A Novel Hybrid Approach Towards Parking Space Occupancy Detection

Traffic congestion is one of the most notable urban transport problems, as it causes high energy consumption and air pollution. Unavailability of free parking spaces is one of the major reasons for traffic jams. Congestion and parking are interrelated because searching for a free parking spot creates additional delays and increase local circulation. In the center of large cities, 10% of the traffic circulation is due to cruising, as drivers nearly spend 20 min searching for free parking space. Therefore, it is necessary to develop a parking space availability prediction system that can inform the drivers in advance about the location-wise, day-wise, and hour-wise occupancy of parking lots. In this paper, we proposed a framework based on a deep long short term memory network to predict the availability of parking space with the integration of Internet of Things (IoT), cloud technology, and sensor networks. We use the Birmingham parking sensors dataset to evaluate the performance of deep long short term memory networks. Three types of experiments are performed to predict the availability of free parking space which is based on location, days of a week, and working hours of a day. The experimental results show that the proposed model outperforms the state-of-the-art prediction models.

Nowadays the concept of smart cities has gained grate popularity. and thanks to the IoT of things technology for the concept and the idea of smart city in this paper, we present an IoT based smart parking system. A Smart parking system that helps drivers to find vacant spot. Driver Problems such as limited car parking, traffic problems and road safety are being addressed by IoT. In this paper, I present an IoT based smart parking system. The Smart car Parking system will help user to solve the problem for finding a parking space and to reduce the time that they have spent in searching for the nearest available car parking. A mobile application is also provided that allows an end user to check the availability of parking space and book a parking slot according to their time convenience.

In recent times the concept of smart cities has become very popular. Thanks to the Internet of things the idea of smart city now seems to be completed. Consistent efforts are being made in the field of IoT in order to maximize the productivity and reliability of urban infrastructure. Problems such as, traffic congestion, limited car parking facilities and road safety are being addressed by IoT. In this paper, we present an IoT based cloud integrated smart parking system. The proposed Smart Parking system consists of an on-site deployment of an IoT module that is used to monitor and signalize the state of availability of each single parking space. A mobile application is also provided that allows an end user to check the availability of parking space and book a parking slot accordingly.

The current parking system still uses a manual parking system, vehicle owners still have difficulty finding an empty parking space because they have to go around the parking area so it is less efficient and takes a long time. This study aims to help car drivers save time in finding parking locations and knowing the availability of parking spaces. In this study, there are two types of input used: infrared sensors, which function to measure the capacity of the parking space, and RFID sensors, which are used to detect cards. The data processing process is carried out using Arduino Uno, while the LCD is used to display the number of available parking slots and the location of the slot. In addition, the servo motor functions to open the barrier. This system operates in a way, when a car enters and attaches a registered card, the servo motor will open, and the number of parking slots will decrease. The driver then selects a parking slot, which will be automatically marked as "full" on the LCD screen. When the infrared sensor detects a car that wants to exit, the servo motor will open again, and the number of parking slots on the LCD will increase.

In this modern era, motorcycles are a primary means of transportation used by many people in Indonesian society, including students who use them to access campus. However, the increase in motorcycles also raises safety issues and the availability of parking spaces on campus. The parking system needs to be improved at the Faculty of Engineering, University of Mataram, because it does not use an automatic checking system, resulting in concerns about vehicle safety. This research aims to build a Web-based Motorcycle Parking Information System to store real-time rider data and detect faces and police numbers through CCTV. The Personal Extreme Programming (PXP) method is used as a development method because of its high level of flexibility and its ability to adapt to changing needs. This system was developed using the Bootstrap framework for the front end and Laravel for the back end, with MySQL Workbench as a server to manage the database. System testing uses the Black Box Testing method to ensure each unit or module functions according to predetermined needs. The test results show that all features function validly and by the expected specifications. This research provides an effective solution for improving parking security and parking space management on campus, thus providing a sense of comfort and security for students and all parking users at the Faculty of Engineering, University of Mataram.

The development of private vehicle ownership is very rapid, but it is not balanced by adequate supporting infrastructure such as roads and parking lots. Especially for parking lots, parking horizontally will be difficult to develop because of the limited land availability. The addition of parking lots can be done vertically by building a multi-storey parking building. So far, the existence of multi-storey parking buildings has not provided an information system on the availability of parking spaces. The form of multi-storey parking lots often makes the driver have to go around few times to find an empty space. This situations wasting of energy and time. This study aims to design an information system as application models in human-computer interaction, that will inform someone there is empty or already filled parking space, so that it can save time and make it easier for drivers to find parking spaces to park their cars. This information system prototype design consists of three main parts, called sensors, controllers, and displays. Car parking control system that works with an automatic portal (parking gate) along with a display screen for information on the location of empty parking spaces and those that have been filled. The portal will open if information states the parking lot is still available, and the portal will not open if information states the parking lot is full.

The high demand for ubiquitous availability of reliable parking spaces in cities faces challenges on timely information sharing and low-cost infrastructure deployment. In this paper, we propose a mobile crowdsensing system, namely ParkHop, to aggregate on-street and roadside parking space information through sensorless sensing, and disseminate this information to urban drivers in a resilient manner. ParkHop targets special social groups that have stable work routines to serve as crowd workers. We propose a crowdsensing algorithm employing a joint estimator to process crowdsensed data, and evaluate the reliability of crowd workers based on the veracity of their answers to a series of control questions. In addition, the specific worker selection method to speed up the crowdsensing process and incentive scheme to achieve fair reward distribution have been carefully designed in ParkHop. Our system disseminates the availability of parking spaces and their up-to-date price information to drivers with on-demand needs via a publish-subscribe messaging pattern. The efficacy of ParkHop for aggregation and dissemination of parking space information has been evaluated in both real-world tests and simulations. Our results show the system is robust and agile enough to cope with different crowdsensing scenarios.

In densely populated areas, obtaining parking spaces is a major problem because the number of automobiles on the road is increasing daily. RFID is the most often used technique for removing or overcoming the cause. Checking the card's balance rather than hunting for parking spaces at far-off locations is the present RFID concept's procedure. The biggest problem with the existing approach is that it is hard to measure how much money is taken out because it varies over time and between various slots. Therefore, this research study provides a solution, namely the suggested method, which guarantees an efficient monitoring system and permits the monitoring of parking spaces in remote regions. These efforts The goal of this project is to tie the RFID concept to the Internet of Things (IoT). Users can communicate remotely regarding parking space availability thanks to IoT's client-server connection. The creation of a website that informs users when parking spaces are available would enhance the mobile-friendly environment. From a distance, users will be able to reserve a parking spot, and that spot will be held for 30 minutes while it waits for the user to arrive. After the time restriction has gone and the slot is still available, the user must rebook it. By doing this, parking lot traffic congestion is reduced to a minimum. This can be employed in retail areas where traffic congestion is regularly caused by parking concerns.

With the rapid growth of the economy, the number of vehicle users has surged, leading to an increasing demand for parking spaces. The widespread use of smartphones has encouraged users to turn to mobile application-based solutions. The development of IoT technology has facilitated the integration of wireless connectivity, mobile devices, and mobile applications.. In order to provide a complete parking solution for both users and parking space owners, this paper suggests an smartphone application and a smart parking system powered by the Internet of Things (IoT).The application enables users to book parking spots, verify reservations, find the closest spot based on vehicle size, find the parking slot, and retrieve daily, weekly, and monthly account data. The availability and location of open parking spaces are communicated using Wi-Fi, microcontrollers, and infrared (IR) sensors.And technology for wireless communication to a server. A smartphone app is then used to retrieve this data. RFID tags affixed are employed to verify users who make hourly, daily, weekly, or monthly parking reservation reservations. Based on the size of the vehicle, a scheduling algorithm is used to determine the closest available space. The seamless user experience is the goal of the mobile app's design. The study also emphasizes the difficulties and inefficiencies brought about by conventional parking arrangements. The authors suggest an Internet of Things (IoT)-based smart parking system that makes it simple for users to find open spots in a certain location.

In the modern world with about a billion vehicles present around the globe, and being in a densely populated country like India creates the need for an efficient parking system and with world advancing towards automation, there is also a need for an automated parking system. Mainly the problem of parking arises in big cities and this causes problems like traffic congestion, driver frustration & air pollution, etc. The issue mainly arises from not knowing whether the parking spaces is available at any given point of time. Even if known, many vehicles may be competing for limited parking spaces causing severe traffic congestions. Even there are problems that can be caused with regards to the parking management. It may be difficult for the parking management to organise the parking of the vehicles in an orderly manner. Thus we are trying to resolve the problems stated by developing an RFID based smart parking system that monitors the availability of idle parking slots and guides the vehicle to the nearest such slot by sending a message to the mobile number registered in the vehicle’s RFID. The proposed system uses infrared transmitter-receiver pairs that remotely communicate the status of parking occupancy to the Arduino UNO microcontroller and displays the vacant slots on the display at the entrance of the parking so that the user gets to know the availability /unavailability of parking space prior to his/her entry into the parking place. Implementation involves minimal human interaction and provides a seamless parking experience thereby reducing a lot of time wasted by the user in parking his/her vehicle. Key Words: Parking System, RFID, Arduino UNO

Drivers face parking problems in most area, especially during peak hours. The difficulty roots from the availability of parking space at the given time and place. Despite the technologies and protocols used to solve parking problems and have an intelligent city, many vehicles may pursue a small number of parking spaces, which in turn leads to serious traffic congestion. A driver can spend a lot of time to look for an available parking space closed to his destination, which means the increasing of the traffic problem of the city, a very high consumption of fuel and the spectacular impact on the environment. Wireless sensor networks offer an attractive choice for low cost and easy-to-deploy solutions for intelligent traffic guidance systems and parking lot applications. This paper focuses on comparative study of different smart parking techniques developed with the aim of overcoming said problems using various wireless sensor networks and to propose architecture of a multi-service smart parking management system.

With the increasing population in urban areas, finding a vacant parking space has always been the biggest problem for drivers, which causes a series of issues such as energy waste and environmental pollution. Most outdoor parking lots cannot provide details of vacant parking spaces due to limited sensor technology in outdoor environments (i.e., poor resistance to external interference due to heat, light or signal noise). Although some studies are based on images captured by cameras, the existing vacancy detection methods using fixed-position surveillance cameras are not flexible and accurate enough for wide use. We propose an Inclined Bounding Box (IBB) method for detecting vacant parking spaces using aerial images. The IBB method takes advantage of the feature-description ability of deep Convolutional Neural Network (CNN) to identify the status of parking spaces and develops an inclined bounding boxes calibration algorithm on the top layer of CNN architecture. The proposed IBB method can automatically identify parking spaces, locate vacant parking spaces with any direction and detect multiple parking spaces simultaneously. The experimental results show that the proposed IBB method is more accurate than the three counterpart methods.

Finding a vacant parking space in outdoor parking lots is a daily concern of most vehicle drivers during rush hours, especially in the urban context. In this paper, an outdoor parking space vacancy detection system is proposed, using mobile devices to improve parking space searching experience for vehicle drivers by providing them with the location and occupancy information of parking spaces. The system uses state-of-the-art image recognition algorithm, namely Convolutional Neural Network with a Raspberry Pi to identify vacant parking spaces from a parking lot image retrieved in real time via an IP camera. A university parking lot has been chosen as the test bed to deploy the proposed system for real time parking space vacancy detection. An Android smartphone application called Driver App is developed to enable ubiquitous visualization of real time outdoor parking spaces occupancy information for vehicle drivers. Evaluation outcomes based on the responses to System Usability Scale (SUS) questionnaire revealed high usability of the Driver App as a tool that provides smart parking service to assist vehicle drivers in searching for a vacant parking space.

In this study, we have investigated potential use of Multilayer Perceptron (MLP) to predict parking space availability for use within Field Programmable Gate Array (FPGA) accelerated embedded devices. While previous studies have explored the use of MLP for classification problem in FPGA, very little studies concentrated on the potential use of MLP in regression problem, especially in parking space forecasting. Therefore we formulated five Multi-Layer Perceptron (MLP) models with varying hidden units to perform single-step prediction to forecast parking space availability within the next 15 minutes based on the previous one-hour parking occupancy. The proposed models were trained on the historical data of Kuala Lumpur Convention Center dataset and evaluated against baseline ARIMA models. The results have shown that our proposed MLP model performed relatively well against baseline model with the root mean square error between (RMSE) 78.25 to 78.41 and mean absolute error (MAE) between 37.02 to 39.17.

Urban parks and green spaces are managed by local authorities, and 8 local authorities are utilizing the park and green space management system in Korea. However, in each local government, park and green space data, system components, main function, and tasks were established in different forms and their utilization was also very low. In this context, this study suggests a general-purpose model of the park and green space management system that can be used commonly by local governments for park and green space management. Based on the requirements that the GIS (geographic information system) should be used for continuous management in the “park and green space master plan guideline”, and the creation of an urban park inventory in the “act on urban parks, green areas, etc.”, we proposed a general-purpose model that builds GIS—based spatial information. We expect that local governments can reduce time and cost of introducing the park and green space management system, and the central government will be able to collect data and statistics on national park and green space, and establish data-based policies.