Exploiting Recurring Patterns to Improve Scalability of Parking Availability Prediction Systems

Parking Guidance and Information (PGI) systems aim at supporting drivers in finding suitable parking spaces, also by predicting the availability at driver’s Estimated Time of Arrival (ETA), leveraging information about the general parking availability situation. To do these predictions, most of the proposals in the literature dealing with on-street parking need to train a model for each road segment, with significant scalability issues when deploying a city-wide PGI. By investigating a real dataset we found that on-street parking dynamics show a high temporal auto-correlation. In this paper we present a new processing pipeline that exploits these recurring trends to improve the scalability. The proposal includes two steps to reduce both the number of required models and training examples. The effectiveness of the proposed pipeline has been empirically assessed on a real dataset of on-street parking availability from San Francisco (USA). Results show that the proposal is able to provide parking predictions whose accuracy is comparable to state-of-the-art solutions based on one model per road segment, while requiring only a fraction of training costs, thus being more likely scalable to city-wide scenarios

Survey of smart parking systems

The large number of vehicles constantly seeking access to congested areas in cities means that finding a public parking place is often difficult and causes problems for drivers and citizens alike. In this context, strategies that guide vehicles from one point to another, looking for the most optimal path, are needed. Most contributions in the literature are routing strategies that take into account different criteria to select the optimal route required to find a parking space. This paper aims to identify the types of smart parking systems (SPS) that are available today, as well as investigate the kinds of vehicle detection techniques (VDT) they have and the algorithms or other methods they employ, in order to analyze where the development of these systems is at today. To do this, a survey of 274 publications from January 2012 to December 2019 was conducted. The survey considered four principal features: SPS types reported in the literature, the kinds of VDT used in these SPS, the algorithms or methods they implement, and the stage of development at which they are. Based on a search and extraction of results methodology, this work was able to effectively obtain the current state of the research area. In addition, the exhaustive study of the studies analyzed allowed for a discussion to be established concerning the main difficulties, as well as the gaps and open problems detected for the SPS. The results shown in this study may provide a base for future research on the subject.Fil: Diaz Ogás, Mathias Gabriel. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Fabregat Gesa, Ramon. Universidad de Girona; EspañaFil: Aciar, Silvana Vanesa. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentin

Gestión inteligente del estacionamiento empleando internet de las cosas

The main requirement of smart cities is intelligent and effective parking system, which currently most parking systems exist basedon various technologies such as Internet of Things, so intelligent parking management is gradually becoming a necessity. Hence inthis article a new manner is introduced in the form of prioritization, which alters the type of prioritization than the previous methods, sothat the different parameters such as the distance between parking lots, distance between vehicle and a parking lot, number of freeparking spaces in the destination parking lot, number of unsuccessful parks, and the number of parking lot visits are considered, and ingeneral a system is recommended that helps drivers to find a parking lot with the minimum cost based on the aforesaid parameters. Thesimulation of proposed approach performed in Arena application and the results of the simulation and its comparison with theprevious works suggest that the proposed method results in the better decrease of the waiting time than the existing waiting timein the previous works and contributes to minimize drivers waiting time

Smart mobility: a survey

Internet of Things (IoT) describes a world where everyday objects are always connected to the Internet, allowing them to communicate and interact with each other. By connecting these everyday objects to the Internet and making them available everywhere at any time, IoT allows to remotely monitor, manage, and gather status information about them and their surrounding environment. IoT is a revolutionary concept that brought new experiences to everyday life and enabled Smart City initiatives all over the world. These initiatives are using a combination of technology paired with physical infrastructure and services, to improve people’s quality of life. One of the high priority domain to support the Smart City’s vision is the field of Smart Mobility. This paper reviews the current IoT approaches and concepts related to Smart Cities and Smart Mobility. In addition, it analyzes distinct features and numerous applications covering both Intelligent Transportation and Real Time Traffic Management Systems.info:eu-repo/semantics/publishedVersio

Trends in Smart City Development

This report examines the meanings and practices associated with the term 'smart cities.' Smart city initiatives involve three components: information and communication technologies (ICTs) that generate and aggregate data; analytical tools which convert that data into usable information; and organizational structures that encourage collaboration, innovation, and the application of that information to solve public problems

Smart mobility: a survey

Internet of Things (IoT) describes a world where everyday objects are always connected to the Internet, allowing them to communicate and interact with each other. By connecting these everyday objects to the Internet and making them available everywhere at any time, IoT allows to remotely monitor, manage, and gather status information about them and their surrounding environment. IoT is a revolutionary concept that brought new experiences to everyday life and enabled Smart City initiatives all over the world. These initiatives are using a combination of technology paired with physical infrastructure and services, to improve people's quality of life. One of the high-priority domain to support the Smart City's vision is the field of Smart Mobility. This paper reviews the current IoT approaches and concepts related to Smart Cities and Smart Mobility. In addition, it analyzes distinct features and numerous applications covering both Intelligent Transportation and Real Time Traffic Management Systems

A Practical Review to Support the Implementation of Smart Solutions within Neighbourhood Building Stock

The construction industry has witnessed an increase in the use of digital tools and smart solutions, particularly in the realm of building energy automation. While realising the potential benefits of smart cities, a broader scope of smart initiatives is required to support the transition from smart buildings towards smart neighbourhoods, which are considered critical urban development units. To support the interplay of smart solutions between buildings and neighbourhoods, this study aimed to collect and review all the smart solutions presented in existing scientific articles, the technical literature, and realised European projects. These solutions were classified into two main sections, buildings and neighbourhoods, which were investigated through five domains: building-energy-related uses, renewable energy sources, water, waste, and open space management. The quantitative outcomes demonstrated the potential benefits of implementing smart solutions in areas ranging from buildings to neighbourhoods. Moreover, this research concluded that the true enhancement of energy conservation goes beyond the building’s energy components and can be genuinely achieved by integrating intelligent neighbourhood elements owing to their strong interdependencies. Future research should assess the effectiveness of these solutions in resource conservation

Vacant Parking Lot Information System Using Transfer Learning and IoT

Parking information systems have become very important, especially in metropolitan areas as they help to save time, effort and fuel when searching for parking. This paper offers a novel low-cost deep learning approach to easily implement vacancy detection at outdoor parking spaces with CCTV surveillance. The proposed method also addresses issues due to perspective distortion in CCTV images. The architecture consists of three classifiers for checking the availability of parking spaces. They were developed on the TensorFlow platform by re-training MobileNet (a pre-trained Convolutional Neural Network (CNN)) model using the transfer learning technique. A performance analysis showed 88% accuracy for vacancy detection. An end-to-end application model with Internet of Things (IoT) and an Android application is also presented. Users can interact with the cloud using their Android application to get real-time updates on parking space availability and the parking location. In the future, an autonomous car could use this system as a V2I (Vehicle to Infrastructure) application in deciding the nearest parking space