CN117334075A - Intelligent parking method and system based on Internet of things technology - Google Patents
Intelligent parking method and system based on Internet of things technology Download PDFInfo
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Abstract
The invention provides an intelligent parking method and system based on the internet of things technology, which relate to the technical field of intelligent parking and comprise the following steps: the method comprises the steps of carrying out real-time parking space information collection on a target parking lot through an image collection device, obtaining occupied parking space information and idle parking space information with position identification, connecting a user terminal, reading parking requirements of a user, matching the idle parking space information, obtaining M pieces of matched parking space information, sending the M pieces of matched parking space information to the user terminal, carrying out matched parking space display, obtaining first reserved parking space information after a user finishes reservation of a parking space, generating a route planning scheme, marking the first parking space position as reserved, generating an entrance reminding, integrating, generating reservation success information and sending the reservation success information to the user. The invention solves the technical problems that the parking space distribution of the traditional parking lot is scattered, effective management and scheduling are difficult to carry out, and the user is lack of fine service and personalized recommendation, so that a plurality of inconveniences exist in the parking process of the user.
Description
Technical Field
The invention relates to the technical field of intelligent parking, in particular to an intelligent parking method and system based on the internet of things technology.
Background
With the acceleration of the urban process and the increase of the automobile possession, the urban traffic situation is more and more congested, the parking difficulty is increased along with the increase of the urban traffic situation, and a plurality of inconveniences are brought to the travel of people. Therefore, the intelligent parking is widely focused and supported by governments and society as an important component of intelligent city construction, and popularization and application of the intelligent parking can improve urban traffic conditions, improve the utilization rate of parking lot resources and promote urban sustainable development. The current intelligent parking method has a certain disadvantage, and a certain lifting space exists for intelligent parking.
Disclosure of Invention
The intelligent parking method and system based on the Internet of things technology aim to solve the technical problems that parking space distribution in a traditional parking lot is scattered, effective management and scheduling are difficult to perform, and refined service and personalized recommendation to users are lacked, so that inconvenience exists in the parking process of the users.
In view of the above problems, the present application provides an intelligent parking method and system based on the internet of things technology.
In a first aspect of the disclosure, an intelligent parking method based on internet of things is provided, the method comprising: acquiring real-time parking space information of a target parking lot through the image acquisition device, and acquiring occupied parking space information and idle parking space information with position identification; connecting a user end and reading the parking requirements of the user; matching the idle parking space information according to the parking requirements of the users to obtain M pieces of matched parking space information, wherein M is a positive integer greater than 1; the M pieces of matched parking space information are sent to the user terminal to display the matched parking spaces, and after a user finishes parking space reservation, first reserved parking space information is obtained, wherein the first reserved parking space information comprises a first parking space position and a first reserved time period; generating a route planning scheme according to the first vehicle position; marking the first vehicle location as reserved according to the first reserved period, and generating an entrance reminder; integrating the first vehicle position, the first reservation period, the route planning scheme and the entrance reminding, generating reservation success information and sending the reservation success information to the user.
In another aspect of the present disclosure, there is provided an intelligent parking system based on internet of things, the system comprising: the parking space information acquisition module is used for acquiring real-time parking space information of a target parking lot through the image acquisition device and acquiring occupied parking space information and idle parking space information with position identification; the parking demand acquisition module is used for connecting a user terminal and reading the parking demand of the user; the matching parking space acquisition module is used for matching the idle parking space information according to the parking requirements of the user to acquire M pieces of matching parking space information, wherein M is a non-negative integer; the matched parking space display module is used for sending the M pieces of matched parking space information to the user terminal to display the matched parking space, and after a user finishes parking space reservation, the first reserved parking space information is obtained and comprises a first parking space position and a first reserved time period; the route planning generation module is used for generating a route planning scheme according to the first vehicle position; the entrance reminding generation module is used for marking the first vehicle position as reserved according to the first reserved time period and generating an entrance reminding; and the reservation information sending module is used for integrating the first vehicle position, the first reservation period, the route planning scheme and the entrance reminding, generating reservation success information and sending the reservation success information to the user.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the method comprises the steps of carrying out real-time parking space information collection on a target parking lot through an image collection device, obtaining occupied parking space information and idle parking space information with position identification, connecting a user terminal, reading parking requirements of a user, matching the idle parking space information, obtaining M pieces of matched parking space information, sending the M pieces of matched parking space information to the user terminal, carrying out matched parking space display, obtaining first reserved parking space information after a user finishes reservation of a parking space, generating a route planning scheme, marking the first parking space position as reserved, generating an entrance reminding, integrating, generating reservation success information and sending the reservation success information to the user. The intelligent parking lot has the advantages that the technical problems that the parking space distribution is scattered, effective management and scheduling are difficult to perform, the user is lack of refined service and personalized recommendation, various inconveniences exist in the parking process of the user are solved, the real-time monitoring and management of the parking space states through equipment such as a camera are achieved, idle parking space information is provided more conveniently and rapidly, the parking lot resource utilization rate is optimized, and accurate parking space recommendation and route planning service are provided for the user through an intelligent algorithm and data analysis, so that the technical effects of optimizing user experience and satisfaction are achieved.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
Fig. 1 is a schematic flow chart of an intelligent parking method based on the internet of things technology according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a possible process of obtaining information of an occupied parking space and information of an idle parking space in an intelligent parking method based on the internet of things technology according to an embodiment of the present application;
fig. 3 is a schematic diagram of a possible structure of an intelligent parking system based on the internet of things technology according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a parking space information acquisition module 10, a parking demand acquisition module 20, a matching parking space acquisition module 30, a matching parking space display module 40, a route planning generation module 50, an entrance reminding generation module 60 and a reservation information transmission module 70.
Detailed Description
According to the intelligent parking method based on the Internet of things, the technical problems that parking space distribution is scattered, effective management and scheduling are difficult to conduct, and refined service and personalized recommendation for users are lacked, so that a plurality of inconveniences exist in the parking process of the users are solved, the real-time monitoring and management of parking space states through equipment such as cameras are achieved, idle parking space information is provided more conveniently and rapidly, accordingly the resource utilization rate of a parking lot is optimized, and accurate parking space recommendation and route planning service are provided for the users through intelligent algorithm and data analysis, so that the technical effects of optimizing user experience and satisfaction are achieved.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Example 1
As shown in fig. 1, an embodiment of the present application provides an intelligent parking method based on the internet of things technology, where the method includes:
step S100: acquiring real-time parking space information of a target parking lot through the image acquisition device, and acquiring occupied parking space information and idle parking space information with position identification;
specifically, the intelligent parking method based on the internet of things is applied to an intelligent parking system based on the internet of things, the intelligent parking system based on the internet of things is in communication connection with an image acquisition device, and the image acquisition device is used for acquiring real-time parking space information of a target parking lot.
Further, as shown in fig. 2, step S100 of the present application further includes:
step S110: carrying out digital marking on each parking space in the target parking lot;
step S120: a plurality of image acquisition devices are arranged for real-time panoramic image acquisition, wherein the image acquisition devices comprise all parking spaces and digital marks thereof;
step S130: and detecting the vehicle according to the image acquisition result, and carrying out position identification according to the digital mark to acquire the occupied parking space information and the idle parking space information.
In particular, a label, sign or electronic identification device or the like is used to mark the parking space so that its position can be determined later. And arranging a plurality of image acquisition devices in the parking lot, wherein the image acquisition devices are used for acquiring panoramic images of the parking lot in real time and capturing digital marks of each parking space. In practical application, a camera with high definition, wide angle view and low illumination is selected as an image acquisition device. Meanwhile, because the parking space is large, the number and the position distribution of the acquisition devices are required to be determined according to actual conditions, so that the coverage range of the acquisition devices can meet all parking spaces.
Processing the acquired image data, and firstly, detecting a vehicle by using a deep learning method to identify the vehicle parked on a parking space; and then accurately identifying and matching the digital marks, carrying out position identification according to the digital marks of each parking place, determining which parking places are occupied and which parking places are idle, counting the number of occupied parking places and the number of idle parking places, and generating occupied parking place information and idle parking place information.
Step S200: connecting a user end and reading the parking requirements of the user;
specifically, a network protocol is used to establish a two-way communication connection with the user terminal, and the parking requirement of the user is read through the connection, for example, the user can express the parking requirement by inputting a license plate number, selecting a destination and a parking time period. The user request is parsed and processed, for example, matching recommended exits from a plurality of exits based on a destination provided by the user, and space matching is performed near the recommended exits.
Step S300: matching the idle parking space information according to the parking requirements of the users to obtain M pieces of matched parking space information, wherein M is a non-negative integer;
further, step S300 of the present application further includes:
step S310: acquiring a preset label scheme;
step S320: according to the preset label scheme, carrying out label marking on the user parking requirement and the idle parking space information to obtain a user label vector and N parking space label vectors, wherein N is a positive integer greater than 1;
step S330: performing similarity calculation on the user tag vector and the N stall tag vectors to obtain N similarity indexes;
in particular, the system defines a set of label systems in advance, and the systems can comprise labels with multiple dimensions of parking time period, parking space position, price, size, parking space type and the like, and the labels form the preset label scheme.
For parking demand information provided by a user, converting the parking demand information into a user tag vector, describing various aspects of the user demand through tag marking, for example, performing tag marking according to information such as license plate numbers, vehicle types, parking time periods and the like; for the acquired idle parking space information, the acquired idle parking space information is converted into a parking space label vector, and various aspects of the parking space are described through label marking, for example, the label marking is carried out according to the information of the parking space position, the idle time period, the price, the size, the parking space type and the like.
Because the labels of the user demand and the idle parking space information may have the condition of incomplete matching, before similarity calculation is performed, the labels are subjected to unified processing, and a specific method may be to consider the labels which are not mentioned in the user demand as the same labels as those in the idle parking space information.
Further, step S330 of the present application further includes:
step S331: calling historical parking data of the user;
step S332: carrying out demand trend analysis on the historical parking data, and setting a label coefficient according to an analysis result;
step S333: and calculating the similarity between the user tag vector and the N parking space tag vectors according to the tag coefficients, wherein the similarity calculation formula is as follows:
P(X i ，X)＝W 1 Q 1 +W 2 Q 2 +...W n Q n
wherein X is i Is the ith parking space label vector, X is the user label vector, P (X i X) is the ith similarity, Q 1 、Q 2 、...Q n For the matching result of the ith parking space label vector and the user label vector, 1 is taken when the matching is consistent, 0 is taken when the matching is inconsistent, W is taken 1 、W 2 、...W n Is a label coefficient.
Specifically, historical parking data of the user is obtained, including information of parking time, parking position, parking space size and the like, and the data can be input from a smart parking system, a third party application or manually by the user. Demand trending analysis is performed on the historical parking data of users to determine user preferences and importance for parking space selection, e.g., some users may be more focused on the geographic location of the parking space, while some users may be more focused on the price and size of the parking space. And setting weight coefficients for different labels according to the result of the demand trend analysis so as to more accurately match the parking demands of users.
It is noted that the matching of the parking periods is a big precondition for the matching of the parking periods, so that a larger proportion of weight needs to be given to the parking periods in the labels, for example, the label coefficient of the parking periods is set to be 60%. Meanwhile, in order to improve the matching effect, the comprehensive influence of a plurality of factors, such as traffic conditions, parking lot capacity and the like, needs to be considered so as to more comprehensively evaluate the suitability of the parking spaces.
The ith parking space label vector in the N parking space label vectors is obtained, N labels in the ith parking space label vector are matched with labels in the user label vector, wherein labels which are not mentioned in the user label vector are used as matched labels, the labels which are matched and consistent are marked as 1, the labels which are not matched are marked as 0, and a matching result Q of the N labels is obtained 1 、Q 2 、...Q n Substituting the label matching result and the corresponding label coefficient into the formula to carry out weighted summation, and calculating to obtain the ith similarity of the ith parking space label vector and the user label vector.
And carrying out similarity calculation on the N stall label vectors sequentially by adopting the calculation method to obtain N similarity indexes, wherein the larger the similarity indexes are, the more the stall is matched with the user requirement.
Step S340: and arranging the N similarity indexes in a descending order, extracting M pieces of idle parking space information corresponding to the first M pieces of similarity indexes meeting a preset similarity threshold, and taking the M pieces of idle parking space information and the ordering information thereof as M pieces of matching parking space information.
Specifically, the above-mentioned label coefficient of the parking period is set as the preset similarity threshold, and the exemplary label coefficient of the parking period is 60%, and the preset similarity threshold is also 60%, that is, only when the parking period is satisfied, there is a matching parking space. The preset similarity threshold may be adjusted according to practical situations, for example, setting a higher similarity threshold may improve matching accuracy, but may reduce the number of matching results.
And arranging the similarity indexes in a descending order, extracting M pieces of idle parking space information corresponding to the first M pieces of similarity indexes meeting a preset similarity threshold, and returning the information as matching parking space information to a user.
Further, step S300 of the present application further includes:
step S350: when M is 0, generating reservation failure reminding;
step S360: the reservation failure prompt is sent to a user, the user is prompted to input a parking requirement again, an updated parking requirement is obtained, and the idle parking space information is matched according to the updated parking requirement;
step S370: and if the matching result is still not 0, connecting other parking lots nearby, and recommending the matching parking spaces.
Specifically, if a matching parking space cannot be found according to the parking requirement of the user, namely, m=0, a reservation failure prompt is generated, the reservation failure prompt is sent to the user, the user is prompted to input the parking requirement again, and the idle parking space information is matched again according to the updated parking requirement. If the proper parking space cannot be found in the current parking lot, other parking lots nearby are connected, and the matched parking lot and parking space are tried to be found and recommended to the user through technologies such as vehicle positioning, parking lot database query and the like.
Step S400: the M pieces of matched parking space information are sent to the user terminal to display the matched parking spaces, and after a user finishes parking space reservation, first reserved parking space information is obtained, wherein the first reserved parking space information comprises a first parking space position and a first reserved time period;
specifically, the M matched parking space information is sent to a user terminal for display, the information comprises parking space number, position, price and the like, after a user selects a proper parking space on a display interface, reservation operation is needed to be completed, a reservation request is sent to an intelligent parking system, and if reservation is successful, reservation parking space information is fed back; if the failure occurs, a corresponding error prompt is fed back. First location information of the user's reservation, including its location and reservation period, is recorded, which will be used for subsequent route planning and entry reminder functions.
Step S500: generating a route planning scheme according to the first vehicle position;
further, step S500 of the present application further includes:
step S510: acquiring the current position of a user, and generating a recommendation inlet according to the current position;
step S520: the real-time parking data in the target parking lot is called to generate a graph structure containing road information, wherein an intersection in the target parking lot is a node of the graph structure; the paths between adjacent nodes are edges of the graph structure;
step S530: and taking the recommended entry as a starting point, taking the first vehicle position as an end point, evaluating and sequencing each node, obtaining a path of the optimized objective function, and generating a route planning scheme.
Specifically, the user's current location information is obtained, and recommended parking lot entries are generated according to the current location, and the recommended entries may be ordered based on various strategies, such as distance, road traffic, etc. And (3) retrieving real-time parking data in the target parking lot, wherein the real-time parking data comprise information such as the occupation condition of a parking space in the parking lot, the vehicle flow and the like, and integrating the information into a graph structure containing road information. In the graph structure, intersections in the parking lot are used as nodes of the graph structure, and roads between adjacent nodes are edges of the graph structure.
Preprocessing the graph structure by taking the recommended entry as a starting point and the first vehicle position as an ending point, for example, calculating heuristic valuation functions from each node to the ending point by using an A-type algorithm (a direct search algorithm for solving the shortest path in a static network), calculating information such as distance between nodes, road traffic situation and the like, sequentially searching paths from the starting point to the ending point on the graph structure, and evaluating the searched paths, wherein the evaluated indexes can comprise path length, road traffic situation, parking space occupation situation and the like.
The paths are sequenced according to the evaluation result, the optimal paths meeting the conditions are screened out, the optimal paths are converted into a visualized route planning scheme, the visualized route planning scheme is displayed to a user, and the scheme can comprise specific information such as routes, turning prompts, estimated time consumption and the like.
Step S600: marking the first vehicle location as reserved according to the first reserved period, and generating an entrance reminder;
step S700: integrating the first vehicle position, the first reservation period, the route planning scheme and the entrance reminding, generating reservation success information and sending the reservation success information to the user.
Specifically, in the reservation period of the first parking space, the state of the parking space reserved by the user is marked as reserved, reservation information is stored in the system database, and at this time, other users cannot select the parking space to park. A corresponding entry alert is generated according to the reserved period, alerting the user when to enter the parking lot, e.g., alerting the first 15 minutes of the reserved period.
The method comprises the steps of acquiring information such as a first vehicle position, a reservation period, a route planning scheme, an entrance reminding and the like reserved by a user from the previous steps, integrating the reservation success information into one message, pushing the reservation success information to the user, and realizing the reservation success information through modes such as short messages, APP pushing and electronic mail.
Further, the present application further includes:
step S810: generating a confirmation time node according to the first reservation parking space information;
step S820: and when the first vehicle position is unoccupied in the confirmation time node, canceling the reserved vehicle position and adding the reserved vehicle position into an idle vehicle position list again.
Specifically, a certain confirmation time node is reserved according to the reservation period of the user so as to confirm whether the user uses the parking space on time, for example, the user arrives at the parking space position 10 minutes after the reservation period starts. After confirming the time node, checking whether the state of the parking space is occupied, if so, indicating that the user has used the parking space without any operation; if the parking space is not occupied, a cancel operation is needed, the parking space state reserved by the user is marked as idle, and the parking space state is added into the idle parking space list again for other users to use.
In summary, the intelligent parking method and system based on the internet of things technology provided by the embodiment of the application have the following technical effects:
the method comprises the steps of carrying out real-time parking space information collection on a target parking lot through an image collection device, obtaining occupied parking space information and idle parking space information with position identification, connecting a user terminal, reading parking requirements of a user, matching the idle parking space information, obtaining M pieces of matched parking space information, sending the M pieces of matched parking space information to the user terminal, carrying out matched parking space display, obtaining first reserved parking space information after a user finishes reservation of a parking space, generating a route planning scheme, marking the first parking space position as reserved, generating an entrance reminding, integrating, generating reservation success information and sending the reservation success information to the user.
The intelligent parking lot has the advantages that the technical problems that the parking space distribution is scattered, effective management and scheduling are difficult to perform, the user is lack of refined service and personalized recommendation, various inconveniences exist in the parking process of the user are solved, the real-time monitoring and management of the parking space states through equipment such as a camera are achieved, idle parking space information is provided more conveniently and rapidly, the parking lot resource utilization rate is optimized, and accurate parking space recommendation and route planning service are provided for the user through an intelligent algorithm and data analysis, so that the technical effects of optimizing user experience and satisfaction are achieved.
Example two
Based on the same inventive concept as the intelligent parking method based on the internet of things in the foregoing embodiment, as shown in fig. 3, the present application provides an intelligent parking system based on the internet of things, the system includes:
the parking space information acquisition module 10 is used for acquiring real-time parking space information of a target parking lot through the image acquisition device, and acquiring occupied parking space information and idle parking space information with position identification;
the parking demand acquisition module 20, wherein the parking demand acquisition module 20 is used for connecting a user terminal and reading the parking demand of the user;
the matching parking space acquisition module 30 is used for matching the idle parking space information according to the parking requirements of the user to acquire M pieces of matching parking space information, wherein M is a non-negative integer;
the matched parking space display module 40 is used for sending the M pieces of matched parking space information to the user terminal to display the matched parking space, and after the user finishes parking space reservation, first reserved parking space information is obtained, wherein the first reserved parking space information comprises a first vehicle position and a first reserved time period;
a route plan generating module 50, where the route plan generating module 50 is configured to generate a route plan according to the first vehicle location;
an entrance reminder generation module 60, where the entrance reminder generation module 60 is configured to mark the first vehicle location as reserved according to the first reserved period, and generate an entrance reminder;
the reservation information sending module 70 is configured to integrate the first vehicle location, the first reservation period, the route planning scheme, and the entrance reminder, generate reservation success information, and send the reservation success information to the user.
Further, the system further comprises:
the digital marking module is used for digitally marking each parking space in the target parking lot;
the panoramic image acquisition module is used for arranging a plurality of image acquisition devices to acquire real-time panoramic images, and comprises all parking spaces and digital marks thereof;
and the position identification module is used for detecting the vehicle according to the image acquisition result, and carrying out position identification according to the digital mark to acquire the occupied parking space information and the idle parking space information.
Further, the system further comprises:
the label scheme acquisition module is used for acquiring a preset label scheme;
the label marking module is used for marking the user parking requirement and the idle parking space information according to the preset label scheme to obtain a user label vector and N parking space label vectors, wherein N is a positive integer greater than 1;
the similarity calculation module is used for calculating the similarity of the user tag vector and the N stall tag vectors to obtain N similarity indexes;
the matching parking space information acquisition module is used for arranging the N similarity indexes in a descending order, extracting M pieces of idle parking space information corresponding to the first M pieces of similarity indexes meeting a preset similarity threshold, and taking the M pieces of idle parking space information and the ordering information thereof as M pieces of matching parking space information.
Further, the system further comprises:
the historical parking data calling module is used for calling the historical parking data of the user;
the demand trend analysis module is used for carrying out demand trend analysis on the historical parking data and setting a label coefficient according to an analysis result;
the calculating module is used for calculating the similarity between the user tag vector and the N parking space tag vectors according to the tag coefficients, wherein the similarity calculating formula is as follows:
P(X i ，X)＝W 1 Q 1 +W 2 Q 2 +...W n Q n
wherein X is i Is the ith parking space label vector, X is the user label vector, P (X i X) is the ith similarity, Q 1 、Q 2 、...Q n Is the ith parking space label vector and the user label vectorWhen the matching is consistent, 1 is fetched, when the matching is inconsistent, 0 is fetched, W 1 、W 2 、...W n Is a label coefficient.
Further, the system further comprises:
the reservation failure reminding generation module is used for generating reservation failure reminding when M is 0;
the reservation failure reminding sending module is used for sending the reservation failure reminding to a user, prompting the user to input a parking requirement again, acquiring an updated parking requirement, and matching the idle parking space information according to the updated parking requirement;
and the matching parking space recommending module is used for connecting other nearby parking lots to recommend the matching parking spaces if the matching result is not 0 yet.
Further, the system further comprises:
the recommendation inlet generation module is used for acquiring the current position of the user and generating a recommendation inlet according to the current position;
the graphic structure generation module is used for calling the real-time parking data in the target parking lot and generating a graphic structure containing road information, wherein an intersection in the target parking lot is a node of the graphic structure; the paths between adjacent nodes are edges of the graph structure;
and the path planning module is used for taking the recommended entrance as a starting point, taking the first vehicle position as an end point, evaluating and sequencing each node, acquiring the path of the optimized objective function and generating a route planning scheme.
Further, the system further comprises:
the confirmation time node generation module is used for generating a confirmation time node according to the first reserved parking space information;
and the reserved parking space canceling module is used for canceling the reserved parking space and re-adding the reserved parking space into an idle parking space list when the first parking space position is not occupied at the confirmation time node.
Through the foregoing detailed description of a smart parking method based on the internet of things, those skilled in the art can clearly know a smart parking method and a smart parking system based on the internet of things in the present embodiment, and for the device disclosed in the embodiment, the description is relatively simple because it corresponds to the method disclosed in the embodiment, and the relevant points refer to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. The intelligent parking method based on the internet of things is characterized by being applied to an intelligent parking system, wherein the intelligent parking system is in communication connection with an image acquisition device, and the method comprises the following steps:
acquiring real-time parking space information of a target parking lot through the image acquisition device, and acquiring occupied parking space information and idle parking space information with position identification;
connecting a user end and reading the parking requirements of the user;
matching the idle parking space information according to the parking requirements of the users to obtain M pieces of matched parking space information, wherein M is a positive integer greater than 1;
the M pieces of matched parking space information are sent to the user terminal to display the matched parking spaces, and after a user finishes parking space reservation, first reserved parking space information is obtained, wherein the first reserved parking space information comprises a first parking space position and a first reserved time period;
generating a route planning scheme according to the first vehicle position;
marking the first vehicle location as reserved according to the first reserved period, and generating an entrance reminder;
integrating the first vehicle position, the first reservation period, the route planning scheme and the entrance reminding, generating reservation success information and sending the reservation success information to the user.
2. The method of claim 1, wherein acquiring, by the image acquisition device, real-time parking space information of the target parking lot, the occupied parking space information and the free parking space information with the position identification, comprises:
carrying out digital marking on each parking space in the target parking lot;
a plurality of image acquisition devices are arranged for real-time panoramic image acquisition, wherein the image acquisition devices comprise all parking spaces and digital marks thereof;
and detecting the vehicle according to the image acquisition result, and carrying out position identification according to the digital mark to acquire the occupied parking space information and the idle parking space information.
3. The method of claim 1, wherein matching the free space information according to the user's parking needs to obtain M matched space information, wherein M is a positive integer greater than 1, comprises:
acquiring a preset label scheme;
according to the preset label scheme, carrying out label marking on the user parking requirement and the idle parking space information to obtain a user label vector and N parking space label vectors, wherein N is a positive integer greater than 1;
performing similarity calculation on the user tag vector and the N stall tag vectors to obtain N similarity indexes;
and arranging the N similarity indexes in a descending order, extracting M pieces of idle parking space information corresponding to the first M pieces of similarity indexes meeting a preset similarity threshold, and taking the M pieces of idle parking space information and the ordering information thereof as M pieces of matching parking space information.
4. The method of claim 3, wherein performing similarity calculation on the user tag vector and the N parking space tag vectors to obtain N similarity indexes comprises:
calling historical parking data of the user;
carrying out demand trend analysis on the historical parking data, and setting a label coefficient according to an analysis result;
and calculating the similarity between the user tag vector and the N parking space tag vectors according to the tag coefficients, wherein the similarity calculation formula is as follows:
P(X i ，X)＝W 1 Q 1 +W 2 Q 2 +…W n Q n
wherein X is i Is the ith parking space label vector, X is the user label vector, P (X i X) is the ith similarity, Q 1 、Q 2 、…Q n For the matching result of the ith parking space label vector and the user label vector, 1 is taken when the matching is consistent, 0 is taken when the matching is inconsistent, W is taken 1 、W 2 、…W n Is a label coefficient.
5. The method of claim 1, wherein the matching the free space information according to the user parking demand obtains M matching space information, wherein M is a positive integer greater than 1, further comprising:
when M is 0, generating reservation failure reminding;
the reservation failure prompt is sent to a user, the user is prompted to input a parking requirement again, an updated parking requirement is obtained, and the idle parking space information is matched according to the updated parking requirement;
and if the matching result is still not 0, connecting other parking lots nearby, and recommending the matching parking spaces.
6. The method of claim 1, wherein generating a routing plan based on the first location comprises:
acquiring the current position of a user, and generating a recommendation inlet according to the current position;
the real-time parking data in the target parking lot is called to generate a graph structure containing road information, wherein an intersection in the target parking lot is a node of the graph structure; the paths between adjacent nodes are edges of the graph structure;
and taking the recommended entry as a starting point, taking the first vehicle position as an end point, evaluating and sequencing each node, obtaining a path of the optimized objective function, and generating a route planning scheme.
7. The method as recited in claim 1, further comprising:
generating a confirmation time node according to the first reservation parking space information;
and when the first vehicle position is unoccupied in the confirmation time node, canceling the reserved vehicle position and adding the reserved vehicle position into an idle vehicle position list again.
8. An intelligent parking system based on the internet of things technology, which is characterized in that the intelligent parking system is in communication connection with an image acquisition device and is used for implementing the intelligent parking method based on the internet of things technology as claimed in claims 1-7, and comprises the following steps:
the parking space information acquisition module is used for acquiring real-time parking space information of a target parking lot through the image acquisition device and acquiring occupied parking space information and idle parking space information with position identification;
the parking demand acquisition module is used for connecting a user terminal and reading the parking demand of the user;
the matching parking space acquisition module is used for matching the idle parking space information according to the parking requirements of the user to acquire M pieces of matching parking space information, wherein M is a non-negative integer;
the matched parking space display module is used for sending the M pieces of matched parking space information to the user terminal to display the matched parking space, and after a user finishes parking space reservation, the first reserved parking space information is obtained and comprises a first parking space position and a first reserved time period;
the route planning generation module is used for generating a route planning scheme according to the first vehicle position;
the entrance reminding generation module is used for marking the first vehicle position as reserved according to the first reserved time period and generating an entrance reminding;
and the reservation information sending module is used for integrating the first vehicle position, the first reservation period, the route planning scheme and the entrance reminding, generating reservation success information and sending the reservation success information to the user.
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| CN117809481A (en) * | 2024-02-29 | 2024-04-02 | 泰安市东信智联信息科技有限公司 | Urban intelligent parking optimal recommendation system |
| CN117809481B (en) * | 2024-02-29 | 2024-05-07 | 泰安市东信智联信息科技有限公司 | Urban intelligent parking optimal recommendation system |
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