Smart Parking Solutions Research Articles

NEURAL NETWORK BASED IMAGE RECOGNITION METHOD FOR SMART PARKING

With the exponential growth of vehicles on our streets, the need for finding an unoccupied parking spot today could most of the time be problematic, but even more in the coming future. Smart parking solutions have proved to be a helpful approach to facilitate the localization of unoccupied parking spots. In many smart parking solutions, sensors are used to determine the vacancy of a parking spot. i.e use of sensors can provide a highly accurate solution in terms of determining the status of parking lots. However, this is not ideal from a scalability point of view, since the need for installing and maintaining each of the sensors is not considered cost-effective. In the latest years vision based solutions have been considered more when building a smart parking solution, since cameras can easily be installed and used on a large parking area. Furthermore, the use of cameras can provide more advanced solution for finding a vacant parking spot and also for providing the safety of the car on the public parking area. This paper is aimed at the developing a Neural-Network based Image Recognition Method for Smart Parking.

A survey on smart parking systems in urban cities

SummaryParking vehicles in densely populated areas are often challenging, stressful, and sometimes it becomes a monotonous job for the drivers in jam‐packed areas. There are several reasons for the delay in finding parking spaces such as scarcity of parking slots, disordered or unmanaged parking of vehicles, lacking or unaware of parking information at the destination, which further leads to the wastage of time, fuel, energy and increase in environmental pollution. Literature has revealed a significant number of smart parking solutions based on the Internet of Things (IoT) and context‐awareness with the incorporation of routing strategies and vehicle detection techniques in a pervasive computing environment. With the rapid escalation of the smart and intelligent devices along with their applicability in a highly decentralized environment, real‐time traffic monitoring, and finding parking spaces have become quite trivial. Smart parking sensors and technologies assist drivers in finding vacant parking slots while they are on the way to their destination. Considering the needs, wants, and demands of metropolitan cities, in this article, we have reviewed the recently published articles, mostly from the last 5 years, on smart parking systems augmented with sensors, embedded systems, context‐awareness capability, and IoT which yields in saving time, fuel, energy, and reduces the stress of the drivers. To accomplish this, we have reviewed different models on smart parking solutions based on algorithmic formalisms, theoretical frameworks, formal models, smart device‐based prototypes as well as real‐time applications, and verifying the correctness properties of the system. The results shown may provide a base for the state of the art future research directions.

Ring signature and improved multi‐transaction mode consortium blockchain‐based private information retrieval for privacy‐preserving smart parking system

SummaryIn big cities, the drivers face a major problem in identifying an optimal vacant parking space for their vehicles as the number of vehicles has rapidly grown over the recent years. This objective of determining the available parking space results in wastage of time, air pollution, and traffic congestion. Smart parking systems facilitate the driver to book parking slots and attain real‐time parking information. However, the existing smart parking solutions necessitate the disclosure of sensitive information like desired destination from the vehicle drivers. Moreover, the current smart parking solutions are highly centralized, making them vulnerable for launching privacy breaches by service providers and resulting in the issues of single‐point failure. In this paper, ring signature and improved multi‐transaction mode consortium blockchain‐based private information retrieval (RS‐IMTMCB‐PIR) scheme is proposed for privacy preserving in smart parking system. This RS‐IMTMCB‐PIR scheme initially utilizes an improved multi‐transaction mode consortium blockchain constructed by different number of parking lot owners in order to achieve maximized parking offers based on the factor of availability, transparency, and security. It incorporates an improved private information retrieval approach for protecting the location privacy of drivers and secretly retrieving the offers of parking from the improved multi‐transaction mode consortium blockchain. It further utilizes the benefits of ring signature for permitting the drivers in a potential anonymous authentication process that aids in available parking slot reservation. The simulation results of this proposed RS‐IMTMCB‐PIR scheme portrayed a predominant performance in ensuring maximized degree of drivers' privacy with reduced computation and communication overheads.

Smart Parking System Based on the IR Sensor and Node MCU with the Blynk Application

Background: The prime challenge in Parking Systems is to administer the parking during peak hours or peak seasons. Besides being time consuming, it is laborious. Amalgamation of various infrastructure of hardware and software is prodigious and thus adding to its conventional hardware, making the investment in Smart Parking solution highly hazardous and splintered. Electronic payment vendors causes another crucial drawback. Objective: With the evolution of technology, we have proposed the plan to diminish human endeavors to such a degree, that a limit of one individual will be required to deal with the total colossal parking spot and a most extreme of one or two volunteers if there should arise an occurrence of any technical issues with minimal cost of operation. Methods: In our proposed work we have used Infrared Sensors at each parking slot and also used a Node Micro Controller Unit, a Wi-Fi microchip for connectivity. The Internet of Things platform used over here is Blynk. Results: The proposed technique performs better compared to existing state-of-art methodologies as it is cost-effective and easy to implement. Also, this can maintain the total vehicle count of a particular day which can be used for further traffic analysis. Conclusion: This paper presents the prototype of a Smart Parking System based on the IR sensor and Node MCU which is connected to the Blynk app that monitors the whole parking lot. It provides an optimized parking solution for various places available with parking facilities throughout the city. The proposed Smart parking system enables the guard incharge to obtain necessary information on the availability of parking space and keep a track of the effective number of vehicles that have entered the arena via a suitable app.

Deterministic and Empirical Approach for Millimeter-Wave Complex Outdoor Smart Parking Solution Deployments.

The characterization of different vegetation/vehicle densities and their corresponding effects on large-scale channel parameters such as path loss can provide important information during the deployment of wireless communications systems under outdoor conditions. In this work, a deterministic analysis based on ray-launching (RL) simulation and empirical measurements for vehicle-to-infrastructure (V2I) communications for outdoor parking environments and smart parking solutions is presented. The study was carried out at a frequency of 28 GHz using directional antennas, with the transmitter raised above ground level under realistic use case conditions. Different radio channel impairments were weighed in, considering the progressive effect of first, the density of an incremental obstructed barrier of trees, and the effect of different parked vehicle densities within the parking lot. On the basis of these scenarios, large-scale parameters and temporal dispersion characteristics were obtained, and the effect of vegetation/vehicle density changes was assessed. The characterization of propagation impairments that different vegetation/vehicle densities can impose onto the wireless radio channel in the millimeter frequency range was performed. Finally, the results obtained in this research can aid communication deployment in outdoor parking conditions.

Smart Parking Applications and Its Efficiency

Parking is a problem in many cities. Usually, it is not possible to build new parking lots due to insufficient available areas. This paper focuses on the parking situation in Slovak city Žilina. The authors carried out an extensive traffic survey in private and city-owned parking lots. Not only were occupancy data collected, but also the opinions of the drivers who parked there. The second half of the paper is based on results from the survey. It includes a proposal of the new intelligent parking system which can improve the efficiency of parking. This system is proposed in flowcharts and also described. The intelligent parking system with guidance to a free parking space can improve the traffic situation in cities. Drivers find a free parking space faster, which reduces congestion and various other negative externalities. On the other hand, the system has high acquisition costs and other problems. These issues of smart parking solutions are also discussed in the paper.

Smart Parking Systems: Reviewing the Literature, Architecture and Ways Forward

The Internet of Things (IoT) has come of age, and complex solutions can now be implemented seamlessly within urban governance and management frameworks and processes. For cities, growing rates of car ownership are rendering parking availability a challenge and lowering the quality of life through increased carbon emissions. The development of smart parking solutions is thus necessary to reduce the time spent looking for parking and to reduce greenhouse gas emissions. The principal role of this research paper is to analyze smart parking solutions from a technical perspective, underlining the systems and sensors that are available, as documented in the literature. The review seeks to provide comprehensive insights into the building of smart parking solutions. A holistic survey of the current state of smart parking systems should incorporate the classification of such systems as big vehicular detection technologies. Finally, communication modules are presented with clarity.

Sistema Automatizado de Estacionamiento para Patentes Argentinas

El mercado global de soluciones inteligentes para estacionamiento está en auge siendo altamente competitivo debido principalmente al crecimiento del parque automotor. En Argentina aún prevalece la operatoria manual. Este trabajo presenta el Sistema Automatizado de Estacionamiento (SAE), diseñado y desarrollado en su versión prototipo para una empresa privada, para controlar y gestionar el ingreso, egreso y estadía de vehículos en playas de estacionamiento. El sistema cuenta con un módulo de reconocimiento de patentes vigentes en Argentina, la placa principal que permite conectar la unidad central del sistema con los periféricos como detectores magnéticos, barreras de acceso y barreras infrarrojas, y una base de datos que almacena información necesaria para la gestión del estacionamiento. Se contemplan usuarios abonados y no abonados y tarifas para distintos tipos de vehículo, para lo cual se implementa un sistema para la detección de tamaño. El SAE maneja casos de fallo tanto de hardware como del sistema y situaciones de excepción. Se contemplan además vías de ingreso y egreso con entrada y salida de vehículos en simultáneo.

Smart Parking System with Dynamic Pricing, Edge-Cloud Computing and LoRa.

A rapidly growing number of vehicles in recent years cause long traffic jams and difficulty in the management of traffic in cities. One of the most significant reasons for increased traffic jams on the road is random parking in unauthorized and non-permitted places. In addition, managing of available parking places cannot achieve the expected reduction in traffic congestion related problems due to mismanagement, lack of real-time parking guidance to the drivers, and general ignorance. As the number of roads, highways and related resources has not increased significantly, a rising need for a smart, dynamic and effective parking solution is observed. Accordingly, with the use of multiple sensors, appropriate communication network and advanced processing capabilities of edge and cloud computing, a smart parking system can help manage parking effectively and make it easier for the vehicle owners. In this paper, we propose a multi-layer architecture for smart parking system consisting of multi-parametric parking slot sensor nodes, latest long-range low-power wireless communication technology and Edge-Cloud computation. The proposed system enables dynamic management of parking for large areas while providing useful information to the drivers about available parking locations and related services through near real-time monitoring of vehicles. Furthermore, we propose a dynamic pricing algorithm to yield maximum possible revenue for the parking authority and optimum parking slot availability for the drivers.

A Smart Parking Solution Architecture Based on LoRaWAN and Kubernetes

Finding a parking space in a city is one of the most common activities of a driver. This becomes more difficult when the city is unknown or has huge vehicular congestion. A solution to address this issue is called smart parking. Smart parking solutions rely on Internet of Things (IoT) and several technologies to achieve their purpose. This paper proposes an architecture for deploying a smart parking solution based on Long-Range Wide Area Network (LoRaWAN) sensors, LoRaWAN and a cluster of Kubernetes. This approach provides an open architecture able to share information with other parties through a REST API interface. Likewise, it contains a mobile and a web application for user interaction. This solution provides an administration interface for managing parking lots. The user interface lets a user to find, view information, display available spaces and rate a parking lot in real time. This solution could be used as an application as service parking system. The proposed architecture is fully portable and scalable due to the use of Kubernetes.

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.

Designing an integrated smart parking application

The past decade has witnessed a renewed interest in city living. Associated with this trend are parking problems in city centers and central business districts. Using the City of Pittsburgh as a case study, our study identifies a critical parking issue and how best it could be ameliorated. The study reveals that a demand-side intervention; providing real-time and predictive information to parking users, provides the most robust option in addressing the lack of parking availability in downtown Pittsburgh. Towards this end, we design a schema for an integrated smart parking application project and discuss how its functionalities could be enhanced as well as how it could be replicated in other cities. The development of the schema also includes a robust needs assessment and a user centric design process. The use of an open source platform, modular structure and ease of retrofitting can enable other cities to lower the cost of implementing and managing similar smart parking solutions.

Let My Car Alone: Parking Strategies with Social-Distance Preservation in the Age of COVID-19

Searching for an available parking space is a time-consuming and frustrating task for drivers, which also leads to huge amounts of fuel waste. Far from being solved, as the COVID-19 crisis slowly resolves, we can expect an increase in the use of private cars in comparison with public transportation, which will further aggravate the problem. Therefore, the use of smart parking solutions that help drivers to find an available parking space will become key to alleviate this problem. Moreover, existing solutions should be extended and adapted to incorporate the concept of social distancing, which is the only prevention measure (along with proper hygiene) which has been able to stop the virus so far. In this paper, we present an approach for the recommendation of parking spaces that considers social distance metrics to decide which parking spaces should be suggested to each driver. As far was we know, this problem has not been considered before in the literature. We illustrate the proposal with a use case scenario of a parking lot. Our experimental evaluation shows its feasibility and benefits.

Smart Parking: A Literature Review from the Technological Perspective

The development and high growth of the Internet of Things (IoT) have improved quality of life and strengthened different areas in society. Many cities worldwide are looking forward to becoming smart. One of the most popular use cases in smart cities is the implementation of smart parking solutions, as they allow people to optimize time, reduce fuel consumption, and carbon dioxide emissions. Smart parking solutions have a defined architecture with particular components (sensors, communication protocols, and software solutions). Although there are only three components that compose a smart parking solution, it is important to mention that each component has many types that can be used in the deployment of these solutions. This paper identifies the most used types of every component and highlights usage trends in the established analysis period. It provides a complementary perspective and represents a very useful source of information. The scientific community could use this information to decide regarding the selection of types of components to implement a smart parking solution. For this purpose, herein we review several works related to smart parking solutions deployment. To achieve this goal, a semi-cyclic adaptation of the action research methodology combined with a systematic review is used to select papers related to the subject of study. The most relevant papers were reviewed to identify subcategories for each component; these classifications are presented in tables to mark the relevance of each paper accordingly. Trends of usage in terms of sensors, protocols and software solutions are analyzed and discussed in every section. In addition to the trends of usage, this paper determines a guide of complementary features from the type of components that should be considered when implementing a smart parking solution.

Smart Vehicular System based on the Internet of Things

With the advent of smart city and its implications, different components of the smart city such as traffic, pollution monitoring, infotainment and others need to be considered as well for enabling the complete smartness. One of the major components of the smart city is regulation of traffic and its standards for smooth vehicular movement and it depends on the road conditions and environment. Road conditions provide valuable information for developing assistive systems for the vehicles and to be provided and trained with different road conditions for better accuracy and finally enabling the smartness around the system. With the increasing vehicular population around the globe and in developing countries like India, assistive systems based on Internet of Things (IoT) play a major role in developing smart systems for the vehicles. Once the population of the vehicles increases, assistive systems need a smart mechanism for parking as well. The proposed Internet of things (IoT) based system provides the user with different conditions of the road and a smart parking solution.

SecSPS: A Secure and Privacy-Preserving Framework for Smart Parking Systems

Smart parking systems are a crucial component of the “smart city” concept, especially in the age of the Internet of Things (IoT). They aim to take the stress out of finding a vacant parking spot in city centers, due to the increasing number of cars, especially during peak hours. To realize the concept of smart parking, IoT-enabling technologies must be utilized, as the traditional way of developing smart parking solutions entails a lack of scalability, compatibility with IoT-constrained devices, security, and privacy awareness. In this paper, we propose a secure and privacy-preserving framework for smart parking systems. The framework relies on the publish/subscribe communication model for exchanging a huge volume of data with a large number of clients. On one hand, it provides functional services, including parking vacancy detection, real-time information for drivers about parking availability, driver guidance, and parking reservation. On the other hand, it provides security approaches on both the network and application layers. In addition, it supports mutual authentication mechanisms between entities to ensure device/ data authenticity, and provide security protection for users. That makes our proposed framework resilient to various types of security attacks, such as replay, phishing, and man-in-the-middle attacks. Finally, we analyze the performance of our framework, which is suitable for IoT devices, in terms of computation and network overhead.

A Smart Parking Solution for Jeddah City

A Smart Parking Solution for Jeddah City

A Survey of Smart Parking Solutions

Considering the increase of urban population and traffic congestion, smart parking is always a strategic issue to work on, not only in the research field, but also from economic interests. Thanks to information and communication technology evolution, drivers can more efficiently find satisfying parking spaces with smart parking services. The existing and ongoing works on smart parking are complicated and transdisciplinary. While deploying a smart parking system, cities, as well as urban engineers, need to spend a very long time to survey and inspect all the possibilities. Moreover, many varied works involve multiple disciplines, which are closely linked and inseparable. To give a clear overview, we introduce a smart parking ecosystem and propose a comprehensive and thoughtful classification by identifying their functionalities and problematic focuses. We go through the literature over the period of 2000–2016 on parking solutions as they were applied to smart parking development and evolution, and propose three macro-themes: information collection, system deployment, and service dissemination. In each macro-theme, we explain and synthesize the main methodologies used in the existing works and summarize their common goals and visions to solve current parking difficulties. Finally, we give our engineering insights and show some challenges and open issues. Our survey gives an exhaustive study and a prospect in a multidisciplinary approach. Besides, the main findings of the current state-of-the-art throw out recommendations for future research on smart cities and the Internet architecture.

Asset-Lite Parking: Big Data Analytics in Development of Sustainable Smart Parking Solutions in Washington, D.C.

Real-time parking occupancy detection is often the missing piece when municipalities migrate up the smart parking spectrum. Municipalities use occupancy detection to ( a) provide real-time information to customers about parking availability; ( b) make demand-based price adjustments for the efficient use of curb space in a congested area; ( c) establish the right meter policies, such as time limits; and ( d) inform parking enforcement. The state of the practice for occupancy detection has been the use of assets (e.g., sensors and cameras) for every parking space. However, given current pricing models and usage patterns, this approach is neither economically sustainable nor necessary. The ParkDC Penn Quarter–Chinatown pilot launched in Washington, D.C., seeks to develop reliable occupancy data on the basis of information from all parts of the parking ecosystem (e.g., networked meters, enforcement, and pay-by-cell transactions). Combined with a sampling of occupancy data collected through limited sensor deployment, mobile cameras, and fixed cameras, Washington, D.C., aims to develop a sustainable solution based on an optimal mix of assets and coverage. The cost, customer satisfaction, revenue, and operational implications of asset-lite solutions are discussed. This paper will enable jurisdictions to develop cost-efficient models for occupancy detection so that those jurisdictions can strategically position themselves to implement real-time availability information and performance-based pricing.

Classification tree analysis of factors affecting parking choices in Qatar

Qatar has experienced a significant population growth in the past decade. The growth has been accompanied by an increase in automobile ownership rates leading to parking problems especially in the capital city of Doha. The objective of this study was to find the factors affecting people's choice of parking in this rich developing country when different parking options are available. Two commercial centers located in the city of Doha, Qatar were selected for this study; the City Center mall and the Souq Waqif shopping center. Each location has two different parking options available. Parking options vary in many features including distance to destination, paid/free, covered/open, paved/unpaved, and guarded/unguarded. In addition, the parking options also differed in the ITS infrastructure deployed in the form of intelligent parking space detection system to assist visitors to navigate to an available spot. A survey was handed out to randomly selected visitors at the main entrance of each of these shopping areas to obtain a random sample of study participants. Binary classification tree models were developed to understand the factors associated with binary parking choices at both of these commercial centers. In addition to the demographic factors associated with the parking choice; the reasons for choosing a particular parking option were also explored through the survey. The analysis of survey data presented herein provides an interesting insight into parking choices of the visitors that can be used in planning future parking facilities sand managing existing parking locations. Among the reasons cited by respondents for making their parking choices, “Intelligent Parking Space Detection” was chosen as one of the factors affecting people's choice of parking significantly more often than amenities such as “Wider parking spot”. The findings indicate that future parking investments may be better directed towards smart parking solutions.