Intelligent park management method and system based on artificial intelligence

Abstract

The invention provides a smart park management method and system based on artificial intelligence, and the method comprises the steps: obtaining visitor reservation information, confirming the visitor reservation information, obtaining visitor request information, and judging whether to accept a visitor access request or not according to whether the visitor request information and the visitor reservation information are consistent or not; recommending a parking space for the visitor according to the visitor request and the destination; generating a navigation route for the visitor according to the recommended parking space, comparing that the user driving route is consistent with the navigation route, and if the user driving route is inconsistent with the navigation route, sending alarm information; and adjusting the air conditioner temperature of the visit destination of the visitor in the park based on the visitor driving information. Through the method and the corresponding system, the operation efficiency of the equipment in the park is improved, and the user experience is enhanced.

Description

Technical Field

[0001] The present invention proposes an artificial intelligence-based smart park management method and system, which relate to the technical field of innovation park operation management. Background Art

[0002] A smart park refers to an integrated system that uses modern information technology, including the Internet of Things (IoT), big data analysis, artificial intelligence (AI), cloud computing, and smart sensing technology, to conduct intelligent and automated management of infrastructure, services, security, and environment within the park. Such a park uses highly integrated and optimized technology applications to make park management more efficient, safe, energy-efficient, and environmentally friendly, while also improving the user experience and quality of life within the park.

[0003] In the field of modern park management, with the expansion of park scale and the increase of business activities, park management faces many challenges, such as visitor management, traffic flow control, security monitoring and environmental regulation. Traditional park management systems often rely on manual operation, which is inefficient and cannot meet the needs of rapid response and real-time data processing. Summary of the invention

[0004] The present invention provides a method and system for managing a smart park based on artificial intelligence to solve the above-mentioned problems:

[0005] The present invention proposes a method for managing a smart park based on artificial intelligence, the method comprising:

[0006] Acquire visitor reservation information, confirm the visitor reservation information, acquire visitor request information, and determine whether to accept the visitor access request based on whether the visitor request information is consistent with the visitor reservation information;

[0007] Recommend parking spaces to visitors based on their requests and destinations;

[0008] Generate a navigation route for visitors based on the recommended parking spaces, and compare the user's driving route with the navigation route. If they are inconsistent, send an alarm message;

[0009] Adjust the air conditioning temperature at the destinations that visitors visit within the park based on the visitor's travel information.

[0010] Further, obtaining visitor reservation information, confirming the visitor reservation information, obtaining visitor request information, and determining whether to accept the visitor access request according to whether the visitor request information and the visitor reservation information are consistent, including:

[0011] Obtain visitor reservation information, including user name, contact information, visit destination within the park, user face, reservation date and reservation time period;

[0012] Sending the visitor reservation information to the person in charge of the destination to be visited, and the person in charge of the destination to be visited confirms the visitor reservation information;

[0013] Receive the visitor reservation information confirmed by the person in charge of the visit destination, obtain the visitor request information, and when the visitor request information is consistent with the visitor reservation information, accept the visitor access request; when the visitor request information is not consistent with the visitor reservation information, reject the visitor access request.

[0014] Further, recommend parking spaces to visitors based on their requests and destinations; including:

[0015] Obtain information about available parking spaces within the park, the access control location of visitors entering the park, the visitor's destination within the park, and the weather during the visitor's reservation time period;

[0016] A parking space is recommended for visitors according to a parking space recommendation model. Specifically, the parking space recommendation model is:

[0017]

[0018] in, represents the normalized distance, α, β, γ and δ are weight coefficients, represents the normalized traffic flow, represents the estimated time to reach the parking space, W represents the weather conditions, C pi Indicates the parking space type, G * represents the global traffic flow, I * represents the vehicle inflow rate, I th Indicates the preset threshold of traffic flow,

[0019]

[0020]

[0021] Among them, d pi represents the distance between parking space pi and the visitor's destination in the park, t pi represents the time required to reach parking space pi, T pi It represents the traffic flow detected by the ground sensor circle at parking space pi, G represents the overall traffic flow of the entire park, and I represents the inflow rate of traffic flow, that is, the number of new vehicles.

[0022] Furthermore, a navigation route is generated for the visitor based on the recommended parking space, and the user's driving route is compared with the navigation route. If they are inconsistent, an alarm message is sent, including:

[0023] Generate navigation routes for visitors based on recommended parking spaces and access control locations for visitors to enter the park;

[0024] Use GPS to track the user's driving information in real time, including the user's driving location and driving path, and upload the user's driving information to the central monitoring system;

[0025] The user's driving path uploaded to the central monitoring system is compared with the navigation route generated in advance. When it is detected that the user's driving route is inconsistent with the navigation route and the deviation exceeds the preset threshold, an alarm is automatically triggered and the alarm information is sent to the security personnel.

[0026] Furthermore, the air conditioning temperature of the destination visited by the visitor in the park is adjusted based on the visitor's travel information, including:

[0027] Collect historical temperature adjustment data, traffic flow, outdoor temperature, indoor temperature and visitor arrival time data, obtain visitor estimated arrival time and real-time traffic flow of visitor destinations in the park based on visitor travel paths, and obtain outdoor temperature and indoor temperature through sensors;

[0028] Use historical data and real-time data to construct historical feature vectors and real-time feature vectors respectively;

[0029] Use historical feature vectors to train a temperature prediction model using a machine learning algorithm;

[0030] Optimizing the temperature prediction model weights using regression analysis and cross-validation techniques;

[0031] The real-time feature vector is input into the optimized temperature prediction model to obtain the predicted optimal indoor temperature, and adjustment is performed based on the predicted optimal indoor temperature.

[0032] The present invention proposes an artificial intelligence-based smart park management system, the system comprising:

[0033] A visitor access request acceptance module is used to obtain visitor reservation information, confirm the visitor reservation information, obtain visitor request information, and determine whether to accept the visitor access request based on whether the visitor request information is consistent with the visitor reservation information;

[0034] A parking space recommendation module is used to recommend parking spaces to visitors based on their requests and destinations;

[0035] The route comparison module is used to generate a navigation route for visitors based on the recommended parking spaces and compare the user's driving route with the navigation route. If they are inconsistent, an alarm message is sent;

[0036] The module for adjusting the temperature of the destination visited is used to adjust the air-conditioning temperature of the destination visited by the visitor in the park based on the visitor's travel information.

[0037] Furthermore, the module for determining whether to accept a visitor access request includes:

[0038] A visitor reservation information acquisition module is used to acquire visitor reservation information, wherein the reservation information includes user name, contact information, visit destination within the park, user face, reservation date and reservation time period;

[0039] A confirmation information module, used to send the visitor reservation information to the person in charge of the visit destination, and the person in charge of the visit destination confirms the visitor reservation information;

[0040] The judgment module is used to receive the visitor reservation information confirmed by the person in charge of the visit destination, obtain the visitor request information, and accept the visitor access request when the visitor request information is consistent with the visitor reservation information; when the visitor request information is not consistent with the visitor reservation information, reject the visitor access request.

[0041] Furthermore, the parking space recommendation module includes:

[0042] The visitor information acquisition module is used to obtain the information of available parking spaces in the park, the access control location of visitors entering the park, the visitor's destination in the park, and the weather during the visitor's reservation time period;

[0043] The model-based scoring module is used to recommend parking spaces for visitors based on the parking space recommendation model. Specifically, the parking space recommendation model is:

[0044]

[0045] in, represents the normalized distance, α, β, γ and δ are weight coefficients, represents the normalized traffic flow, represents the estimated time to reach the parking space, W represents the weather conditions, C pi Indicates the parking space type, G * represents the global traffic flow, I * represents the vehicle inflow rate, I th Indicates the preset threshold of traffic flow,

[0046]

[0047] Among them, d pi represents the distance between parking space pi and the visitor's destination in the park, t pi represents the time required to reach parking space pi, T pi It represents the traffic flow detected by the ground sensor circle at parking space pi, G represents the overall traffic flow of the entire park, and I represents the inflow rate of traffic flow, that is, the number of new vehicles.

[0048] Furthermore, the route comparison module includes:

[0049] Generate navigation route module, used to generate navigation routes for visitors based on recommended parking spaces and access control locations for visitors to enter the park;

[0050] A module for tracking user driving information is used to use GPS to track the user's driving information in real time. The driving information includes: the user's driving position and driving path, and upload the user's driving information to the central monitoring system;

[0051] The comparison alarm module is used to compare the user's driving path uploaded to the central monitoring system with the navigation route generated in advance. When it is detected that the user's driving route is inconsistent with the navigation route and the deviation exceeds the preset threshold, an alarm is automatically triggered and the alarm information is sent to the security personnel.

[0052] Further, the module for adjusting the temperature of the access destination includes:

[0053] The module for collecting historical and real-time data is used to collect historical temperature adjustment data, traffic flow, outdoor temperature, indoor temperature and visitor arrival time data, obtain the visitor's estimated arrival time and the real-time traffic flow of the visitor's destination in the park according to the visitor's driving path, and obtain the outdoor temperature and indoor temperature through sensors;

[0054] A feature vector construction module is used to respectively construct a historical feature vector and a real-time feature vector using historical data and real-time data;

[0055] A training model module is used to train a temperature prediction model using a historical feature vector through a machine learning algorithm;

[0056] An optimization weight module, used for optimizing the weight of the temperature prediction model using regression analysis and cross-validation techniques;

[0057] The temperature adjustment module is used to input the real-time feature vector into the optimized temperature prediction model, obtain the predicted optimal indoor temperature, and adjust based on the predicted optimal indoor temperature.

[0058] The beneficial effects of the present invention are as follows: improving security, the system verifies the visitor's reservation information and request information to ensure that only legitimate visitors can enter, effectively increasing the security of the facility; optimizing the parking experience, automatically recommending parking spaces to reduce the time visitors spend looking for parking spaces, improving visitor satisfaction, and at the same time improving the space utilization rate of the parking lot; enhancing the navigation and monitoring effects, the real-time comparison of the automatically generated navigation route and the driving route can promptly detect deviations from the scheduled route and promptly deal with possible safety or misoperation issues; improving the visitor experience, by adjusting the air-conditioning temperature at the destination in real time to ensure that visitors can enjoy a comfortable environment when they arrive, thereby improving the overall experience of the visitors; this technical solution not only improves the operating efficiency of the facility, but also enhances the user experience through the comprehensive use of information verification, intelligent recommendation and environmental regulation, and is an important part of a modern intelligent building management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a schematic diagram of an artificial intelligence-based smart park management method described in the present invention. DETAILED DESCRIPTION

[0060] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0061] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. The embodiments described are only a part of the embodiments of the present invention, rather than 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.

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0063] One embodiment of the present invention provides a method for managing a smart park based on artificial intelligence, the method comprising:

[0064] Acquire visitor reservation information, confirm the visitor reservation information, acquire visitor request information, and determine whether to accept the visitor access request based on whether the visitor request information is consistent with the visitor reservation information;

[0065] Recommend parking spaces to visitors based on their requests and destinations;

[0066] Generate a navigation route for visitors based on the recommended parking spaces, and compare the user's driving route with the navigation route. If they are inconsistent, send an alarm message;

[0067] Adjust the air conditioning temperature at the destinations that visitors visit within the park based on the visitor's travel information.

[0068] The working principle and effect of the above technical solution are as follows: Visitor information verification, in this system, firstly, reservation information is collected from the visitor, and then the visitor's access request information is received. The system compares the two and verifies the consistency of the information to decide whether to allow the visitor to access. This step ensures that only visitors who have made a reservation in advance and whose information is verified to be consistent can enter the facility; Parking space recommendation, the system recommends the most suitable parking space according to the visitor's reservation destination, which can optimize the allocation of parking spaces according to the visitor's exact location and expected destination, thereby saving the visitor's time and improving the efficiency of parking lot use; Navigation route generation and monitoring, the system generates a navigation route for the visitor to reach the recommended parking space, and compares the actual route of the visitor with the navigation route provided by the system by monitoring the route. If the route is found to be inconsistent, the system will automatically issue an alarm message to prompt the security personnel to respond accordingly to ensure the safety of the visitor and the facility; Based on the actual driving information of the visitor, the system adjusts the air conditioning temperature in each destination visited by the visitor. By predicting the arrival time and location of the visitor, the system can adjust the temperature in advance to ensure that the visitor enjoys a comfortable environment when he arrives. Such adjustments are based on real-time data and can effectively improve the visitor's experience. Improve security: the system verifies the visitor's reservation information and request information to ensure that only legitimate visitors can enter, effectively increasing the security of the facility; optimize the parking experience: automatically recommend parking spaces to reduce the time visitors spend looking for parking spaces, improve visitor satisfaction, and at the same time improve the space utilization rate of the parking lot; enhance navigation and monitoring effects: the real-time comparison of the automatically generated navigation route and the driving route can promptly detect deviations from the scheduled route and deal with possible safety or misoperation issues in a timely manner; improve the visitor experience: by adjusting the air-conditioning temperature at the destination in real time, it ensures that visitors can enjoy a comfortable environment when they arrive, thereby improving the overall experience of the visitor; this technical solution not only improves the operating efficiency of the facility, but also enhances the user experience through the comprehensive use of information verification, intelligent recommendation and environmental control. It is an important part of modern intelligent building management systems.

[0069] In one embodiment of the present invention, obtaining visitor reservation information, confirming the visitor reservation information, obtaining visitor request information, and determining whether to accept the visitor access request according to whether the visitor request information and the visitor reservation information are consistent include:

[0070] Obtain visitor reservation information, including user name, contact information, visit destination within the park, user face, reservation date and reservation time period;

[0071] Sending the visitor reservation information to the person in charge of the destination to be visited, and the person in charge of the destination to be visited confirms the visitor reservation information;

[0072] Receive the visitor reservation information confirmed by the person in charge of the visit destination, obtain the visitor request information, and when the visitor request information is consistent with the visitor reservation information, accept the visitor access request; when the visitor request information is not consistent with the visitor reservation information, reject the visitor access request.

[0073] The working principle and effect of the above technical solution are as follows: collecting appointment information, visitors need to provide information including name, contact information, visit destination, facial data, appointment date and appointment time period. This step is completed through a digital platform to ensure that all necessary information is recorded and traceable; information sending and confirmation, the collected visitor appointment information is sent to the person in charge of the visit destination, the person in charge reviews the appointment information, and after confirmation, the confirmed information is fed back to the visitor management system; visitor request verification, when visitors arrive, they need to provide access request information, the system compares and verifies these real-time data with the previously stored appointment information; if the request information provided by the visitor is consistent with the appointment information (such as name, appointment date, time, face matching, etc.), the system accepts the access request and allows the visitor to enter; if the information does not match, the system will reject the visitor's access request. By verifying the visitor's appointment information and the information provided during the actual visit, it is ensured that only pre-approved individuals can enter sensitive or restricted areas. This verification mechanism greatly enhances the security of access control; the automated appointment and verification process reduces the need for manual operation and improves the efficiency of visitor reception. The person in charge can quickly process access requests through digital tools, saving processing time and improving response rate; data accuracy and traceability, all visitor information is recorded in the system, including appointment information and verification results, the integration and accuracy of these data are helpful for auditing and monitoring; customer experience improvement, systematic appointment and fast confirmation process provide a smoother visitor experience. The pre-confirmation mechanism reduces the waiting time on site and clarifies the access requirements in advance; the response capability is enhanced. In specific circumstances (such as security issues), the information of relevant visitors can be quickly located and corresponding processing can be made in time, which improves the efficiency and effectiveness of emergency response; this technical solution integrates information technology and management processes, which not only effectively enhances the safety management of the venue, but also promotes the improvement of operational efficiency and visitor satisfaction. It is suitable for a variety of scenarios that require strict access control and efficient visitor management.

[0074] One embodiment of the present invention recommends a parking space for a visitor based on the visitor's request and destination; comprising:

[0075] Obtain information about available parking spaces within the park, the access control location of visitors entering the park, the visitor's destination within the park, and the weather during the visitor's reservation time period;

[0076] A parking space is recommended for visitors according to a parking space recommendation model. Specifically, the parking space recommendation model is:

[0077]

[0078] in, represents the normalized distance, α, β, γ and δ are weight coefficients, represents the normalized traffic flow, represents the estimated time to reach the parking space, W represents the weather conditions, C pi Indicates the parking space type, G * represents the global traffic flow, I * represents the vehicle inflow rate, I th Indicates the preset threshold of traffic flow,

[0079]

[0080] Among them, d pi represents the distance between parking space pi and the visitor's destination in the park, t pi represents the time required to reach parking space pi, T pi It represents the traffic flow detected by the ground sensor circle at parking space pi, G represents the overall traffic flow of the entire park, and I represents the inflow rate of traffic flow, that is, the number of new vehicles.

[0081] The working principle and effect of the above technical solution are as follows: The purpose of formula design is to provide a unified, smooth and mathematical way to evaluate the score of parking spaces, taking into account factors such as weather conditions and parking space types, using the expression W·S pi , where W and S pi are binary variables that can take values ​​of 0 or 1, which can simplify logical judgments. pi = 1 (underground parking), the value of the expression is 1. In this case, additional consideration is needed because it is more reasonable to park in underground parking spaces on rainy days, and other related factors to form a comprehensive evaluation model. *) makes the score less sensitive to the value. This means that small changes in factors such as distance or time have a greater impact on the score when the value is small (i.e. close to zero), and their impact gradually decreases as the value increases (farther away from zero). This design helps prevent extreme values ​​from having an excessive impact on the total score, making the scoring system smoother and more robust. This method of comprehensively considering multiple factors can more comprehensively evaluate the rationality and pros and cons of parking spaces. Exponential growth or decay characteristics can help the model depict a resilient response mechanism. For example, the form of use can show a rapid decrease in a certain benefit, namely the parking space score, as the distance increases. This is often logical when simulating actual conditions, because many real-world dynamic systems follow similar nonlinear attenuation laws. The use of mathematical expressions makes the formula not only more precise, but also easier to adjust and expand. For example, if the weighting factor needs to be adjusted or a new evaluation dimension needs to be added, it can be easily modified on the existing structure. The adaptability and accuracy of the model can be improved. By adding additional scores for specific situations, the model can more sensitively reflect the actual needs under specific environmental conditions, thereby improving the accuracy and practicality of the overall evaluation. The model can be made more in line with actual conditions: in actual situations, underground parking spaces are indeed more popular than ground parking spaces on rainy days. Through such a design of the model, it is ensured that the scoring system can accurately reflect the actual value of different parking spaces under different conditions. This refined and precise formulation not only makes the model more powerful and flexible, but also helps to provide decision support that is more in line with reality.

[0082] In one embodiment of the present invention, a navigation route is generated for a visitor based on a recommended parking space, and a user's driving route is compared with the navigation route. If they are inconsistent, an alarm message is sent, including:

[0083] Generate navigation routes for visitors based on recommended parking spaces and access control locations for visitors to enter the park;

[0084] Use GPS to track the user's driving information in real time, including the user's driving location and driving path, and upload the user's driving information to the central monitoring system;

[0085] The user's driving path uploaded to the central monitoring system is compared with the navigation route generated in advance. When it is detected that the user's driving route is inconsistent with the navigation route and the deviation exceeds the preset threshold, an alarm is automatically triggered and the alarm information is sent to the security personnel.

[0086] In one embodiment of the present invention, the air conditioning temperature of a visitor's destination in a park is adjusted based on the visitor's travel information, including:

[0087] Collect historical temperature adjustment data, traffic flow, outdoor temperature, indoor temperature and visitor arrival time data, obtain visitor estimated arrival time and real-time traffic flow of visitor destinations in the park based on visitor travel paths, and obtain outdoor temperature and indoor temperature through sensors;

[0088] Use historical data and real-time data to construct historical feature vectors and real-time feature vectors respectively;

[0089] Use historical feature vectors to train a temperature prediction model using a machine learning algorithm;

[0090] Optimizing the temperature prediction model weights using regression analysis and cross-validation techniques;

[0091] The real-time feature vector is input into the optimized temperature prediction model to obtain the predicted optimal indoor temperature, and adjustment is performed based on the predicted optimal indoor temperature.

[0092] Construct the historical feature vector, X = [x 1 , x 2 , x 3 , ..., x n ], where each xi represents a specific input feature, such as historical temperature adjustment data, traffic flow, outdoor temperature, indoor temperature, and visitor arrival time data. The collected feature data X is used to train the temperature prediction model f(X) through a machine learning algorithm (such as random forest or gradient boosting machine). The model outputs the predicted optimal indoor temperature y, which is expressed as:

[0093]

[0094] Use regression analysis and cross-validation techniques to optimize the model weight w and bias b to ensure that the difference between the predicted temperature and the actual demand is minimized. Integrate the optimized model into the intelligent temperature control system, and the system will automatically adjust the air-conditioning temperature based on the model prediction results.

[0095] The working principle and effect of the above technical solution are as follows: data collection, historical data including but not limited to historical indoor and outdoor temperature data, historical temperature adjustment data, human flow data, and related time data, real-time data including current indoor and outdoor temperature, current human flow data, and expected arrival time of visitors obtained through sensors and system interfaces, data processing and feature vector construction, using the collected historical data to construct historical feature vectors, including temperature, human flow, time, etc., constructing real-time feature vectors, including instant temperature readings, real-time human flow and expected arrival time, for real-time temperature adjustment, model training and optimization, using historical feature vectors to train machine learning models (such as random forests or gradient boosting machines) to learn the relationship between environmental variables and temperature settings, using regression analysis and cross-validation techniques to optimize the model's weights and biases to ensure that the predicted temperature is as close to actual demand as possible, and inputting the real-time feature vectors into the optimized temperature prediction model to obtain the predicted optimal indoor temperature. According to the model prediction results, the intelligent temperature control system automatically adjusts the air-conditioning temperature to ensure that the indoor temperature meets the expected settings. Improve energy efficiency and comfort. The system can intelligently adjust the temperature according to predictions and real-time data, reducing energy waste while improving the comfort of the indoor environment. It can automatically adjust the temperature settings for different time periods and different indoor traffic flows to avoid excessive hot and cold. It uses real-time data and machine learning models to dynamically adjust the temperature settings in response to changes in the external environment and internal demand, improving the system's adaptability and response speed. The model reduces prediction errors through continuous learning and optimization to ensure more accurate temperature control. Through automated data collection and analysis, it reduces manual intervention and possible human errors, improving the reliability and efficiency of system operation. The intelligent temperature control system has a high degree of automation and can monitor and adjust the indoor environment in real time, freeing managers from heavy monitoring tasks. This air-conditioning temperature control system based on data-driven and intelligent algorithms can not only improve energy efficiency and indoor comfort, but also represents the progress of intelligent building technology in practical applications, and demonstrates the practical value of big data and artificial intelligence technology in daily life.

[0096] One embodiment of the present invention is a smart park management system based on artificial intelligence, the system comprising:

[0097] A visitor access request acceptance module is used to obtain visitor reservation information, confirm the visitor reservation information, obtain visitor request information, and determine whether to accept the visitor access request based on whether the visitor request information is consistent with the visitor reservation information;

[0098] A parking space recommendation module is used to recommend parking spaces to visitors based on their requests and destinations;

[0099] The route comparison module is used to generate a navigation route for visitors based on the recommended parking spaces and compare the user's driving route with the navigation route. If they are inconsistent, an alarm message is sent;

[0100] The module for adjusting the temperature of the destination visited is used to adjust the air-conditioning temperature of the destination visited by the visitor in the park based on the visitor's travel information.

[0101] In one embodiment of the present invention, a smart park management system based on artificial intelligence, the module for accepting visitor access request includes:

[0102] A visitor reservation information acquisition module is used to acquire visitor reservation information, wherein the reservation information includes user name, contact information, visit destination within the park, user face, reservation date and reservation time period;

[0103] A confirmation information module, used to send the visitor reservation information to the person in charge of the visit destination, and the person in charge of the visit destination confirms the visitor reservation information;

[0104] The judgment module is used to receive the visitor reservation information confirmed by the person in charge of the visit destination, obtain the visitor request information, and accept the visitor access request when the visitor request information is consistent with the visitor reservation information; when the visitor request information is not consistent with the visitor reservation information, reject the visitor access request.

[0105] In one embodiment of the present invention, a smart park management system based on artificial intelligence, the parking space recommendation module includes:

[0106] The visitor information acquisition module is used to obtain the information of available parking spaces in the park, the access control location of visitors entering the park, the visitor's destination in the park, and the weather during the visitor's reservation time period;

[0107] The model-based scoring module is used to recommend parking spaces for visitors based on the parking space recommendation model. Specifically, the parking space recommendation model is:

[0108]

[0109] in, represents the normalized distance, α, β, γ and δ are weight coefficients, represents the normalized traffic flow, represents the estimated time to reach the parking space, W represents the weather conditions, C pi Indicates the parking space type, G * represents the global traffic flow, I * represents the vehicle inflow rate, I th Indicates the preset threshold of traffic flow,

[0110]

[0111] Among them, d pi represents the distance between parking space pi and the visitor's destination in the park, t pi represents the time required to reach parking space pi, T pi It represents the traffic flow detected by the ground sensor circle at parking space pi, G represents the overall traffic flow of the entire park, and I represents the inflow rate of traffic flow, that is, the number of new vehicles.

[0112] In one embodiment of the present invention, a smart park management system based on artificial intelligence, the route comparison module includes:

[0113] Generate navigation route module, used to generate navigation routes for visitors based on recommended parking spaces and access control locations for visitors to enter the park;

[0114] A module for tracking user driving information is used to use GPS to track the user's driving information in real time. The driving information includes: the user's driving position and driving path, and upload the user's driving information to the central monitoring system;

[0115] The comparison alarm module is used to compare the user's driving path uploaded to the central monitoring system with the navigation route generated in advance. When it is detected that the user's driving route is inconsistent with the navigation route and the deviation exceeds the preset threshold, an alarm is automatically triggered and the alarm information is sent to the security personnel.

[0116] In one embodiment of the present invention, a smart park management system based on artificial intelligence, the module for adjusting the temperature of the visited destination includes:

[0117] The module for collecting historical and real-time data is used to collect historical temperature adjustment data, traffic flow, outdoor temperature, indoor temperature and visitor arrival time data, obtain the visitor's estimated arrival time and the real-time traffic flow of the visitor's destination in the park according to the visitor's driving path, and obtain the outdoor temperature and indoor temperature through sensors;

[0118] A feature vector construction module is used to respectively construct a historical feature vector and a real-time feature vector using historical data and real-time data;

[0119] A training model module is used to train a temperature prediction model using a historical feature vector through a machine learning algorithm;

[0120] An optimization weight module, used for optimizing the weight of the temperature prediction model using regression analysis and cross-validation techniques;

[0121] The temperature adjustment module is used to input the real-time feature vector into the optimized temperature prediction model, obtain the predicted optimal indoor temperature, and adjust based on the predicted optimal indoor temperature.

[0122] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for managing a smart park based on artificial intelligence, characterized in that: The method comprises: Acquire visitor reservation information, confirm the visitor reservation information, acquire visitor request information, and determine whether to accept the visitor access request based on whether the visitor request information is consistent with the visitor reservation information; Recommend parking spaces to visitors based on their requests and destinations; Generate a navigation route for visitors based on the recommended parking spaces, and compare the user's driving route with the navigation route. If they are inconsistent, send an alarm message; Adjust the air conditioning temperature at the destinations that visitors visit within the park based on the visitor's travel information.

2. According to claim 1, a method for managing a smart park based on artificial intelligence is characterized in that: Obtaining visitor reservation information, confirming the visitor reservation information, obtaining visitor request information, and determining whether to accept the visitor access request based on whether the visitor request information and the visitor reservation information are consistent, including: Obtain visitor reservation information, including user name, contact information, visit destination within the park, user face, reservation date and reservation time period; Sending the visitor reservation information to the person in charge of the destination to be visited, and the person in charge of the destination to be visited confirms the visitor reservation information; Receive the visitor reservation information confirmed by the person in charge of the visit destination, obtain the visitor request information, and when the visitor request information is consistent with the visitor reservation information, accept the visitor access request; when the visitor request information is not consistent with the visitor reservation information, reject the visitor access request.

3. According to claim 1, a method for managing a smart park based on artificial intelligence is characterized in that: Recommend parking spaces to visitors based on their request and destination; including: Obtain information about available parking spaces within the park, the access control location of visitors entering the park, the visitor's destination within the park, and the weather during the visitor's reservation time period; A parking space is recommended for visitors according to a parking space recommendation model. Specifically, the parking space recommendation model is: in, represents the normalized distance, α, β, γ and δ are weight coefficients, represents the normalized traffic flow, represents the estimated time to reach the parking space, W represents the weather conditions, C pi Indicates the parking space type, G * represents the global traffic flow, I * represents the vehicle inflow rate, I th Indicates the preset threshold of traffic flow, Among them, d pi represents the distance between parking space pi and the visitor's destination in the park, t pi represents the time required to reach parking space pi, T pi It represents the traffic flow detected by the ground sensor circle at parking space pi, G represents the overall traffic flow of the entire park, and I represents the inflow rate of traffic flow, that is, the number of new vehicles.

4. According to claim 1, a method for managing a smart park based on artificial intelligence is characterized in that: Generate a navigation route for visitors based on the recommended parking spaces, and compare the user's driving route with the navigation route. If they are inconsistent, send an alarm message, including: Generate navigation routes for visitors based on recommended parking spaces and access control locations for visitors to enter the park; Use GPS to track the user's driving information in real time, including the user's driving location and driving path, and upload the user's driving information to the central monitoring system; The user's driving path uploaded to the central monitoring system is compared with the navigation route generated in advance. When it is detected that the user's driving route is inconsistent with the navigation route and the deviation exceeds the preset threshold, an alarm is automatically triggered and the alarm information is sent to the security personnel.

5. According to claim 1, a method for managing a smart park based on artificial intelligence is characterized in that: Adjust the air conditioning temperature of the visitor's destination within the park based on the visitor's travel information, including: Collect historical temperature adjustment data, traffic flow, outdoor temperature, indoor temperature and visitor arrival time data, obtain visitor estimated arrival time and real-time traffic flow of visitor destinations in the park based on visitor travel paths, and obtain outdoor temperature and indoor temperature through sensors; Use historical data and real-time data to construct historical feature vectors and real-time feature vectors respectively; Use historical feature vectors to train a temperature prediction model using a machine learning algorithm; Optimizing the temperature prediction model weights using regression analysis and cross-validation techniques; The real-time feature vector is input into the optimized temperature prediction model to obtain the predicted optimal indoor temperature, and adjustment is performed based on the predicted optimal indoor temperature.

6. An artificial intelligence-based smart park management system, characterized in that: The system comprises: A visitor access request acceptance module is used to obtain visitor reservation information, confirm the visitor reservation information, obtain visitor request information, and determine whether to accept the visitor access request based on whether the visitor request information is consistent with the visitor reservation information; A parking space recommendation module is used to recommend parking spaces to visitors based on their requests and destinations; The route comparison module is used to generate a navigation route for visitors based on the recommended parking spaces and compare the user's driving route with the navigation route. If they are inconsistent, an alarm message is sent; The module for adjusting the temperature of the destination visited is used to adjust the air-conditioning temperature of the destination visited by the visitor in the park based on the visitor's travel information.

7. According to claim 6, an artificial intelligence-based smart park management system is characterized in that: The module for accepting visitor access request includes: A visitor reservation information acquisition module is used to acquire visitor reservation information, wherein the reservation information includes user name, contact information, visit destination within the park, user face, reservation date and reservation time period; A confirmation information module, used to send the visitor reservation information to the person in charge of the visit destination, and the person in charge of the visit destination confirms the visitor reservation information; The judgment module is used to receive the visitor reservation information confirmed by the person in charge of the visit destination, obtain the visitor request information, and accept the visitor access request when the visitor request information is consistent with the visitor reservation information; when the visitor request information is not consistent with the visitor reservation information, reject the visitor access request.

8. According to claim 6, an artificial intelligence-based smart park management system is characterized in that: The recommended parking space module includes: The visitor information acquisition module is used to obtain the information of available parking spaces in the park, the access control location of visitors entering the park, the visitor's destination in the park, and the weather during the visitor's reservation time period; The model-based scoring module is used to recommend parking spaces for visitors based on the parking space recommendation model. Specifically, the parking space recommendation model is: in, represents the normalized distance, α, β, γ and δ are weight coefficients, represents the normalized traffic flow, represents the estimated time to reach the parking space, W represents the weather conditions, C pi Indicates the parking space type, G * represents the global traffic flow, I * represents the vehicle inflow rate, I th Indicates the preset threshold of traffic flow, Among them, d pi represents the distance between parking space pi and the visitor's destination in the park, t pi represents the time required to reach parking space pi, T pi It represents the traffic flow detected by the ground sensor circle at parking space pi, G represents the overall traffic flow of the entire park, and I represents the inflow rate of traffic flow, that is, the number of new vehicles.

9. According to claim 6, an artificial intelligence-based smart park management system is characterized in that: The comparison route module includes: Generate navigation route module, used to generate navigation routes for visitors based on recommended parking spaces and access control locations for visitors to enter the park; A module for tracking user driving information is used to use GPS to track the user's driving information in real time. The driving information includes: the user's driving position and driving path, and upload the user's driving information to the central monitoring system; The comparison alarm module is used to compare the user's driving path uploaded to the central monitoring system with the navigation route generated in advance. When it is detected that the user's driving route is inconsistent with the navigation route and the deviation exceeds the preset threshold, an alarm is automatically triggered and the alarm information is sent to the security personnel.

10. According to claim 6, the intelligent park management system based on artificial intelligence is characterized in that: The module for adjusting the temperature of the access destination includes: The module for collecting historical and real-time data is used to collect historical temperature adjustment data, traffic flow, outdoor temperature, indoor temperature and visitor arrival time data, obtain the visitor's estimated arrival time and the real-time traffic flow of the visitor's destination in the park according to the visitor's driving path, and obtain the outdoor temperature and indoor temperature through sensors; A feature vector construction module is used to respectively construct a historical feature vector and a real-time feature vector using historical data and real-time data; A training model module is used to train a temperature prediction model using a historical feature vector through a machine learning algorithm; An optimization weight module, used for optimizing the weight of the temperature prediction model using regression analysis and cross-validation techniques; The temperature adjustment module is used to input the real-time feature vector into the optimized temperature prediction model, obtain the predicted optimal indoor temperature, and adjust based on the predicted optimal indoor temperature.

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