Smart Parking System Research Articles

Development of a smart parking system based on internet of things using object-oriented analysis and design method

Smart City is one of the Smart Initiatives that tries to provide solutions to parking problems that are found in big cities. The growth of the vehicle population is not matched by the growth of parking infrastructure, which raises various problems such as illegal parking, traffic jams, and driving safety. Thanks to the massive evolution of the Internet of Things, the Smart Parking idea became a breakthrough in solving the growing parking problem. In this paper, we explain the prototype development of the Smart Parking System using the Internet of Things which has three subsystems, namely embedded systems, as well as Android and web-based applications. Smart Parking System’s software was developed using the Object-Oriented Analysis and Design (OOAD) method and has been tested using black-box testing with 41 test cases that were successfully received.

Cloud Based Smart Parking System

Lately, the idea of brilliant urban communities has increased awesome notoriety. Parking becomes one of the tedious tasks in our day to day life. Many efforts have been done in this field to solve parking based problems like traffic congestion, limited parking space, high parking charges, and the most basic problem is to find nearby parking space. In this paper, we proposed an algorithm that increases the efficiency of the current cloud-based smart parking system and develops a network architecture based on Internet-Of-Things technology. Our proposed system helps users automatically find a free parking space at the least cost based on new performance metrics to calculate the user parking cost by considering the distance from the user to parking area and the total number of free places in each car park. A mobile application is provided that navigate the user to the free parking space based on the efficiency based on distance and cost. This cost will be utilized to offer an answer of finding an accessible parking spot upon a demand by the client and an answer of proposing another car park if the present park is full.

Smart Parking System Using Batch Algorithms Cloud Computing and Internet of Things

Innovative smart parking system works on sensor based IOT technology and cloud computing data collection to direct the driver to the particular parking spot. This paper implements an agile algorithm that improves the efficiency of the present cloud-based parking system and builds a network architecture based on the IOT technology. This paper introduces a system that helps users find a parking space at the least cost based on new efficiency constraints to calculate the user parking cost by considering the dimensions and the total number of free spaces in each car park. This cost will be used to offer a solution of finding an available parking space upon a request by the user and a solution of suggesting a new car park if the current car park is full. The simulation results convey that the algorithm helps improve the stability of successful parking and minimizes the user waiting time at the same time avoiding congestion. We also successfully implemented the algorithm virtually. Existing systems implement first come first serve algorithms to allocate parking space to cars which arrive to parking space, hence wasting a lot of space at the time costing efficiency to the parking lot. The proposed algorithm first sorts the cars based on their size, hence efficiently using the space available and balancing load at the parking side. Also separating the parking space for both large and small cars can help improve the parking congestion and price per space utility factor. The algorithm uses batch algorithms knowingly used in operating systems to arrange tasks and processes in an effective manner. It divides the cars into small and large categories alike the processes in operating systems, which helps to deal with the cars better. The whole system is also backed by low power IOT hardware like Arduino® Uno, NodeMCU® ESP8266, ZigBee networks and cloud computing solutions like Google© Firebase® and Thing Speak®.

Smart Parking System Based on Rules

The intelligent town idea plays a significant part in today's technological term. Consequently, the worry about parking in an urban area has become imminent. The parking problem can become a great chance presented by present trends to satisfy the world's linked continuum. This article focuses primarily on the smart car parking system idea. This system of parking offers 6 slots. But up to n amount of slot can be extended. The proprietor is assigned to each individual slot. And in the allocated scheme, the proprietor must park the car, but when a remote slot is assigned, i.e. slot 9, 10 makes the system uncomfortable to use for a brief stay. Therefore, a rule-based service customization method is used and this parking scheme will record remain time for a few days and the system will therefore allocate a slot to the vehicle's proprietor. Together with the IR sensor and RFID reader, Raspberry Pi is used in this scheme and linked to the web page with integrated Wi-Fi.

Smart Parking Sensors: State of the Art and Performance Evaluation

Smart parking systems present one of the essential infrastructure concepts that enable Internet of Things (IoT) in Smart cities. Finding a free parking lot plays a role in reducing traffic congestion, gas emissions, and increasing the quality of life of people living and working in it. Therein, the fundamental part of every smart parking system is the detection of vehicle presence, which is usually employed by devices comprised of power-hungry sensors. This paper gives an extension to state-of-the-art by a systematic in-depth overview of technologies used for the smart parking detection realization consuming mW of power. Deeper insights on the real-scenario performances and power consumption of most popular sensor devices and Low Power Wide Area (LPWA) radio technologies available today (LoRa, Sigfox and NB-IoT) are provided. The results show that based on the architectures of IoT system, lowest consumption is for LoRa devices. Further, analysis of power consumption of commercial LPWA-based Smart parking sensor device is provided along with battery estimation lifetime, which is especially important for the deployment of future smart parking solutions. Battery lifetime heavily depends on the number of parking lots exchanges and based on the less frequent changes, the estimated battery lifetime is approximately 7 years. Inspired by the limitations of power-hungry and relatively expensive smart parking sensor devices, two strategies for the optimization are proposed: first one is based on the premise where a drop in received signal strength of the LPWA device can serve as the presence of the vehicle in the parking lot, while the second one proposes a big picture on a novel architecture for harvesting the surrounding energy and using the same for circuitry wake-up therefore saving the energy.

A Prediction Algorithm for Cloud Integrated Smart Parking System to Search Vacant Parking Spot using Internet of Things

A Prediction Algorithm for Cloud Integrated Smart Parking System to Search Vacant Parking Spot using Internet of Things

A Smart Guidance Indoor Parking System Based on Dijkstra’s Algorithm and Ant Colony Algorithm

One of the more apparent problems associated with the growing number of parking spaces in shopping complexes, office buildings, and other types of building is the lack of notification to drivers of vacant and occupied parking bays in a large parking space. Given the heavy traffic commonly seen during the weekends, most drivers might spend at least 20 to 30 minutes just to find an empty parking bay, which leads to wasteful fuel consumption. Currently, most shopping malls have conventional parking systems, where heavy traffic can lead to an increase in the number of accidents occurring. This is a serious problem that requires a solution. The existing parking systems are complex and have poor performance due to low-speed processing and inefficiency. Thus, to overcome these problems, a smart parking system should be designed and implemented. This paper introduces a smart guidance indoor parking system based on embedded system integrated with both the Dijkstra’s algorithm and Ant Colony algorithm (ACO) to provide drivers with an efficient path to the nearest parking bay. The smart guidance indoor parking comprises two parts, namely the hardware and the software. The hardware part explains the components used in the system and the software part explains the algorithms which have been used in the system. The proposed smart guidance indoor parking has achieved 37.50%, 10.81%, and 34.88% improvement compared with the conventional Dijkstra’s algorithm. The smart guidance indoor parking system was successfully developed in an adaptable structure, convenient cost and easy handling procedure.

IoT Smart Parking System Based on the Visual-Aided Smart Vehicle Presence Sensor: SPIN-V.

Humanity is currently experiencing one of the short periods of transition thanks to novel sensing solutions for smart cities that bring the future to today. Overpopulation of cities demands the development of solid strategic plannings that uses infrastructure, innovation, and technology to adapt to rapid changes. To improve mobility in cities with a larger and larger vehicle fleet, a novel sensing solution that is the cornerstone of a smart parking system, the smart vehicular presence sensor (SPIN-V, in its Spanish abbreviation), is presented. The SPIN-V is composed of a small single-board computer, distance sensor, camera, LED indicator, buzzer, and battery and devoted to obtain the status of a parking space. This smart mobility project involves three main elements, namely the SPIN-V, a mobile application, and a monitoring center, working together to monitor, control, process, and display the parking space information in real-time to the drivers. In addition, the design and implementation of the three elements of the complete architecture are presented.

Low Cost Smart Parking System with IOT

Low Cost Smart Parking System with IOT

Smart Parking System Based on Bluetooth Low Energy Beacons With Particle Filtering

Urban centers and dense populations are expanding, hence, there is a growing demand for novel applications to aid in planning and optimization. In this article, a smart parking system that operates both indoor and outdoor is introduced. The system is based on Bluetooth low energy (BLE) beacons and uses particle filtering to improve its accuracy. Through simple BLE connectivity with smartphones, an intuitive parking system is designed and deployed. The proposed system pairs each spot with a unique BLE beacon, providing users with guidance to free parking spaces and a secure and automated payment scheme based on real-time usage of the parking space. Three sets of experiments were conducted to examine different aspects of the system. A particle filter is implemented in order to increase the system performance and improve the credence of the results. Through extensive experimentation in both indoor and outdoor parking spaces, the system was able to correctly predict which spot the user has parked in, as well as estimate the distance of the user from the beacon.

Logistics sustainability practices: an IoT-enabled smart indoor parking system for industrial hazardous chemical vehicles

Logistics sustainability practices in industrial cases gain more attention recently especially when transportation efficiency becomes a bottleneck. The research of smart parking develops rapidly especially the thriving of Internet of Things (IoT). In this research, the industrial hazardous chemical vehicle (IHCV) consists of tractor and trailer. The vehicle coupling and decoupling occur frequently in order to fulfil logistics missions. The real-time dynamic indoor location information of both tractors and trailers are of great significance among users. Excessive time and human effort consumed in locating the vehicles lead to the transportation delay and disorderly parking exacerbate congestion inside the indoor parking garage. In this paper, we propose an IoT-enabled smart indoor parking system for logistics vehicles. A self-learning genetic tracking algorithm is developed to ensure the tracking performance. The feasibility and effectiveness of this solution architecture and algorithm are verified in a real-life chemical logistics company. The results show that the proposed algorithm not only performs constant improving location accuracy up to 96.7% after learning but also ensure the long-term use compared to the triangulation method. Moreover, disorderly parking can be identified by location cell partition as to eliminate potential risks. Improved logistics efficiency and lowered congestion situation contribute to the sustainable logistics.

A Cloud Based Smart Parking System using Iot Technology

Car parking is the major problem faced in the current major city. There are more number of vehicles around the city and the parking spaces are less in number and we need to solve this problem in the efficient parking management system. By this we demonstrate the use of IoT based Parking system that allows the effective parking space shown in the system utilization using IoT technology. The project we use IR sensors to demonstrate for the sensing things in the parking slots available in the particular parking area along with dc motor to simulate the gates open and close. We use the Wi-Fi modem for internet connectivity and a micro controller for operating system. The system detects the parking slots are occupied using IR sensors. The system reads the number of available parking slots or occupied and updates the data through the cloud based server to allow to check the parking slots are availability in online. This allows the system to check available parking spaces in online from anywhere in the world.This solution is reliable in any circumstances.

GWO Model for Optimal Localization of IoT-Enabled Sensor Nodes in Smart Parking Systems

Due to rapid growth in urban population and advances in the automotive industry, the number of vehicles is increasing exponentially, posing the parking challenges. Automated parking systems provide efficient and optimal parking solution so that the drivers can have hassle free and quick parking. One of the demanding requirements is the design of smart parking systems, not only for comfort but also of economic interest. With the advancements in the Internet of Things (IoT), wireless sensors-based parking systems are the promising solutions for the deployment. Optimal positioning of IoT enabled wireless sensor nodes in the parking area is a crucial factor for the efficient parking model with the lower cost. In this paper, we propose a novel multi-objective grey wolf optimization technique for node localization with an objective to minimize a localization error. Two objective functions are considered for distance and geometric topology constraints. The proposed algorithm is compared with other node localization algorithms. Our algorithm outperforms the existing algorithms. The result shows that localization error is reduced up to 17% in comparison with the other algorithms. The proposed algorithm is computationally efficient due to the choice of fast converging parameters.

Smart Parking System With Privacy Preservation and Reputation Management Using Blockchain

Most of the existing smart parking systems threaten the drivers' privacy by revealing information about their visited locations. Moreover, they are centralized making them vulnerable to a single point of failure and attack, which threatens the availability of the parking service. They also suffer from a lack of transparency, where the centralized service organizer may favor some parking lots by booking their parking slots first. To tackle these concerns, we propose a blockchain-based smart parking system with privacy preservation and reputation management. In our system, a consortium blockchain is created by different parking lots to run the parking system securely and transparently, where the parking offers are recorded on a shared and immutable ledger. We use a commitment technique during the submission of the offers to ensure fair parking rates. Then, we use a private information retrieval technique during the offers retrieval to preserve the drivers' location privacy. Furthermore, to anonymously and efficiently authenticate drivers during the reservation process, we use a short randomizable signature. We also use a time-locked anonymous payment technique to discourage drivers from not committing to their parking reservations and provide a secure and privacy-preserving payment method for parking service. Finally, we integrate a blockchain-based anonymous reputation management scheme into our system, where drivers can anonymously rate the parking service to ensure high quality of service. Our evaluations demonstrate that our smart parking system is secure and capable of preserving drivers' privacy with low communication, computation, and storage overheads.

The Smart Parking Management System

With growing, Car parking increases with the number of car users. With the increased use of smartphones and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the server and are recovered by the mobile application which offers many options attractively and with no cost to users and lets the user check reservation details. With IoT technology, the smart parking system can be connected wirelessly to easily track available locations.

Maximum Likelihood Estimators for Three-Dimensional Rigid Body Localization in Internet of Things Environments

Different from the conventional point source localization, rigid body localization (RBL) not only aims to estimate the position of the target but also to acquire the attitude information, which is also essential information in many Internet of Things (IoT) applications, such as the virtual reality systems, smart parking systems. This paper develops three maximum likelihood estimators (MLEs) for the RBL purpose in 3 dimensional space via a single base station. The MLEs are designed for the RBL framework, which adopts the direction of arrival (DoA) of the signal from a small scale wireless sensor network (SSWSN) mounted on the surface of the rigid target as measurement and can be realized by a single base station. The three MLEs respectively exploit the SSWSN topology information, the DoA measurement information only, as well as the equality constraint of the rotation matrix and the DoA measurement information. In addition, we implement the modified Guass-newton algorithm for the MLEs of the rotation matrix and the translation vector. Simulations show that the proposed MLE fusing the equality constraint of the rotation matrix and the DoA measurement information most approaches the Cramer-Rao Lower Bound and also outperforms the other two MLEs in terms of convergence success rate and the computational cost.

Application of IOT Devices for Smart Car Parking System

Nowadays a car parking has become a major issue in transportation sector due to lack of parking facilities and increased number of vehicles on road. The development of Internet-of-Things (IOT) devices, networking, and mobile applications are favoring the deployment of new and smart parking sys-tems through which users can be informed in real-time about the presence of vacant parking slots. The IOT device links the objects of the real world to the virtual world and enables connectivity of anything, anytime, anywhere. This paper introduces a smart car parking system and develops a network architec-ture based on IOT technology.

Machine Learning and IoT based Real Time Parking System: Challenges and Implementation

There is a tremendous increase in number of vehicles in last two decades. So, it becomes important to make effective use of technology to enable hassle free parking at public and/or private places. In traditional parking systems, drivers face difficulty in finding available parking slots. These systems ignore the fact of parking the vehicles on roads, time management in peak hours, wrong parking of a vehicle in a parking slot. Moreover, the traditional systems require more human intervention in a parking zone. To deal with above said issues, there is an urgent requirement of developing Smart Parking Systems. In this manuscript, the authors propose a Smart Parking System based on IoT and Machine learning techniques to answer the real time management of parking and uncertainties. The proposed solution utilizes smart sensors, cloud computing and cyber physical system. Development of graphical user interface for administrator and end-user is a major challenge as it requires to ensure smooth monitoring, control and security of parking system. Moreover, it needs to establish effortless coordination with an end-user. The proposed system is successful in smartly addressing the challenges such as indicating status of parking slot well in advance to end-user, use of reserved and unreserved parking slots, wrong parking, unauthorized parking, real time analysis of free and occupied slots, detecting multiple objects in a parking slot such as bike in car slot, fault detection in one or more components and traffic management during peak hours. The system minimizes the human intervention and saves time, money and energy.

Applying smart parking system with internet of things (IoT) design

Managing parking system has become major issues in almost all malls in Jakarta. The majority of mall in Jakarta have difficulty to develop plan that enables to optimize their parking slots. Some malls use valet system to gain more profit or ease the customers, unfortunately the valet system price is quite expensive for major customers and it sounds unpopular. Therefore, many area of valet parking space is not maximized. The similar problems also faced by traditional parking system where it creates problems for customers such as difficult to find parking space, paper ticket missing and unable to locate car location. The purpose in this study is to propose a Smart Parking System (SPS) through the use of Internet of Things (IoT). The article applies smart parking system that enables online booking system, paperless ticket, cashless payments and automated guided parking. The objective of the article is expected to enhance the current online parking management system with IoT design, with the aim to be used as reference for parking management in malls.

Quality of service-based service selection in smart parking

Smartness in the existing environment is required for overall growth of any country. Government is putting tremendous effort and a huge sum of money for making cities smart to achieve smartness. A very first asset that needs to be made smart is smart parking system to avoid the traffic congestion. There are many service providers which are offering smart parking services, but there is no quality of service (QoS) framework available so far. So, for a customer point of view, it is very hard to select the best service provider and gain maximum satisfaction. So, in this paper, we have designed a QoS framework which consists of 33 metrics to evaluate a smart parking service. These parameters are identified from the user as well as vendors' perspective and help to select better service provider. We have also proposed multi criteria decision making (MCDM) approach technique for order preferences by similarity to ideal solution (TOPSIS) to select best smart parking service provider based on identified QoS. We have demonstrated our approach with the help of case studies.