Comprehensive management background operation and maintenance system

Abstract

The invention discloses a comprehensive management background operation and maintenance system, and the system comprises an automatic charging management module which is used for providing an automatic payment service; the abnormal behavior detection module is used for detecting an abnormal behavior and triggering an alarm; the energy management module is used for automatically adjusting the state of the illumination and ventilation system; the parking space distribution management module comprises an entrance recommendation unit used for recommending an entrance for the vehicle; the parking space distribution unit is used for acquiring idle parking spaces, vehicle positions, access destination positions and charging pile position information when the visitors are identified and the electric vehicles are driven, and establishing a multi-target optimization model; a target parking space is distributed to the vehicle owner through solving; and the navigation positioning unit is used for providing navigation service for the vehicle owner and updating the optimal driving path in real time by adopting a dynamic path planning algorithm. According to the invention, proper entrances and parking spaces can be rapidly and accurately provided for vehicle owners, the optimal path is provided for driving reference of the vehicle owners, the rationality of parking space distribution of the parking lot is ensured, and the utilization rate of parking space resources and the management energy efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of operation and maintenance management technology, and in particular to a comprehensive management background operation and maintenance system. Background Art

[0002] The allocation and management of parking spaces in residential parking lots has always been a major problem in the comprehensive management and operation of residential areas. Since the contradiction between the number of vehicles owned by residents and the number of parking spaces is a common phenomenon, and the demand is relatively concentrated at certain times, it is difficult to allocate parking spaces. Traditional parking lots usually lack an intelligent entrance recommendation mechanism, and all vehicles may flock to the same entrance, causing congestion. The current allocation of parking spaces usually only matches car owners based on available parking spaces, using a first-come, first-served mechanism. Sometimes, car owners even need to go back and forth in the parking lot to find parking spaces, which seriously affects the parking efficiency of car owners and reduces their parking experience. Summary of the invention

[0003] In order to solve at least one of the technical problems mentioned above, the present invention provides a comprehensive management background operation and maintenance system.

[0004] The present invention provides a comprehensive management background operation and maintenance system, the system comprising:

[0005] Parking space allocation management module, automatic billing management module, abnormal behavior detection module and energy management module;

[0006] The automatic billing management module is used to provide automatic payment services and record parking transaction data;

[0007] The abnormal behavior detection module is used to detect abnormal behavior in the parking lot and trigger an alarm when abnormal behavior is detected.

[0008] The energy management module is used to automatically adjust the operating status of the lighting system and the ventilation system according to the parking lot usage status;

[0009] The parking space allocation management module includes:

[0010] The entrance recommendation unit is used to determine whether the current time is in the peak parking period when a vehicle is detected passing through the parking lot entrance; if so, obtain the queue time information of each entrance of the parking lot, and push the entrance corresponding to the shortest queue time as the recommended entrance to the current vehicle; if not, allow the current vehicle to enter from the current entrance;

[0011] The parking space allocation unit is used to recognize the license plate of the vehicle passing through the parking lot entrance. When the owner is identified as a visitor and the vehicle is an electric vehicle, the unit obtains the free parking space information, the vehicle location information, the destination location information and the charging pile location information, and establishes a multi-objective optimization model; solves the multi-objective optimization model, and allocates the target parking space to the owner according to the optimal solution;

[0012] The navigation and positioning unit is used to provide navigation services for the current car owner according to the target parking space, and adopt a dynamic path planning algorithm to update the optimal driving path in real time and push it to the current car owner.

[0013] Preferably, the entry recommendation unit is further used for:

[0014] The LSTM network model is trained based on the parking lot operation data in the historical period to generate a prediction model;

[0015] The current time is input into the prediction model to predict whether the current time is in the peak parking period.

[0016] Preferably, the parking space allocation unit is further used for:

[0017] Determine the distance between each free parking space and the vehicle location, the distance between each free parking space and the destination location, and the distance between each free parking space and the charging pile location, assign weights to each distance, and build a multi-objective optimization model with the goal of minimizing the weighted total distance;

[0018] Construct constraints based on the time required for parking, the total number of parking spaces in the parking lot, the number of free parking spaces in the parking lot, and the number of available charging piles;

[0019] Based on the multi-objective optimization model and the constraints, a genetic algorithm or a particle swarm optimization algorithm is used to solve the problem.

[0020] Preferably, the parking space allocation unit is further used for:

[0021] When the car owner is identified as the householder, the householder's historical parking data is collected and the user's parking behavior preference is analyzed through a clustering algorithm to construct a user profile; the historical parking data includes parking time period, parking frequency and preferred parking space area;

[0022] The parking needs of household owners are predicted based on user portraits, and parking spaces are allocated to household owners based on the predicted parking needs of household owners.

[0023] Preferably, the navigation and positioning unit is further used for:

[0024] Obstacles or closed areas are identified while the owner is driving. When obstacles or closed areas are identified in the path, the driving path is recalculated.

[0025] Preferably, the automatic billing management module is also used to record the data generated by each parking transaction using blockchain technology.

[0026] Preferably, the abnormal behaviors include theft, illegal destruction, and detention time exceeding a preset time.

[0027] Preferably, the abnormal behavior detection module is further used for:

[0028] When abnormal behaviors such as theft, illegal destruction, and staying for longer than a preset time are detected in the parking lot, the person who triggered the abnormal behavior will be locked as a monitoring target;

[0029] Obtain the surveillance video corresponding to the monitored object, extract features from the frame images in the video, and generate a target feature map;

[0030] The clarity of the target feature map is calculated. When the clarity does not meet the preset value, image enhancement and deblurring operations are performed until the clarity reaches the preset value. The position coordinates of the monitored object in continuous frame images are extracted, and the monitored object is tracked and located based on the continuous position coordinates.

[0031] Preferably, the energy management module further includes:

[0032] The lighting control unit is used to detect the activity status of vehicles and people in the parking lot based on infrared sensors. When vehicle or human activity is detected, the lights in the corresponding area of ​​the parking lot are turned on; when no vehicle or human activity is detected within a preset period of time, the lights are controlled to enter energy-saving lighting mode.

[0033] Preferably, the energy management module further includes:

[0034] A ventilation control unit is used to obtain environmental data and vehicle entry and exit frequency in a parking lot; the environmental data includes carbon dioxide concentration, temperature and humidity; the environmental data and vehicle entry and exit frequency are input into a preset ventilation volume prediction model to predict a target ventilation volume; and the output power of the ventilation system is adjusted according to the difference between the target ventilation volume and the current ventilation volume.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1) The present invention predicts peak hours and adopts an entrance recommendation mechanism to effectively solve the entrance congestion problem. By real-time monitoring and recommending the entrance with the shortest queue time, the traffic flow is effectively dispersed to avoid traffic bottlenecks at the entrance. In this way, the parking lot operation efficiency can be improved: the waiting time of vehicles can be reduced, the vehicle turnover rate can be accelerated, and the overall capacity utilization rate of the parking lot can be improved.

[0037] 2) The present invention establishes a multi-objective optimization model based on information such as the owner's identity, vehicle type, destination and charging pile location to ensure reasonable allocation of parking spaces. Car owners can find suitable parking spaces more quickly and reduce the anxiety of finding parking spaces. In particular, electric vehicle users can quickly find charging facilities.

[0038] 3) The present invention can provide dynamic route planning, taking into account the real-time road conditions and the car owner's destination, to ensure that the car owner obtains the most optimized driving route and can enjoy a smooth navigation experience even inside the parking lot. By optimizing the vehicle's driving path and reducing unnecessary waiting, the carbon emissions of the vehicle in the parking lot are reduced, which conforms to the concept of green travel and achieves the purpose of energy conservation and emission reduction.

[0039] 4) The present invention simplifies the payment process through the automatic billing management module, reduces the waiting time caused by manual charging, makes the process of entering and exiting the parking lot smoother, and improves user satisfaction. The abnormal behavior detection module can quickly identify potential threats or abnormal activities, thereby strengthening the security management in the parking lot; the energy management module intelligently controls the lighting and ventilation systems, avoids unnecessary energy consumption, reduces operating costs, and also reduces carbon emissions, which is in line with the concept of green buildings and sustainable development. Therefore, with the joint cooperation of these modules and the parking space allocation management module, the energy efficiency of parking lot operation and maintenance management can be greatly improved, and the user parking experience can be improved.

[0040] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below.

[0042] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0043] Figure 1 A schematic diagram of the structure of a comprehensive management backend operation and maintenance system provided by an embodiment of the present invention;

[0044] Figure 2 The embodiment of the present invention provides Figure 1 Schematic diagram of the structure of the energy management module 400. DETAILED DESCRIPTION

[0045] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0047] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0048] In addition, in order to better illustrate the present invention, numerous specific details are provided in the following specific embodiments. It should be understood by those skilled in the art that the present invention can be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present invention.

[0049] At present, parking lot allocation and management still have problems such as unreasonable allocation, low resource utilization, low operation and management efficiency, and poor user experience. To this end, the present invention provides a comprehensive management background operation and maintenance system that can provide effective entry recommendation strategies and parking space allocation strategies, thereby greatly improving parking space utilization and parking lot operation and maintenance management efficiency, while improving user experience.

[0050] See also Figure 1 , Figure 1 Schematic diagram of the structure of a comprehensive management background operation and maintenance system 10 provided by an embodiment of the present invention. Figure 1 As shown, the integrated management backend operation and maintenance system 10 includes the following modules:

[0051] Parking space allocation management module 100, automatic billing management module 200, abnormal behavior detection module 300 and energy management module 400;

[0052] Automatic billing management module 200, used to provide automatic payment service and record parking transaction data;

[0053] The abnormal behavior detection module 300 is used to detect abnormal behavior in the parking lot and trigger an alarm when abnormal behavior is detected.

[0054] Energy management module 400, used to automatically adjust the operating status of the lighting system and the ventilation system according to the parking lot usage status;

[0055] The parking space allocation management module 100 includes:

[0056] The entrance recommendation unit 101 is used to determine whether the current time is in the peak parking period when a vehicle is detected passing through the parking lot entrance; if so, obtain the queue time information of each entrance of the parking lot, and push the entrance corresponding to the shortest queue time as the recommended entrance to the current vehicle; if not, allow the current vehicle to enter from the current entrance;

[0057] The parking space allocation unit 102 is used to perform license plate recognition on vehicles passing through the parking lot entrance. When it is recognized that the owner of the vehicle is a visitor and the vehicle is an electric vehicle, the vacant parking space information, the vehicle location information, the destination location information and the charging pile location information are obtained, and a multi-objective optimization model is established; the multi-objective optimization model is solved, and a target parking space is allocated to the owner according to the optimal solution;

[0058] The navigation and positioning unit 103 is used to provide navigation services for the current car owner according to the target parking space, and adopt a dynamic path planning algorithm to update the optimal driving path in real time and push it to the current car owner.

[0059] In this embodiment, the automatic billing management module 200 can implement the following functions:

[0060] 1) Automatic identification and billing: Use license plate recognition technology or RFID to automatically identify vehicle information and automatically calculate parking fees based on preset billing rules (such as hourly, daily or monthly).

[0061] 2) Contactless payment: By binding the user's payment method (such as bank card, credit card or third-party payment platform), automatic deductions can be achieved without the need for cash or on-site operations.

[0062] 3) Transaction record management: Automatically record detailed information of each parking transaction, including vehicle information, entry time, exit time, parking duration and fee amount. Provide transaction query and reconciliation functions to facilitate users and managers to view historical transaction records. In addition, for special circumstances, such as vehicle detention overtime, billing errors caused by system failure, etc., it can trace the cost to ensure fair and reasonable billing.

[0063] 4) User interface and notification: Provides a user-friendly interface that allows users to check balances, top up, view bills, etc.; it can also send payment notifications, overdue payment reminders, or transaction confirmations to users.

[0064] The abnormal behavior detection module 300 is used to detect abnormal behaviors in the parking lot and trigger an alarm when abnormal behaviors are detected. Abnormal behaviors in the parking lot usually include theft, illegal damage, and staying for a period exceeding a preset time. For these situations, the module can provide monitoring, behavior analysis, and trigger alarm prompts to notify the parking lot manager to intervene in time and deal with abnormal behaviors. Specifically, the functions of this module are as follows:

[0065] 1) Video surveillance: Use high-definition cameras to continuously monitor activities in the parking lot. The cameras may be equipped with night vision capabilities to capture clear images even in low-light conditions.

[0066] 2) Behavior analysis algorithm: Use computer vision technology and machine learning models to analyze video streams. The algorithm can be trained to be able to directly identify abnormal behavior. When abnormal behavior occurs, the model can directly identify the abnormal behavior based on the video data and lock the monitored object; in other scenarios, the algorithm can also be trained to identify normal behavior patterns. Any behavior that deviates from these patterns can be regarded as potential abnormal behavior.

[0067] 3) Anomaly detection and instant alerts: When the algorithm detects abnormal behavior, such as someone wandering in the parking lot, damaging property, or attempting to enter a vehicle illegally, an alarm is immediately triggered. Abnormal behavior may also include vehicles that stay for a long time, unusual movement patterns, or other predefined suspicious activities. When the alarm is triggered, the system will immediately notify security personnel or automatically send an alarm signal to the police. At the same time, the alarm may be accompanied by sound and light warnings on the spot to deter lawbreakers.

[0068] The energy management module 400 is used to automatically adjust the operating status of the lighting system and the ventilation system according to the use status of the parking lot. By integrating various sensors and intelligent control systems, the module can dynamically adjust the working mode of the lighting and ventilation systems according to the actual use status of the parking lot, thereby achieving the purpose of efficient use of energy.

[0069] The parking space allocation management module 100 aims to optimize the parking experience of vehicles through efficient algorithms and real-time data processing capabilities. By quickly and accurately providing suitable parking spaces for car owners and providing the best route for car owners to refer to, the rationality of parking space allocation in the parking lot is ensured, and the utilization rate of parking space resources and management efficiency are improved.

[0070] Specifically, the parking space allocation management module 100 includes an entrance recommendation unit 101, a parking space allocation unit 102 and a navigation positioning unit 103. Figure 1 As shown, the following are the introductions to these three units:

[0071] The entrance recommendation unit 101 is used to determine whether the current time is in the peak parking period when a vehicle is detected passing through the parking lot entrance; if so, obtain the queue time information of each entrance of the parking lot, and push the entrance corresponding to the shortest queue time as the recommended entrance to the current vehicle; if not, allow the current vehicle to enter from the current entrance;

[0072] The goal of this unit is to reduce the waiting time of vehicles at the entrance during high traffic periods and improve overall efficiency. When a vehicle approaches the entrance of a parking lot, the entrance recommendation unit 101 first checks whether it is currently in the peak parking period, which is usually determined based on historical data and real-time traffic information. If it is confirmed to be a peak period, the system will evaluate the queues at each entrance and select the entrance with the shortest queue time to recommend to the driver, thereby dispersing vehicle traffic and reducing congestion. If it is not a peak period, the vehicle can enter directly from the current entrance without special recommendation.

[0073] The parking space allocation unit 102 is used to perform license plate recognition on vehicles passing through the parking lot entrance. When it is recognized that the owner of the vehicle is a visitor and the vehicle is an electric vehicle, the vacant parking space information, the vehicle location information, the destination location information and the charging pile location information are obtained, and a multi-objective optimization model is established; the multi-objective optimization model is solved, and a target parking space is allocated to the owner according to the optimal solution;

[0074] For vehicles passing through the entrance, especially electric vehicles driven by visitors, the parking space allocation unit 102 will initiate a series of operations, including:

[0075] License plate recognition: The camera captures the license plate number, determines the vehicle information, and identifies the visitor.

[0076] Information acquisition: The system collects information about the location of free parking spaces in the parking lot, the current location of the vehicle, the visitor’s destination (such as a specific store in a mall), and the location of available charging stations.

[0077] Multi-objective optimization: Build a multi-objective optimization model that takes into account distance, charging requirements, and convenience of reaching the destination. The model may consider factors such as the distance from the parking space to the charging station, the distance from the parking space to the destination, and the availability of the parking space.

[0078] Parking space allocation: By solving the optimization model, the system will allocate an optimal parking space for the visitor, which should meet the charging needs (if it is an electric car) and be close to the visitor's destination for subsequent activities.

[0079] The navigation and positioning unit 103 is used to provide navigation services for the current car owner according to the target parking space, and adopt a dynamic path planning algorithm to update the optimal driving path in real time and push it to the current car owner.

[0080] Once a parking space is allocated, the navigation and positioning unit 103 will intervene to provide the driver with accurate navigation instructions from the current position to the allocated parking space. This process may be completed through a mobile application, an in-vehicle navigation system, or an information screen in the parking lot. The navigation service uses a dynamic path planning algorithm, taking into account the real-time traffic conditions inside the parking lot, and continuously updates and pushes the optimal driving path to the driver, ensuring that even if an emergency occurs in the parking lot (such as a temporarily closed route), the route can be quickly adjusted to guide the vehicle to the target parking space smoothly.

[0081] In summary, the comprehensive management background operation and maintenance system 10 provided by the embodiment of the present invention can achieve the following effects:

[0082] 1) By predicting peak hours and adopting an entrance recommendation mechanism, the problem of entrance congestion can be effectively solved. By real-time monitoring and recommending the entrance with the shortest queue time, the traffic flow can be effectively dispersed to avoid traffic bottlenecks at the entrance. In this way, the parking lot operation efficiency can be improved: the waiting time of vehicles can be reduced, the vehicle turnover rate can be accelerated, and the overall capacity utilization of the parking lot can be improved.

[0083] 2) Based on information such as the owner’s identity, vehicle type, destination, and charging station location, a multi-objective optimization model is established to ensure that parking spaces are allocated reasonably. Car owners can find suitable parking spaces more quickly and reduce the anxiety of finding parking spaces. In particular, electric vehicle users can quickly find charging facilities.

[0084] 3) It can provide dynamic route planning, taking into account real-time road conditions and the owner's destination, to ensure that the owner obtains the most optimized driving route and enjoys a smooth navigation experience even inside the parking lot. By optimizing the vehicle's driving path and reducing unnecessary waiting, the vehicle's carbon emissions in the parking lot are reduced, which conforms to the concept of green travel and achieves the goal of energy conservation and emission reduction.

[0085] 4) The automatic billing management module 200 simplifies the payment process, reduces the waiting time caused by manual charging, makes the process of entering and exiting the parking lot smoother, and improves user satisfaction. The abnormal behavior detection module 300 can quickly identify potential threats or abnormal activities, and strengthen the security management in the parking lot; the energy management module 400 intelligently controls the lighting and ventilation systems, avoids unnecessary energy consumption, reduces operating costs, and also reduces carbon emissions, which is in line with the concept of green buildings and sustainable development. Therefore, with the joint cooperation of these modules and the parking space allocation management module 100, the energy efficiency of parking lot operation and maintenance management can be greatly improved, and the user parking experience can be improved.

[0086] In one embodiment, the entry recommendation unit 101 is further configured to:

[0087] The LSTM network model is trained based on the parking lot operation data in the historical period to generate a prediction model;

[0088] The current time is input into the prediction model to predict whether the current time is in the peak parking period.

[0089] When training the prediction model, this embodiment includes the following steps:

[0090] The role of the entrance recommendation unit 101 in the smart parking system goes far beyond simple vehicle guidance. It combines advanced data analysis and machine learning techniques, such as long short-term memory networks (LSTM), to optimize parking experience and resource allocation. The following are detailed steps on how the entrance recommendation unit 101 uses the LSTM network model to make predictions and decisions:

[0091] 1) Data collection and preprocessing: Collect parking lot operation data in historical periods, including but not limited to vehicle entry and exit times, parking hours, parking space occupancy, weather conditions, holiday information, etc. Clean and preprocess the data, remove outliers, fill in missing values, and normalize them.

[0092] 2) Model training: The LSTM network model is trained using historical data. LSTM is particularly suitable for processing time series data because it can capture long-term dependencies of data over time. The LSTM model is trained to learn the pattern of peak parking hours, that is, when the parking lot usage rate will suddenly increase. After training, the model can be saved and used to predict new unknown data points. The resulting prediction model will be able to predict whether the parking lot is about to or is experiencing a peak period based on the input features.

[0093] 3) Real-time prediction and decision-making: The data at the current moment (such as timestamp, external events, weather conditions, etc.) is input into the prediction model, and the model outputs the probability of whether the current moment is in or about to enter the parking peak period. If the prediction result shows that it is a peak period, the entrance recommendation unit 101 can activate the corresponding strategy to recommend vehicles to enter from other entrances, or dynamically adjust the number of open entrances to speed up the entry of vehicles.

[0094] 4) Continuous optimization: The results of model predictions and actual events will be recorded for subsequent model evaluation and retraining. The model has a self-learning function and is regularly updated through iterative optimization to adapt to changes in parking lot operation data and maintain prediction accuracy.

[0095] In one embodiment, the parking space allocation unit 102 is further configured to:

[0096] Determine the distance between each free parking space and the vehicle location, the distance between each free parking space and the destination location, and the distance between each free parking space and the charging pile location, assign weights to each distance, and build a multi-objective optimization model with the goal of minimizing the weighted total distance;

[0097] Construct constraints based on the time required for parking, the total number of parking spaces in the parking lot, the number of free parking spaces in the parking lot, and the number of available charging piles;

[0098] Based on the multi-objective optimization model and the constraints, a genetic algorithm or a particle swarm optimization algorithm is used to solve the problem.

[0099] Specifically, the parking space allocation calculation process is as follows:

[0100] 1) Construct a multi-objective optimization model:

[0101] Assumption d ip is the distance from vehicle i to the vacant parking space p, d pr is the distance from the free parking space p to the visited destination r, d pc is the distance from the free parking space p to the charging pile c, and the weights of these three distances are set to w1, w2, and w3 respectively. The weight distribution can be obtained based on the analysis of historical parking data. For example, if it is analyzed that the parking demand is the largest for the closest to the visited destination, then the value of w2 can be larger. The setting of these values ​​is selected according to the specific scenario, and this embodiment does not make any limitation.

[0102] Establish the objective function:

[0103] f(p i )=w1d ip +w2d pr +w3d pc

[0104] The goal is to find the min{f(p i )}.

[0105] 2) Construct constraints:

[0106] Assume t p is the parking time, n is the total number of vehicles, N is the total number of parking spaces, N f is the number of available parking spaces in the parking lot, N c is the number of available charging piles, then:

[0107]

[0108] where x i p is a binary variable. If vehicle i is parked in parking space p, then x ip =1, otherwise 0. This constraint means that for each parking space p in the parking lot, the total number of allocated vehicles cannot exceed the total number of free parking spaces N. f .

[0109]

[0110] where y ic is a binary variable. If vehicle i is charged using charging station c, then y ic =1, otherwise 0. c indicates that the constraint holds for every charging pile c.

[0111]

[0112] where t min ,t max These are the minimum parking time requirement and the maximum parking time requirement.

[0113] 3) Solving function:

[0114] Take the genetic algorithm as an example to illustrate the solution process:

[0115] 3.1) Initialization: Randomly generate an initial population P, where each individual represents a possible solution.

[0116] 3.2) Evaluation: Calculate the objective function value of each individual in the population.

[0117] 3.3) Selection: A certain number of individuals are selected for reproduction based on their fitness.

[0118] 3.4) Crossover: Generate a new individual by exchanging partial information of two individuals.

[0119] 3.5) Mutation: Randomly change certain parts of new individuals to increase population diversity.

[0120] 3.6) Update the population: add new individuals to the population and replace the old ones.

[0121] 3.7) Termination condition: If the preset number of iterations is reached or other termination conditions are met, stop the algorithm; otherwise return to step 3.2) to iterate.

[0122] It is understandable that if the owner is a visitor and the car he drives is a gasoline car, then there is no need to consider the case of an electric car. In this case, the objective function can be set to f(p i )=w1d ip +w2d pr , and then solve it in the same way as the above embodiment to allocate the best parking space to the visitor driving the oil car.

[0123] This embodiment establishes a multi-objective optimization model based on information such as the owner's identity, vehicle type, destination, and charging pile location to ensure reasonable allocation of parking spaces. Car owners can find suitable parking spaces more quickly and reduce the anxiety of finding parking spaces. In particular, electric car users can quickly find charging facilities, which greatly improves the user experience when using the parking lot.

[0124] In one embodiment, the parking space allocation unit 102 is further configured to:

[0125] When the car owner is identified as the householder, the householder's historical parking data is collected and the user's parking behavior preference is analyzed through a clustering algorithm to construct a user profile; the historical parking data includes parking time period, parking frequency and preferred parking space area;

[0126] The parking needs of household owners are predicted based on user portraits, and parking spaces are allocated to household owners based on the predicted parking needs of household owners.

[0127] The above embodiment is aimed at the case where the car owner is a visitor. This embodiment mainly considers the case where the car owner is a householder in a residential area. Since householders in a residential area usually have fixed parking spaces or fixed parking habits, the type of vehicle is no longer considered at this time. Instead, parking spaces are allocated mainly based on user preferences to meet the needs of car owners.

[0128] Specifically, the allocation includes the following steps:

[0129] 1) Owner Identification: When a car owner enters the parking lot, the system uses license plate recognition technology or other identity verification methods (such as mobile application login, RFID card, etc.) to identify whether the car owner is the owner of the household.

[0130] 2) Historical parking data collection and analysis: For car owners who have been confirmed as household owners, the system begins to collect their historical parking records, which include but are not limited to: specific parking time periods (such as morning and evening peaks, weekdays / weekends, specific holidays, etc.), parking frequency (number of parking times in a day or a week), and the parking area preferred by car owners (near elevators, exits, or specific floors). Using the clustering algorithm in machine learning, the system analyzes the above data in order to identify the parking patterns and preferences of different household owners and then build user portraits.

[0131] 3) Predicting parking needs: Through user profiling, the system can predict the householder’s future parking needs, such as the probability of needing a parking space on a specific day or time period.

[0132] 4) Intelligent allocation of parking spaces: Based on the predicted parking needs of the householder, the system can reserve a suitable parking space in advance to ensure that the householder can quickly find a space that meets his or her preferences when he or she arrives. This dynamic allocation mechanism not only improves the parking experience of the householder, but also improves the efficiency of parking lot use, reducing the time spent looking for parking spaces and unnecessary waiting.

[0133] 5) Continuous optimization: As time goes by, the system will continue to collect new parking data and continuously update the user profile, so as to more accurately predict and meet the parking needs of the householder. Users can also further optimize the parking spaces recommended by the system by providing feedback or setting personal preferences.

[0134] Therefore, by adopting different parking space allocation methods for visitors and household owners, when the car owner is the household owner of the community, a user profile is built according to the user's preferences to predict parking needs, and more convenient and personalized services are provided to the car owner, thereby greatly improving the user experience and improving the operational efficiency of the parking lot.

[0135] In one embodiment, the navigation and positioning unit 103 is also used to identify obstacles or closed areas during the driving process of the vehicle owner, and recalculate the driving path when obstacles or closed areas are identified in the path.

[0136] In this embodiment, when identifying obstacles or closed areas, sensors are mainly relied upon, including but not limited to visual sensors, radar sensors, and ultrasonic sensors. If an obstacle or closed area is identified, the navigation and positioning unit 103 will evaluate its impact on the current driving path. If the obstacle cannot be bypassed or the closed area blocks the original path, the navigation and positioning unit 103 will trigger a procedure for replanning the path. When replanning the driving path, preferably, the Dijkstra algorithm is used to find the shortest, fastest, or safest alternative route. Once the new path is determined, the navigation and positioning unit 103 will send instructions to the vehicle's automatic driving module to adjust operations such as steering, acceleration, and braking, and continue to monitor the surrounding environment to prepare for new obstacles or changes that may appear.

[0137] Therefore, this embodiment can provide dynamic path planning, taking into account the real-time road conditions and the car owner's destination, to ensure that the car owner obtains the most optimized driving route and enjoys a smooth navigation experience even inside the parking lot. By optimizing the vehicle's driving path and reducing unnecessary waiting, the carbon emissions of the vehicle in the parking lot are reduced, which conforms to the concept of green travel and achieves the purpose of energy conservation and emission reduction.

[0138] In one embodiment, the automatic billing management module 200 is also used to record the data generated by each parking transaction using blockchain technology. By using blockchain technology, the data generated by parking lot transactions cannot be tampered with, which has the advantages of decentralization and high transparency. At the same time, smart contracts can be embedded in the blockchain to automatically execute parking billing rules, such as automatically calculating fees based on parking duration, reducing human intervention. This can greatly improve billing efficiency and reduce random and wrong charges.

[0139] In one embodiment, the abnormal behavior includes theft, illegal destruction, and retention time exceeding a preset time. The abnormal behavior detection module 300 is also used to:

[0140] When abnormal behaviors such as theft, illegal destruction, and staying for longer than a preset time are detected in the parking lot, the person who triggered the abnormal behavior will be locked as a monitoring target;

[0141] Obtain the surveillance video corresponding to the monitored object, extract features from the frame images in the video, and generate a target feature map;

[0142] The clarity of the target feature map is calculated. When the clarity does not meet the preset value, image enhancement and deblurring operations are performed until the clarity reaches the preset value. The position coordinates of the monitored object in continuous frame images are extracted, and the monitored object is tracked and located based on the continuous position coordinates.

[0143] In this embodiment, a video surveillance system is used to capture activities in the parking lot in real time. Computer vision and deep learning algorithms are used to identify abnormal behaviors such as theft, illegal destruction, and long-term detention. When suspected abnormal behavior is identified, the individuals involved are marked as monitoring objects. Relevant surveillance video clips are retrieved. Feature extraction is performed on each frame of the video to generate a target feature map. This step can usually use a convolutional neural network (CNN) for feature extraction.

[0144] Furthermore, the clarity of the target feature map is calculated. If the clarity is lower than a preset threshold, image enhancement and deblurring operations are performed until the clarity reaches the standard. Extracting the position coordinates of the monitored object in continuous frame images can be achieved through target detection and motion estimation algorithms. Finally, using the continuous position coordinate information, the system can track the movement trajectory of the monitored object and maintain tracking continuity even in complex environments. When abnormal behavior is detected, an alarm will be triggered. During the time when the security personnel arrive at the scene, even if the monitored object moves and escapes, the security personnel can still quickly track the monitored object through the positioning and tracking method of this embodiment, so that timely measures can be taken. This can improve the security of parking lot operation and management.

[0145] See also Figure 2In one embodiment, the energy management module 400 further includes:

[0146] The lighting control unit 401 is used to detect the activity status of vehicles and people in the parking lot based on infrared sensors. When vehicle or human activity is detected, the lights in the corresponding area of ​​the parking lot are turned on; when no vehicle or human activity is detected within a preset period of time, the lights are controlled to enter energy-saving lighting mode.

[0147] Specifically, the following functions are provided for lighting control:

[0148] Occupancy detection: Use infrared, ultrasonic or radar sensors to detect whether a vehicle or person has entered an area. When activity is detected, the corresponding lighting fixtures are activated.

[0149] Light sensing: Light sensors can measure the ambient light intensity and automatically adjust the brightness of artificial lighting to make full use of natural light and reduce unnecessary power consumption.

[0150] Timing control: Set the on / off time of the lighting system according to the parking lot’s operating hours and peak traffic hours to avoid excessive lighting during non-peak hours.

[0151] Zone control: Divide the parking lot into multiple zones and control the lighting independently according to the usage of each zone, for example, only illuminating the area where there are parked vehicles or people walking.

[0152] See also Figure 2 In one embodiment, the energy management module 400 further includes:

[0153] The ventilation control unit 402 is used to obtain environmental data and vehicle entry and exit frequency in the parking lot; the environmental data includes carbon dioxide concentration, temperature and humidity; the environmental data and vehicle entry and exit frequency are input into a preset ventilation volume prediction model to predict the target ventilation volume; and the output power of the ventilation system is adjusted according to the difference between the target ventilation volume and the current ventilation volume.

[0154] Specifically, it has the following functions when controlling ventilation:

[0155] Air quality monitoring: Monitor air quality through CO2 and other harmful gas sensors, and automatically adjust the operation of the ventilation system as needed.

[0156] Temperature and humidity control: Temperature and humidity sensors can monitor environmental conditions to ensure that ventilation systems maintain the right indoor climate to prevent mold growth or overheating.

[0157] Ventilation on demand: When air quality monitoring shows that fresh air circulation is needed, the ventilation system will automatically increase the air exchange volume, otherwise it will reduce it to save energy.

[0158] Intelligent Adjustment: Based on predictive models and historical data, the system can predict when more ventilation is needed and adjust in advance to maintain optimal air quality and energy efficiency.

[0159] Therefore, this embodiment uses the energy management module 400 to intelligently control the lighting and ventilation systems, thereby avoiding unnecessary energy consumption, reducing operating costs, and reducing carbon emissions, which is in line with the concept of green buildings and sustainable development. Therefore, under the joint cooperation of these modules and the parking space allocation management module 100, the energy efficiency of parking lot operation and maintenance management can be greatly improved, and the user parking experience can be improved.

[0160] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0161] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. Those skilled in the art can also clearly understand that the descriptions of the various embodiments of the present invention have different focuses. For the convenience and brevity of description, the same or similar parts may not be repeated in different embodiments. Therefore, for parts not described or not described in detail in a certain embodiment, refer to the records of other embodiments.

[0162] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0163] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0164] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0165] A person skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by a computer program to instruct the relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned method embodiments. The aforementioned storage medium includes: a read-only memory (ROM) or a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

Claims

1. A comprehensive management background operation and maintenance system, characterized in that: The system comprises: Parking space allocation management module, automatic billing management module, abnormal behavior detection module and energy management module; The automatic billing management module is used to provide automatic payment services and record parking transaction data; The abnormal behavior detection module is used to detect abnormal behavior in the parking lot and trigger an alarm when abnormal behavior is detected. The energy management module is used to automatically adjust the operating status of the lighting system and the ventilation system according to the parking lot usage status; The parking space allocation management module includes: The entrance recommendation unit is used to determine whether the current time is in the peak parking period when a vehicle is detected passing through the parking lot entrance; if so, obtain the queue time information of each entrance of the parking lot, and push the entrance corresponding to the shortest queue time as the recommended entrance to the current vehicle; if not, allow the current vehicle to enter from the current entrance; The parking space allocation unit is used to recognize the license plate of the vehicle passing through the parking lot entrance. When the owner is identified as a visitor and the vehicle is an electric vehicle, the unit obtains the free parking space information, the vehicle location information, the destination location information and the charging pile location information, and establishes a multi-objective optimization model; solves the multi-objective optimization model, and allocates the target parking space to the owner according to the optimal solution; The navigation and positioning unit is used to provide navigation services for the current car owner according to the target parking space, and adopt a dynamic path planning algorithm to update the optimal driving path in real time and push it to the current car owner.

2. The integrated management background operation and maintenance system according to claim 1 is characterized in that: The entry recommendation unit is also used for: The LSTM network model is trained based on the parking lot operation data in the historical period to generate a prediction model; The current time is input into the prediction model to predict whether the current time is in the parking peak period.

3. The integrated management background operation and maintenance system according to claim 1 is characterized in that: The parking space allocation unit is further used for: Determine the distance between each free parking space and the vehicle location, the distance between each free parking space and the destination location, and the distance between each free parking space and the charging pile location, assign weights to each distance, and build a multi-objective optimization model with the goal of minimizing the weighted total distance; Construct constraints based on the time required for parking, the total number of parking spaces in the parking lot, the number of free parking spaces in the parking lot, and the number of available charging piles; Based on the multi-objective optimization model and the constraints, a genetic algorithm or a particle swarm optimization algorithm is used to solve the problem.

4. The integrated management background operation and maintenance system according to claim 1 is characterized in that: The parking space allocation unit is further used for: When the car owner is identified as the householder, the householder's historical parking data is collected and the user's parking behavior preference is analyzed through a clustering algorithm to construct a user profile; the historical parking data includes parking time period, parking frequency and preferred parking space area; The parking needs of household owners are predicted based on user portraits, and parking spaces are allocated to household owners based on the predicted parking needs of household owners.

5. The integrated management background operation and maintenance system according to claim 1 is characterized in that: The navigation and positioning unit is further used for: The driver can identify obstacles or closed areas while driving, and recalculate the driving path when obstacles or closed areas are detected in the path.

6. The integrated management background operation and maintenance system according to claim 1 is characterized in that: The automatic billing management module is also used to record the data generated by each parking transaction using blockchain technology.

7. The integrated management background operation and maintenance system according to claim 1 is characterized in that: The abnormal behaviors include theft, illegal destruction, and staying for longer than the preset time.

8. The integrated management background operation and maintenance system according to claim 7 is characterized in that: The abnormal behavior detection module is also used for: When abnormal behaviors such as theft, illegal destruction, and staying for longer than a preset time are detected in the parking lot, the person who triggered the abnormal behavior will be locked as a monitoring target; Obtain the surveillance video corresponding to the monitored object, extract features from the frame images in the video, and generate a target feature map; The clarity of the target feature map is calculated. When the clarity does not meet the preset value, image enhancement and deblurring operations are performed until the clarity reaches the preset value. The position coordinates of the monitored object in continuous frame images are extracted, and the monitored object is tracked and located based on the continuous position coordinates.

9. The integrated management background operation and maintenance system according to claim 1, characterized in that: The energy management module further includes: The lighting control unit is used to detect the activity status of vehicles and people in the parking lot based on infrared sensors. When vehicle or human activity is detected, the lights in the corresponding area of ​​the parking lot are turned on; when no vehicle or human activity is detected within a preset period of time, the lights are controlled to enter energy-saving lighting mode.

10. The integrated management background operation and maintenance system according to claim 1, characterized in that: The energy management module further includes: A ventilation control unit is used to obtain environmental data and vehicle entry and exit frequency in a parking lot; the environmental data includes carbon dioxide concentration, temperature and humidity; the environmental data and vehicle entry and exit frequency are input into a preset ventilation volume prediction model to predict a target ventilation volume; and the output power of the ventilation system is adjusted according to the difference between the target ventilation volume and the current ventilation volume.

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