Accurate Guidance Method and App Development for Assigning Parking Spaces Based on Indoor Wi-Fi

Existing parking guidance systems only provide road guidance outside the parking lot but do not provide accurate guidance to specific parking spaces inside the parking lot. By using a Kalman filter, the Grubbs test, and a neural network algorithm to improve the RSSI-based location fingerprint identification technology, an accurate location method based on indoor Wi-Fi is obtained, which implements precise route guidance and a reverse search function for parking spaces. We utilize Beidou positioning to develop a Gaode map for outdoor navigation and use an integrated system of ultrasonic detector/indicators and ground locks to manage parking spaces. Through the secondary development of an Android system and the application of a MySql database, an app for precise parking guidance was developed. The system makes full use of the Internet and parking information, eliminates information asymmetry, improves the utilization ratio of the urban static traffic resources, allocates parking spaces in real-time, breaks information islands, provides parking search and recommendation functions for users, achieves parking information-sharing, and effectively improves parking efficiency and the parking utilization ratio

Scalable and Efficient Clustering for Fingerprint-Based Positioning

Indoor Positioning based on wifi fingerprinting needs a reference dataset, also known as a radio map, in order to match the incoming fingerprint in the operational phase with the most similar fingerprint in the dataset and then estimate the device position indoors. Scalability problems may arise when the radio map is large, e.g., providing positioning in large geographical areas or involving crowdsourced data collection. Some researchers divide the radio map into smaller independent clusters, such that the search area is reduced to less dense groups than the initial database with similar features. Thus, the computational load in the operational stage is reduced both at the user devices and on servers. Nevertheless, the clustering models are machine-learning algorithms without specific domain knowledge on indoor positioning or signal propagation. This work proposes several clustering variants to optimize the coarse and fine-grained search and evaluates them over different clustering models and datasets. Moreover, we provide guidelines to obtain efficient and accurate positioning depending on the dataset features. Finally, we show that the proposed new clustering variants reduce the execution time by half and the positioning error by ≈7% with respect to fingerprinting with the traditional clustering models.publishedVersionPeer reviewe

Advanced Location-Based Technologies and Services

Since the publication of the first edition in 2004, advances in mobile devices, positioning sensors, WiFi fingerprinting, and wireless communications, among others, have paved the way for developing new and advanced location-based services (LBSs). This second edition provides up-to-date information on LBSs, including WiFi fingerprinting, mobile computing, geospatial clouds, geospatial data mining, location privacy, and location-based social networking. It also includes new chapters on application areas such as LBSs for public health, indoor navigation, and advertising. In addition, the chapter on remote sensing has been revised to address advancements

The always best positioned paradigm for mobile indoor applications

In this dissertation, methods for personal positioning in outdoor and indoor environments are investigated. The Always Best Positioned paradigm, which has the goal of providing a preferably consistent self-positioning, will be defined. Furthermore, the localization toolkit LOCATO will be presented, which allows to easily realize positioning systems that follow the paradigm. New algorithms were developed, which particularly address the robustness of positioning systems with respect to the Always Best Positioned paradigm. With the help of this toolkit, three example positioning-systems were implemented, each designed for different applications and requirements: a low-cost system, which can be used in conjunction with user-adaptive public displays, a so-called opportunistic system, which enables positioning with room-level accuracy in any building that provides a WiFi infrastructure, and a high-accuracy system for instrumented environments, which works with active RFID tags and infrared beacons. Furthermore, a new and unique evaluation-method for positioning systems is presented, which uses step-accurate natural walking-traces as ground truth. Finally, six location based services will be presented, which were realized either with the tools provided by LOCATO or with one of the example positioning-systems.In dieser Doktorarbeit werden Methoden zur Personenpositionierung im Innen- und Außenbereich von Gebäuden untersucht. Es wird das ,,Always Best Positioned” Paradigma definiert, welches eine möglichst lückenlose Selbstpositionierung zum Ziel hat. Weiterhin wird die Lokalisierungsplattform LOCATO vorgestellt, welche eine einfache Umsetzung von Positionierungssystemen ermöglicht. Hierzu wurden neue Algorithmen entwickelt, welche gezielt die Robustheit von Positionierungssystemen unter Berücksichtigung des ,,Always Best Positioned” Paradigmas angehen. Mit Hilfe dieser Plattform wurden drei Beispiel Positionierungssysteme entwickelt, welche unterschiedliche Einsatzgebiete berücksichtigen: Ein kostengünstiges System, das im Zusammenhang mit benutzeradaptiven öffentlichen Bildschirmen benutzt werden kann; ein sogenanntes opportunistisches Positionierungssystem, welches eine raumgenaue Positionierung in allen Gebäuden mit WLAN-Infrastruktur ermöglicht, sowie ein metergenaues Positionierungssystem, welches mit Hilfe einer Instrumentierung aus aktiven RFID-Tags und Infrarot-Baken arbeitet. Weiterhin wird erstmalig eine Positionierungsevaluation vorgestellt, welche schrittgenaue, natürliche Bewegungspfade als Referenzsystem einsetzt. Im Abschluss werden 6 lokationsbasierte Dienste vorgestellt, welche entweder mit Hilfe von LOCATO oder mit Hilfe einer der drei Beispiel-Positionierungssysteme entwickelt wurden

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity