parking space allocation strategy, so as to provide personalized parking services for different car owners.

7. The unmanned parking lot management system based on big data according to claim 2 is characterized in that: The data acquisition unit comprises: License plate recognition cameras are deployed at the entrance and exit of the parking lot to capture the license plate information of vehicles entering and leaving in real time and identify the license plate number through OCR technology; Environmental sensing equipment is used to monitor the internal environment of the parking lot and provide data support for optimizing user experience and energy management; The data acquisition software is integrated into the environmental sensing device and is responsible for real-time collection of various data and preliminary processing.

8. The unmanned parking lot management system based on big data according to claim 1 is characterized in that: The parking space management unit comprises: A geomagnetic sensor, installed under each parking space, is used to detect whether the parking space is occupied and transmit the status information to the allocation unit in real time; A parking space lock, installed under the parking space, for controlling the opening and closing of the parking space according to system instructions; The license plate reader is installed on the parking space and is used to identify whether the license plate of the vehicle entering the parking space is the license plate information bound to the parking space number.

9. The unmanned parking lot management system based on big data according to claim 1 is characterized in that: The user interaction unit includes a mobile application, which is used to query currently available parking spaces, reserve parking spaces, reserve destination parking spaces, and pay parking fees by self-service.

10. A method for managing an unmanned parking lot based on big data, characterized in that: Applied to the unmanned parking lot management system based on big data as claimed in any one of claims 1 to 9, the method comprises: The parking space information input unit inputs and stores the information of each parking space in the parking lot; The numbering unit assigns a unique number to each parking space; The entry and exit management unit records the information of vehicles entering and leaving the parking lot, wherein the vehicle information includes license plate information; The user interaction unit receives the target store information input by the user, and sends the target store information to the allocation unit, so that the allocation unit allocates a parking space in an area close to the target store to the vehicle; The allocating unit allocates a parking space to a vehicle entering the parking lot based on the unique number of each parking space to determine the parking space number of the vehicle and binds the parking space number to the license plate; The parking space management unit identifies the license plate information and controls the opening and closing of the parking space; when a vehicle enters the parking space, the license plate information of the vehicle is identified, and when the identified license plate information is consistent with the license plate information bound to the parking space number of the vehicle entering the parking space, the parking space is controlled to be opened; The exit guidance unit provides real-time exit guidance to vehicles based on the road conditions around the parking lot.

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