Availability Of Parking Slots Research Articles

Implementasi Google Cloud Vision untuk Deteksi Ketersediaan Lahan Parkir Kendaraan Mobil di Perguruan Tinggi

The increasing number of car users in colleges has posed significant challenges in effectively managing parking lots. This research focuses on the implementation of Google Cloud Vision to detect and monitor the availability of car parking lots in a college environment. By utilizing cloud-based image processing services and machine learning algorithms from Google Cloud Vision, the proposed system aims to provide real-time analysis and reporting on parking slot availability. The methodology used involves capturing images of the parking area using strategically placed cameras, then uploading these images to Google Cloud Vision to detect the presence or absence of cars. The system is designed to be scalable, ensuring that it can handle different sizes and complexities of parking areas. Preliminary results show that the approach using Google Cloud Vision offers a high level of accuracy in identifying occupied and empty parking slots, thus providing a reliable tool for parking management in a college environment. This work discusses the development, implementation, and evaluation of the system, and highlights its potential in improving parking lot utilization efficiency and reducing the time users spend searching for available parking spaces.

Parking Slot Booking System using IOT

The escalating problem of finding parking spaces in urban areas and large organizations has led to the need for innovative solutions. To address this issue, we present a "Parking Slot Booking System Using IoT" that offers a smart and efficient way to manage parking spaces. Our system utilizes IoT devices such as Arduino Uno and infrared (IR) motion sensors to monitor parking slot availability in real-time. A user-friendly web application allows users to check the availability of parking slots, book slots in advance, and pay for their parking sessions seamlessly. The system aims to reduce the time and effort wasted in searching for parking spots, alleviate traffic congestion, and optimize parking space utilization. By providing users with real-time information about parking availability and automating the parking process, our system enhances user convenience and reduces environmental impact. Keywords: Parking Slot Booking, IoT, Arduino Uno, Infrared Motion Sensors, Web Application, Real-time Monitoring, Traffic Congestion Alleviation.

IOT Based Smart Parking System

Abstract: The problem faced by people in this modern era in urban areas is the problem of parking whether it is in shopping mall, railway station, hospitals, movie theatre, etc. This problem occurs due the increase of number of vehicles in recent times. Furthermore, today’s car parking is insufficient and driver/users waste most of the time in finding a place to park their vehicles. The purpose of this research is to use modern technologies like IoT (Internet of Things) and RFID (Radio-Frequency Identification) which detects the availability of parking slots in the parking lots. Besides, the smart parking system has a web application which displays how many slots are available and alerts the user when status of the slot has changed. Additionally, the user details are added on the database. Hence, the smart parking system will provide a smooth functioning and will take the parking system to new levels

PROTOTYPE SMART PARKING AT STMIK AKBA BASED ON MICROCONTROLLER USING RADIO FREQUENCY IDENTIFICATION (RFID) TECHNOLOGY

This study aims to design a prototype smart parking using a microcontroller is expected to provide convenience for parking lot users at STMIK AKBA, making it easier for drivers to find out the availability of parking slots and where the location of the empty slots is in a parking lot and at the same time test the performance of the prototype using RFID. The results of this study indicate that using this system can provide information to parking users quickly and effectively. The results of the implementation of this system can run well based on the results of system testing in its use which get the results of the system's feasibility test with the average time for access takes 3 seconds and the average time for access to exit takes 6 seconds with a suitable category for use.

Smart Vehicle Parking Facility and Monitoring System Using ML

In response to the exponential growth of vehicles in the last two decades, we propose a Machine Learning-based Smart Parking System designed to address the challenges of parking management without the need for sensors or IoT technology. This system leverages cloud computing and a cyber-physical framework to streamline parking operations, providing real-time information to users about parking slot availability, efficient management of reserved and unreserved slots, detection of anomalies, and intelligent traffic management. With a user-friendly interface, the system minimises human intervention, resulting in time, cost, and energy savings, offering an enhanced and efficient solution for urban parking management.In response to the exponential growth of vehicles in the last two decades, we propose a Machine Learning-based Smart Parking System implemented as a web application using HTML, CSS, and JavaScript, without the need for sensors or IoT technology. This web-based system leverages cloud computing and a cyber-physical framework to streamline parking operations, providing real-time information to users about parking slot availability, efficient management of reserved and unreserved slots, detection of anomalies, and intelligent traffic management. With a user-friendly interface, the system minimises human intervention, resulting in time, cost, and energy savings, offering an enhanced and efficient solution for urban parking management.

Cox Regressive Outlier Robust Incremental Extreme Learning Machine based IoT aware Smart Car Parking and Route Optimization for Intelligent Transportation

An Intelligent Transport System (ITS) is a wide-ranging framework that influences advanced technologies to improve efficiency of transportation networks. An ITS integrated with an IoT enhances the capabilities of transportation networks. Owing to quick development of vehicles, traffic congestion during road network is major problems. Therefore, intelligent traffic control system is required to create smart transportation through optimization of vehicle route, and so on. In this paper, Cox Regressive Fuzzified Outlier Robust Incremental Extreme Learning Machine (CRFORIELM) is developed for smart ITS. The IoT technology in IT’S is used to collect traffic data, vehicle information, Parking slot occupancy data. After data collection process, proposed CRFORIELM technique includes two major processing steps namely parking slot availability detection and traffic aware route optimization. The extreme learning machine includes three types of layers such as input, three hidden layers as well as output layer. Initial hidden layer predicts the parking slot availability using Cox regression is performed. With the parking lot availability predictions, integrate this information into a route optimization algorithm. This algorithm considers the real-time traffic conditions as well as parking availability for detecting optimal route by applying fuzzy triangular membership function in the second hidden layer. Finally, nearest route path is effectively determined to minimize travel time in intelligent transport system. Experimental analysis indicates that the CRFORIELM technique achieved 2%, 5%, 10% improvement in accuracy, sensitivity, specificity and reduced error rates, route detection time by 39%, and 36%, compared to existing methods.

Smart Parking Slot Management System Using IOT

The paper proposes an innovative approach to tackle the pressing issue of efficient parking space management amidst the backdrop of rapid urbanization and escalating vehicle ownership rates. Through the amalgamation of Internet of Things (IoT) technology and ultrasonic sensors, the Smart Parking Slot Management System (SPSMS) emerges as a promising solution. Within this system, IoT-enabled devices, particularly ultrasonic sensors, are strategically deployed within parking slots to constantly monitor their occupancy status in real-time. These sensors function by detecting the presence or absence of vehicles through precise measurements of the distance between the sensor and the ground surface. Subsequently, the collected data is seamlessly transmitted wirelessly to a centralized server or cloud-based platform via internet connectivity. Upon reception of sensor data, the central server undertakes robust processing and analysis to ascertain the availability of parking slots within the designated area. End-users can conveniently access this pertinent information through a dedicated mobile application or a web interface, facilitating effortless identification and reservation of vacant parking spaces. The system further enhances user experience by incorporating automated notifications, alerting users to nearby available parking slots, alongside real-time updates on parking availability and robust reservation management functionalities. Keywords: Internet of Things, Thing Speak, Arduino Uno, ultrasonic sensor, Node MCU.

Integrating YOLOv8 with Fuzzy Logic System: A Novel Hybrid Approach for Efficient Parking Slot Availability Management

In urban areas, the challenge of finding parking spaces has become a significant concern, leading to congestion, wasted time, and increased pollution. Traditional parking management systems often lack the efficiency needed to address this issue adequately. In this paper, a novel approach was proposed to smart parking management that integrates the YOLOv8 model and fuzzy logic system. YOLOv8, a state-of-the-art object detection algorithm, enables real-time detection and tracking of vehicles within parking lots. By utilizing YOLOv8, the system can accurately identify vacant parking spaces in a timely manner. Furthermore, fuzzy logic was employed to enhance decision-making in selecting the optimal parking slot for users. Fuzzy logic enables the system to consider various factors such as proximity to the destination, parking space size, and distance from the entrance. By incorporating fuzzy logic into the decision-making process, the system can provide personalized recommendations tailored to individual user preferences and parking requirements. Based on the fuzzy inputs namely distance from entrance, proximity to exit and space, the system analyzes the best parking slot and assigns “rank” which is also fuzzy output. The decision can be made based on the rank provided to every slot of the parking lot. Slots with the highest rank should be preferred for parking because they are more suitable as they provide ease to parking the cars and can be suitable to customized needs of the users. The model can be deployed with LCD screens at various parking lots in order to save fuel and time of the commuters.

SLOT BOOKING FOR VEHICLE PARKING

The growing population in metro cities is due to massive automobile density, and the trouble with vehicle parking has become a never-ending question. Centralized car parking structures were installed to avoid roadside parking and different associated visitor issues. In many cities, automobile drivers search for a parking slot during rush hours or through visitors jams. This app presents an efficient method to test the supply of parking slots and to order a slot. Existing work will focus solely on parking slot availability. However, in this rapid-paced pace, international drivers can't affirm whether a parking slot is to be had as in step with the call. To triumph over this drawback, smart parking with reservation cellular-based surroundings is proposed. This will make it easier for motorists to park their automobiles and keep away from traffic jams. Drivers can initiate the request for the usage of the reservation app on Android cell to determine the provision of a parking slot. The motive force can reserve the slot via the net charge system if the slot is to be had. The proposed gadget also allows drivers to cancel a reserved parking slot. The amount might be refunded after cancellation charges. Keywords: Pre-parking slot book, vehicle, slot availability, traffic congestion.

Smart Parking System: Optimized Ensemble Deep Learning Model with Internet of Things for Smart Cities

In the recent era of smart city ecosystems and the Internet of Things (IoT), innovative, intelligent parking systems must make cities more sustainable. Every year, the increasing number of city vehicles requires more time to search for parking slots. In large cities, 10\% of the traffic congestion occurs because of cruising; drivers spend almost 20 minutes searching for free space to park their vehicles. The passing time of waiting for parking in the traffic leads the issues such as energy, pollution, and stress. There needs to be more than the developed solutions. Therefore, the necessary to create a parking slot availability detection system that informs the drivers in advance about the free parking slot based on location. This paper introduces an enhanced ensemble Deep Learning (DL) model designed to forecast parking slot availability through the integration of IoT, cloud technology, and sensor networks. The devised model, known as Ensemble CNN-Boosted Graph LSTM (ECNN-BGLSTM), is optimized using a Genetic Algorithm (GA) framework. The model's performance is rigorously evaluated using a dataset from Europe, and various metrics, including Root Mean Square Error (RMSE), Mean Square Error (MSE), and Mean Absolute Error (MAE), are employed for assessment. The experimental findings demonstrate the superior performance of the proposed model compared to existing state-of-the-art approaches.

Smart Car Parking System

This project proposes a smart car parking system that utilizes Arduino UNO, a servo motor, a 16x2 i2c LCD display, two IR sensors (one at the entry and the other at the exit), a PAM 8403 Amp, and a speaker to inform the user about the availability of parking slots. The system works by detecting the presence of a car using the IR sensors and updating the display to show the number of available slots. The servo motor controls the barrier at the entry and exit, while the PAM 8403 Amp and speaker provide voice notifications to guide the driver through the parking process. This system simplifies the parking process by providing real- time information and voice guidance, enhancing the overall parking experience.

Sistem Pemantauan Slot Parkir Menggunakan Sensor Ultrasonik JSN-SR04T dan Pengenalan Plat Nomor Kendaraan dengan ESP32-CAM

A parking slot monitoring system prototype has been produced using the JSN-SR04T ultrasonic sensor and vehicle license plate recognition with ESP32-CAM. The system was created to make it easier for motorists to monitor the availability of parking slots remotely by utilizing Telegram which is connected to the ESP32-CAM module and Arduino Mega 2560. The ultrasonic sensor detects the distance of vehicles entering or exiting the parking lot, then a servo motor opens the entry and exit bars. Vehicle users can monitor the availability of parking slots on the Telegram bot. In each slot there is an ultrasonic sensor that detects the distance so that it can find out whether there is a vehicle in the slot. The test results show that the ultrasonic sensor has an average error percentage of 0.65%. The parking barrier can be opened when the ultrasonic sensor detects the presence of a vehicle at the entrance or exit and the ultrasonic sensor can detect the presence of a vehicle according to the conditions in the slot. The system is equipped with vehicle license plate character recognition using the Optical Character Recognition (OCR) method. Through the ESP32-CAM module camera webserver, the OCR program can detect vehicle plates with the furthest distance of 140 cm using video resolution (400x296) and 300 cm using video resolution (1600x1200). The OCR program can read the vehicle plate characters correctly and the results for the number of characters obtained correspond to the license plate being tested, then the vehicle plate data is stored in the database

IoT Raspberry Pi Based Smart Parking System with Weighted K-Nearest Neighbours Approach

Due to the limited availability of parking slots in parking areas, drivers often have difficulty finding an empty parking slot. The number of parking slots available at a particular location is usually less than the number of vehicles. Hence, drivers spend a lot of time looking for vacant parking slots, which eventually delays the completion of their tasks, such as paying bills, attending a meeting, or visiting a patient at the hospital, etc. There are a couple of parking guidance systems that have been highlighted by the other researchers, but most of them lack real-time, convenient guidance. This research proposed a smart parking guidance system made of an IoT Raspberry Pi combined with an Android application that makes use of the weighted k nearest neighbours for positioning the vehicle. This was achieved through the use of Wi-Fi signal strength indicator fingerprinting, allowing for real-time navigation and parking detection. In order to achieve real-time parking over the internet, Raspberry Pi hardware and the ThingSpeak IoT cloud with ultrasonic sensors are used in the proposed method. An Android application was involved in this parking detection system, which adopted IoT approaches to estimate the location of users in real-time and provide routes using route-finding techniques to assist drivers in finding their desired parking slots. Data from the sensors was processed and translated into the Raspberry Pi using the Python programming language. They were sent using the Message Telemetry Transport protocol to send parking data to the ThingSpeak IoT cloud in real-time. This data was displayed via the Android app. The user is then able to view each available parking slot, acquire the route, and be directed with high accuracy to the parking slots of their choice. In this study, advanced sensing and communication technologies were used together with the weighted k nearest neighbours algorithm for positioning and wayfinding in order to improve parking guidance accuracy. Based on the experimental results, the proposed system showed a lower average error rate of 1.5 metres in comparison to other positioning techniques, such as GPS, or other similar algorithms for positioning, such as maximum a posteriori, which have shown average errors of 2.3 metres and 3.55 metres, respectively, a potential increase of more than 35% from the previous error rate. Doi: 10.28991/CEJ-2023-09-08-012 Full Text: PDF

Smart parking space detection under hazy conditions using convolutional neural networks: a novel approach

Limited urban parking space combined with urbanization has necessitated the development of smart parking systems that can communicate the availability of parking slots to the end-users. Towards this, various deep learning based solutions using convolutional neural networks have been proposed for parking space occupation detection. Though these approaches are robust to partial obstructions and lighting conditions, their performance is found to degrade in the presence of haze conditions. Looking in this direction, this paper investigates the use of dehazing networks that improves the performance of parking space occupancy classifier under hazy conditions. Additionally, training procedures are proposed for dehazing networks to maximize the performance of the system under both hazy and non-hazy conditions. The proposed system is deployable as part of existing smart parking systems, where a limited number of cameras are used to monitor hundreds of parking spaces. To validate our approach, we have developed a custom hazy parking system dataset from real-world task-driven test set of RESIDE-β dataset. The proposed approach is tested against existing state-of-the-art parking space detectors on CNRPark-EXT and hazy parking system datasets. Experimental results indicate a significant accuracy improvement of the proposed approach on the hazy parking system dataset.

Rekayasa Tempat Parkir Kendaraan Mobil Berbasis Teknologi Informasi

The availability of parking lots is a must for perkatoran, shopping centers (malls), universities and others. Along with the ability of the public to have vehicles, both two-wheeled and four-wheeled vehicles, it makes parking spaces difficult and takes a long time to get a parking space, this is because there is no service regarding information on the availability of empty parking slots, so there is no marker to know whether the parking lot is fully filled or not. It is necessary to design a parking monitoring system tool, which aims to provide information on the availability of parking slots. Using the application design method by utilizing several object detection sensors including the Infrared Proximity Sensor and using the Message Queuing Telemetry Transport (MQTT) protocol which functions as a wireless communication protocol. The results of this study show that the system works as expected, that the sensor can detect parking objects that are filled or still empty and the system data communication also works well, namely the sensor sends data to wemos D1, then sent to the MQTT Broker (server) then resumes to wemos D1 and then the data is sent to the message viewer device, namely monitors and LEDs. The LED light as an indicator gives a message, if the LED lights up in green, it means that the parking lot is not filled and if the LED lights up red, it means that the parking slot is filled.

Smart Parking Solution for Smart Cities Using Arduino

Abstract: Today’s world peoples are focusing more on internet. People are becoming dependent on internet as it makes our life easier and faster. In order to maximize the performance and accuracy of the urban area economic-development constant efforts are made in the field of IoT. With the help of IoT platforms we can connect the sensors with the internet. Therefore by using IoT we can implement many applications. The smart parking system is one of this IoT application. There are many problems regarding unplanned parking not only in India but also in many other countries of the world. Hence, we have Introduced IoT based parking system to reduce the issue of unplanned parking and also to reduced the traffic congestion. This project allow the user to find the vacant parking space in a given area. We have developed mobile application using which the user can easily check the availability of parking slot. Keywords: Arduino UNO, IoT, Ultrasonic Sensors, Wifi, Android Application

Car parking occupancy prediction

Nowadays in modern cities, with the continuous growth of cars, parking slot availability is becoming a more and more difficult task. So, an efficient car parking occupancy detection system is becoming a necessity in order to reduce traffic congestion in parking lots. This paper proposes a system based on computer vision algorithms and basic image processing techniques that is capable of determining if a parking space is occupied or not, using aerial images captured through a camera. It aims to solve the issue of detecting a parking space that minimizes the time spent in searching parking lots which in turn reduces the carbon emissions that lead to a better quality of life. Current solutions available to this problem use hardware devices, IoT, sensors, CNN, and various deep learning algorithms. But the proposed system eliminates all the above complexities, thus resulting in greatly decreased expenses.

Design of a Decision-Based Multicriteria Reservation System for the EV Parking Lot

In metropolitans, the problem of finding available parking slots has changed as finding available parking slots having charging stations due to increasing electric vehicle (EV) deployment. Smart management systems can be used in this manner for obtaining an optimum parking slot in EV parking lots (PLs) considering EV users’ preferences. This article proposes a smart reservation system considering the behavior of EV users, parking slot availability (PSA), state-of-charge (SoC) value of EVs, and PL usage history of EV users. In order to handle weighting the behavior of EV users according to a comprehensive criteria comparison, the analytical hierarchy process (AHP) from multicriteria decision-making (MCDM) techniques is used in the smart reservation system. Thereafter, the proposed ranking function is presented to develop the mentioned quality-of-experience (QoE)-based charging slot allocation considering the reservation requests of EV users sent via a mobile application and to accept the optimal EVs in accordance with the weights assigned by AHP. The proposed concept is tested under different cases generated by changing the individual importance degree of EV user’s criteria. The different case studies demonstrate the effectiveness of the proposed decision-based multicriteria reservation system in terms of EV users’ acceptance ratio. Simulation results show that not only the importance degree related to the EV users’ criteria has an important effect in accepting appropriate EV users but also PSA management is another vital criterion especially in peak-load hours.

Camera-Based Parking System Management Using Raspberry Pi

Currently, there are still many use of manual parking systems, namely parking attendants provide instructions for vehicles to park. This is often considered inefficient because there is no data recording of vehicles that park, resulting in a low level of security and comfort for visitors and the parking system does not provide information about parking slots which can make it difficult for visitors to park vehicles. With this, the vehicle that wants to park often has difficulty when parking the vehicle. Through various problems that occur, the author develops a parking system that can provide information on the availability of parking slots in the parking area as well as data storage for vehicle number plates that do parking. In the parking system, the Raspberry Pi 3 Model B is used as the main controller, camera detection to obtain information in the form of characters from the vehicle number plate with the help of OCR (Optical Character Recognition), the use of OTP (One Time Password) code which can be used only once so as to increase security. on the parking system. Vehicle data in the form of number plates and also OTP code will be stored in the database and used when the vehicle will leave the parking area by matching the number plate data and OTP code of a vehicle to be able to leave the parking area. Through the development of the parking system, it is hoped that it will work well for vehicle drivers to find available parking locations and increase safety and comfort for drivers because of data storage in the form of vehicle number plates as vehicle identity and the use of OTP codes that can only be used once.

Internet of Things enabled Parking System In Smart Cities

Internet of Things (IOT) performs a important function in connecting the encompassing environmental matters to the community and made clean to get entry to the ones un-net matters from any far off location. It’s inevitable for the humans to replace with the developing technology. And typically human beings are dealing with issues on parking automobiles in parking slots in a city. In this have a look at we layout a Smart Parking System (SPS) which permits the person to discover the closest parking vicinity and offers availability of parking slots in that respective parking place. And it specially awareness on lowering the time in locating the parking masses and additionally it avoids the needless journeying thru stuffed parking plenty in a parking place. Thus it reduces the gas intake which in flip reduces carbon footprints in an atmosphere.