Real-time parking management system with RFID, IoT sensors and mobile communication

Abstract

A real-time parking management system (100) comprising: a plurality of RFID tags (1) each assigned to a vehicle, wherein the RFID tags (1) are configured to store a unique vehicle identifier; a plurality of RFID readers (2) positioned at the entry and exit points of a parking facility, wherein the RFID readers (2) are configured to detect the RFID tags (1) and read the vehicle identifier; a plurality of visual sensors (3) positioned at parking spaces, entry and exit points, configured to capture images or video feeds to verify vehicle occupancy, detect unauthorized parking, and assist with license plate recognition;a machine learning module (4) configured to analyze historical parking data to predict peak parking times, optimize parking space allocation based on vehicle type, size, and user preferences, and enhance security by detecting suspicious activity based on visual sensor data; a central server (5) configured to receive vehicle identification from the RFID readers (2), process input from the visual sensors (3), confirm vehicle presence, access a database to retrieve and store vehicle information, dynamically allocate parking spaces based on availability, vehicle classification, and user preferences, track parking duration for each vehicle, and control entry and exit gates based on verified credentials and security policies;and a user interface unit (6) configured to allow users to reserve parking spaces, display parking space availability in real time, facilitate payment of parking fees using integrated payment gateways, provide step-by-step navigation support to assigned parking spaces, and inform users about parking status, entry confirmations, and security alerts.

Description

FIELD OF THE INVENTIONThe present invention relates to a real-time parking management system employing RFID technology, visual sensors, machine learning and a central server for efficient and automated parking management.More specifically, it is a system for optimizing parking space management, enhancing safety, and improving user-friendliness through an integrated interface.BACKGROUND OF THE INVENTIONThe article treated in the background section should not be considered to be prior art solely because of its mention in the background section. Likewise, it should not be assumed that a problem mentioned in the background section or associated with the subject matter of the background section has already been recognized in the prior art. The subject matter of the background section merely represents various approaches, which may likewise be inventions per se.Efficient management of parking spaces has become a major challenge in urban environments. Conventional parking systems often suffer from inefficiencies such as lack of real-time tracking of space availability, unauthorized entry, and jams at burst times. The present invention addresses these challenges by utilizing RFID technology, loT-enabled sensors, and machine learning algorithms to provide real-time updates and optimized parking solutions.The information disclosed in this Background section is merely for enhancement of understanding of the background of the invention and therefore may contain information that is not prior art and that is already known to a person of ordinary skill in the art in this country.SUMMARYBefore describing the present systems and methods, it should be appreciated that this application is not limited to the described systems and methods, as there may be several possible embodiments that are not expressly depicted in the present disclosure. It is also to be understood that the terminology used in the specification is for the purpose of describing particular versions or embodiments only and is not intended to limit the scope of the present application.The present invention provides a real-time parking management system that automates the allocation, monitoring, and security of parking spaces using RFID technology, loT sensors, and machine learning. The system includes several components including RFID tags, RFID readers, visual sensors, a machine learning module, a central server, and a user interface unit. The invention ensures safe, efficient and user-friendly parking space management with real-time monitoring and predictive analysis.BRIEF DESCRIPTION OF THE DRAWINGIn order to clarify various aspects of some embodiments of the present invention, a more detailed description of the invention will be given by reference to specific embodiments illustrated in the accompanying drawings. It is understood that this drawing shows only illustrated embodiments of the invention and therefore should not be considered as limiting its scope. The invention will be described and explained with additional specificity and detail through the use of the accompanying drawings.In order that the advantages of the present invention may be readily understood, a detailed description of the invention will be discussed below in connection with the accompanying drawing, which, however, should not be taken as a limitation of the scope of the invention to the accompanying drawing, in which: FIG. 1 shows the block diagram of a real-time parking management system ( 100) that uses RFID, loT sensors, and mobile.DETAILED DESCRIPTIONThe present invention relates to a real-time parking management system (100) that utilizes RFID, loT sensors, and mobile.The real-time parking management system (100) is comprised of multiple integrated components that cooperate to provide a seamless parking experience.RFID tags (1): The system (100) comprises a plurality of RFID tags (1) each associated with a vehicle. These RFID tags ( 1) store unique vehicle identifiers and enable contactless vehicle identification at the entry and exit points of the parking facility.RFID readers (2): The RFID readers (2) positioned at the entrance and exit of the parking facility recognize the RFID tags (1) and call the vehicle identifier. The acquired data are transmitted to the central server (5) for further processing.Visual sensors (3): A plurality of visual sensors (3) are used throughout the parking facility, including the entrance, exit and individual parking spaces. These sensors (3) capture images and videos in real time to verify vehicle occupancy, detect unauthorized parking, and support license plate detection for security purposes.Machine Learning Module (4): The machine learning module (4) processes real-time and historical parking data to optimize space allocation. It predicts peak parking times and dynamically adjusts the available spaces based on vehicle type, size, and user preferences. Moreover, it increases security by analyzing visual sensor data (3) to detect unauthorized activities.Central server (5): Central server (5) is responsible for managing data communication between the system components. It receives vehicle identification data from RFID readers (2), processes inputs from visual sensors (3) and checks the presence of vehicles. The central server (5) dynamically allocates parking spaces, keeps track of the parking duration for each vehicle, and controls the entrance and exit stores based on predefined safety policies.User interface unit (6): The user interface unit (6) allows users to interact with the system (100) via an application or web-based platform. Users may reserve parking spaces, view availability in real-time, make payments via integrated payment gateways, obtain navigation assistance, and obtain notifications of the parking status.The real-time parking management system (100) has been developed to provide a seamless and efficient parking experience by incorporating multiple technologies to automate parking space allocation, security, and monitoring. The system consists of several interconnected components, each of which contributes to the overall functionality of the invention.The system (100) comprises RFID tags (1) that are uniquely associated with each vehicle. These RFID tags ( 1) store unique vehicle identifiers that enable contactless identification at the entry and exit points of a parking facility. The RFID readers (2) are positioned at these points to identify the RFID tags (1) and read the vehicle identifier. These data are then transmitted to the central server (5) for validation and further processing.To improve safety and monitoring capabilities, the system (100) integrates a plurality of visual sensors (3) throughout the parking facility. These sensors (3) are positioned at entry and exit points as well as at individual parking locations to capture real-time images and video transmissions. The collected data is used to verify vehicle occupancy, identify unauthorized parking, and perform license plate identification to ensure that only authorized vehicles are accessing the plant.A machine learning module (4) is incorporated into the system (100) to analyze both real-time and historical parking data. This module is responsible for optimizing the parking space allocation by predicting peak parking times and dynamically adjusting available spaces based on vehicle type, size, and user preferences. Moreover, the machine learning module ( 4) enhances safety by detecting suspect activities based on the data received from the visual sensors ( 3) and other system components.The central server (5) functions as a central processing unit of the system (100). It receives vehicle identification data from RFID readers (2), processes inputs from visual sensors (3) and checks the presence of vehicles. Moreover, the central server (5) dynamically allocates parking spaces based on real-time occupancy data, tracks the parking duration for each vehicle, and controls entrance and exit stores based on safety policies. The server also maintains a database of parking activities that can be used for analysis and reporting purposes.The system (100) further comprises a user interface unit (6) that allows users to interact with the parking space management system via a mobile application or a web-based platform. Users may reserve parking spaces in advance, view the availability of parking spaces in real time, make payments via integrated payment gateways, and receive incremental navigation assistance to reach their assigned parking spaces. The user interface unit (6) also sends notifications of park status, entry acknowledgments, and security warnings.The system (100) provides several important functions to improve parking management.The visual sensors (3) play a decisive role in improving security by checking the number plates of the vehicles and matching them with a database in order to prevent unauthorized access. These sensors also aid in monitoring vehicle movements within the parking facility and ensure better control and management of the available spaces.The machine learning module (4) continuously processes real-time and historical data to update the predictive analysis. By analyzing parking patterns, it dynamically optimizes space allocation based on user preferences, vehicle type, and impact times. This function significantly reduces the waiting times and increases the efficiency of the parking.The loT network comprises embedded sensors (3) installed in individual parking spaces to monitor occupancy. These sensors transmit real-time information to the central server (5), which allows accurate tracking of the parking space and immediate updates on the user interface (6). This function helps users find free parking spaces without unnecessary delays.The user interface (6) is designed to provide real-time warnings and navigation assistance. It informs the users of the availability of parking spaces and guides them efficiently to their assigned spaces. Moreover, this unit provides seamless integration with mobile applications so that users can interact with the system easily.The machine learning module ( 4) also enhances safety by detecting anomalies such as unauthorized parking, vehicles that are in stay too long, and unusual patterns of motion. By analyzing the visual sensor (3) and RFID input data, potential violations are detected and the administrators are warned so that they can intervene in a corrective fashion.When the vehicle exits, the central server ( 5) generates a detailed digital acknowledgment with a summary of the parking duration and the charges associated therewith. This acknowledgement is automatically sent to the user interface (6), ensuring a transparent and efficient payment operation.The system (100) integrates the real-time tag recognition with the RFID authentication to increase security. This duplicate verification process ensures that only authorized vehicles are given access to the parking facility, prevents fraudulent entry, and increases overall security.The user interface (6) also allows users to specify preferences such as preferred parking zones, duration and vehicle type. These preferences are taken into account by the machine learning module ( 4) in order to offer a parking experience tailored to the individual requirements.Visual sensors ( 3) and loT-based occupancy detection cooperate to identify free parking spaces. By minimizing the search time, the system ( 100) improves overall user satisfaction and reduces parking device overload...Advantages of the invention: The real-time parking space management system (100) offers several advantages over conventional parking space management systems:• The automatic and contactless allocation of parking spaces reduces jams.• Tracking in real time increases security and prevents unauthorized access.• Predictive analyses optimize space allocation, reduce idle times and improve user experience.• Integrated payment gateways rationalize the collection of parking fees.• License plate recognition and visual monitoring provide an additional level of security

Claims

A real-time parking management system (100) comprising: a plurality of RFID tags (1) each associated with a vehicle, the RFID tags (1) configured to store a unique vehicle identifier; a plurality of RFID readers (2) positioned at entry and exit points of a parking facility, the RFID readers (2) configured to identify the RFID tags (1) and read the vehicle identifier; a plurality of visual sensors (3) positioned at parking locations, entry and exit points and configured to capture images or video feeds to verify vehicle occupancy, identify unauthorized parking, and assist in license plate identification; a machine learning module (4) configured to analyze historical parking data to predict peak parking times, optimize allocation of parking space based on vehicle type, size, and user preferences, and increase security by detecting suspect activities based on visual sensor data; a central server (5) configured to receive the vehicle identifier from the RFID readers (2), process inputs from the visual sensors (3) and confirm the presence of the vehicle, access a database to retrieve and store vehicle information, dynamically allocate parking spaces based on availability, vehicle classification, and user preferences, track duration of parking for each vehicle, and control entry and exit stores based on confirmed credentials and security policies; A user interface unit (6) configured to allow users to reserve parking spaces, to indicate the availability of parking spaces in real time, to facilitate payment of parking fees using integrated payment gateways, to provide incremental navigation assistance to assigned parking spaces, and to inform users of the parking status, entry acknowledgments, and security warnings.The system (100) of claim 1, wherein the visual sensors (3) are configured to verify and match vehicle identifiers to the database to increase security and prevent unauthorized access.The system (100) of claim 1, wherein the machine learning module (4) continuously updates predictive analyses to optimize parking space allocation based on real-time and historical data.The system (100) of claim 1, wherein the IoT network further comprises embedded sensors (3) positioned in parking spaces to monitor vehicle occupancy and forward this information to the central server (5).The system (100) of claim 1, wherein the user interface unit (6) provides real-time warnings and navigation assistance based on the real-time availability of parking spaces and the vehicle position.The system (100) according to claim 1, wherein the machine learning module (4) processes data from visual sensors (3) and RFID inputs to detect anomalies such as unauthorized parking, vehicles that remain too long, or violations of vehicle movement.The system (100) according to claim 1, wherein the central server (5) is configured to generate a digital acknowledgement on exit of the vehicle, which summarizes the parking duration and the charges, and to send them to the user interface unit (6) of the user.The system (100) of claim 1, wherein the system (100) is configured to dynamically control access to parking spaces by integrating real-time license plate identification with RFID authentication for improved security.The system (100) of claim 1, wherein the user interface unit (6) allows the users to set preferences such as preferred parking zones, duration and vehicle type for optimized assignment using the machine learning module (4).The system (100) of claim 1, wherein visual sensors (3) and loT-based occupancy detection cooperate to identify free parking spaces and minimize search time for users.

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