Enabling Smart Urban Services With Gps Trajectory Data
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Author | : Chao Chen |
Publisher | : Springer Nature |
Total Pages | : 351 |
Release | : 2021-04-01 |
Genre | : Computers |
ISBN | : 981160178X |
With the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale. As one of the most typical representatives, it has now become widely recognized that taxi trajectory data provides rich opportunities to enable promising smart urban services. Yet, a considerable gap still exists between the raw data available, and the extraction of actionable intelligence. This gap poses fundamental challenges on how we can achieve such intelligence. These challenges include inaccuracy issues, large data volumes to process, and sparse GPS data, to name but a few. Moreover, the movements of taxis and the leaving trajectory data are the result of a complex interplay between several parties, including drivers, passengers, travellers, urban planners, etc. In this book, we present our latest findings on mining taxi GPS trajectory data to enable a number of smart urban services, and to bring us one step closer to the vision of smart mobility. Firstly, we focus on some fundamental issues in trajectory data mining and analytics, including data map-matching, data compression, and data protection. Secondly, driven by the real needs and the most common concerns of each party involved, we formulate each problem mathematically and propose novel data mining or machine learning methods to solve it. Extensive evaluations with real-world datasets are also provided, to demonstrate the effectiveness and efficiency of using trajectory data. Unlike other books, which deal with people and goods transportation separately, this book also extends smart urban services to goods transportation by introducing the idea of crowdshipping, i.e., recruiting taxis to make package deliveries on the basis of real-time information. Since people and goods are two essential components of smart cities, we feel this extension is bot logical and essential. Lastly, we discuss the most important scientific problems and open issues in mining GPS trajectory data.
Author | : Chao Chen |
Publisher | : Springer Nature |
Total Pages | : 351 |
Release | : 2021-04-01 |
Genre | : Computers |
ISBN | : 981160178X |
With the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale. As one of the most typical representatives, it has now become widely recognized that taxi trajectory data provides rich opportunities to enable promising smart urban services. Yet, a considerable gap still exists between the raw data available, and the extraction of actionable intelligence. This gap poses fundamental challenges on how we can achieve such intelligence. These challenges include inaccuracy issues, large data volumes to process, and sparse GPS data, to name but a few. Moreover, the movements of taxis and the leaving trajectory data are the result of a complex interplay between several parties, including drivers, passengers, travellers, urban planners, etc. In this book, we present our latest findings on mining taxi GPS trajectory data to enable a number of smart urban services, and to bring us one step closer to the vision of smart mobility. Firstly, we focus on some fundamental issues in trajectory data mining and analytics, including data map-matching, data compression, and data protection. Secondly, driven by the real needs and the most common concerns of each party involved, we formulate each problem mathematically and propose novel data mining or machine learning methods to solve it. Extensive evaluations with real-world datasets are also provided, to demonstrate the effectiveness and efficiency of using trajectory data. Unlike other books, which deal with people and goods transportation separately, this book also extends smart urban services to goods transportation by introducing the idea of crowdshipping, i.e., recruiting taxis to make package deliveries on the basis of real-time information. Since people and goods are two essential components of smart cities, we feel this extension is bot logical and essential. Lastly, we discuss the most important scientific problems and open issues in mining GPS trajectory data.
Author | : Yongxuan Lai |
Publisher | : Springer Nature |
Total Pages | : 810 |
Release | : 2022-02-22 |
Genre | : Computers |
ISBN | : 3030953912 |
The three volume set LNCS 13155, 13156, and 13157 constitutes the refereed proceedings of the 21st International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2021, which was held online during December 3-5, 2021. The total of 145 full papers included in these proceedings were carefully reviewed and selected from 403 submissions. They cover the many dimensions of parallel algorithms and architectures including fundamental theoretical approaches, practical experimental projects, and commercial components and systems. The papers were organized in topical sections as follows: Part I, LNCS 13155: Deep learning models and applications; software systems and efficient algorithms; edge computing and edge intelligence; service dependability and security algorithms; data science; Part II, LNCS 13156: Software systems and efficient algorithms; parallel and distributed algorithms and applications; data science; edge computing and edge intelligence; blockchain systems; deept learning models and applications; IoT; Part III, LNCS 13157: Blockchain systems; data science; distributed and network-based computing; edge computing and edge intelligence; service dependability and security algorithms; software systems and efficient algorithms.
Author | : Keng Hua Chong |
Publisher | : Taylor & Francis |
Total Pages | : 335 |
Release | : 2024-11-29 |
Genre | : Business & Economics |
ISBN | : 1040255531 |
This book couples data analytics with social behavioural studies and participatory design to derive deeper insights on city dwellers’ present needs and future aspirations, thereby enabling the development of targeted spatial and programmatic interventions for diverse communities. Public housing in Singapore has been regarded internationally as a success story. This book outlines the latest strategies and concepts for addressing the emerging social challenges of the ageing population: shrinking household size, increasingly diverse demographics and widening inequality, and fostering inclusive and resilient neighbourhoods. Adopting an interdisciplinary approach, this book: Outlines an innovative data-driven planning process for housing neighbourhood and community design Provides a framework for planners and designers to synthesise qualitative and quantitative data analyses Presents a comprehensive set of tested urban analytics tools, digital platforms and participatory toolkits used to design and develop community initiatives. A recommended text for students undertaking urban planning, urban design, housing design, architecture, real estate, urban sociology and community design, the book’s strategies for evidence-based neighbourhood designs will also appeal to practitioners and policymakers.
Author | : Ivan Nunes Da Silva |
Publisher | : BoD – Books on Demand |
Total Pages | : 248 |
Release | : 2016-12-07 |
Genre | : Technology & Engineering |
ISBN | : 9535128078 |
What are smart cities? What are their purposes? What are the impacts resulting from their implementations? With these questions in mind, this book is compiled with the primary concern of answering readers with different profiles; from those interested in acquiring basic knowledge about the various topics surrounding the subject related to smart cities, to those who are more motivated by knowing the technical elements and the technological apparatus involving this theme. This book audience is multidisciplinary, as it will be confirmed by the various chapters addressed here. It explores different knowledge areas, such as electric power systems, signal processing, telecommunications, electronics, systems optimization, computational intelligence, real-time systems, renewable energy systems, and information systems.
Author | : Fadi Al-Turjman |
Publisher | : CRC Press |
Total Pages | : 194 |
Release | : 2018-12-19 |
Genre | : Computers |
ISBN | : 0429663633 |
Smart Cities and intelligence are among the most significant topics in IoT. Intelligence in communication and infrastructure implementation is at the heart of this concept, and its development is a key issue in smart cities. This book addresses the challenges in realizing intelligence in smart cities and sensing platforms in the era of cloud computing and IoT, varying from cost and energy efficiency to availability and service quality. It focuses on both the design and implementation aspects of artificial intelligence approaches in smart cities and sensing applications that are enabled and supported by IoT paradigms, and mainly on data delivery approaches and their performability aspects.
Author | : Zhidan Liu |
Publisher | : Springer Nature |
Total Pages | : 75 |
Release | : 2021-05-18 |
Genre | : Computers |
ISBN | : 9811622418 |
This book introduces the concepts of mobility data and data-driven urban traffic monitoring. A typical framework of mobility data-based urban traffic monitoring is also presented, and it describes the processes of mobility data collection, data processing, traffic modelling, and some practical issues of applying the models for urban traffic monitoring. This book presents three novel mobility data-driven urban traffic monitoring approaches. First, to attack the challenge of mobility data sparsity, the authors propose a compressive sensing-based urban traffic monitoring approach. This solution mines the traffic correlation at the road network scale and exploits the compressive sensing theory to recover traffic conditions of the whole road network from sparse traffic samplings. Second, the authors have compared the traffic estimation performances between linear and nonlinear traffic correlation models and proposed a dynamical non-linear traffic correlation modelling-based urban traffic monitoring approach. To address the challenge of involved huge computation overheads, the approach adapts the traffic modelling and estimations tasks to Apache Spark, a popular parallel computing framework. Third, in addition to mobility data collected by the public transit systems, the authors present a crowdsensing-based urban traffic monitoring approach. The proposal exploits the lightweight mobility data collected from participatory bus riders to recover traffic statuses through careful data processing and analysis. Last but not the least, the book points out some future research directions, which can further improve the accuracy and efficiency of mobility data-driven urban traffic monitoring at large scale. This book targets researchers, computer scientists, and engineers, who are interested in the research areas of intelligent transportation systems (ITS), urban computing, big data analytic, and Internet of Things (IoT). Advanced level students studying these topics benefit from this book as well.
Author | : Giancarlo Fortino |
Publisher | : Springer Science & Business Media |
Total Pages | : 203 |
Release | : 2014-04-04 |
Genre | : Technology & Engineering |
ISBN | : 3319004913 |
The Internet of Things (IoT) usually refers to a world-wide network of interconnected heterogeneous objects (sensors, actuators, smart devices, smart objects, RFID, embedded computers, etc) uniquely addressable, based on standard communication protocols. Beyond such a definition, it is emerging a new definition of IoT seen as a loosely coupled, decentralized system of cooperating smart objects (SOs). A SO is an autonomous, physical digital object augmented with sensing/actuating, processing, storing, and networking capabilities. SOs are able to sense/actuate, store, and interpret information created within themselves and around the neighbouring external world where they are situated, act on their own, cooperate with each other, and exchange information with other kinds of electronic devices and human users. However, such SO-oriented IoT raises many in-the-small and in-the-large issues involving SO programming, IoT system architecture/middleware and methods/methodologies for the development of SO-based applications. This Book will specifically focus on exploring recent advances in architectures, algorithms, and applications for an Internet of Things based on Smart Objects. Topics appropriate for this Book include, but are not necessarily limited to: - Methods for SO development - IoT Networking - Middleware for SOs - Data Management for SOs - Service-oriented SOs - Agent-oriented SOs - Applications of SOs in Smart Environments: Smart Cities, Smart Health, Smart Buildings, etc. Advanced IoT Projects.
Author | : Stan Geertman |
Publisher | : Springer |
Total Pages | : 506 |
Release | : 2019-05-09 |
Genre | : Science |
ISBN | : 3030194248 |
This book contains a selection of the best articles presented at the CUPUM (Computational Urban Planning and Urban Management) conference, held in the second week of July 2019 at the University of Wuhan, China. The chapters included were selected based on a double-blind review process involving external reviewers.
Author | : Baoguo Han |
Publisher | : Elsevier |
Total Pages | : 588 |
Release | : 2020-02-13 |
Genre | : Technology & Engineering |
ISBN | : 0128199237 |
Nanosensors for Smart Cities covers the fundamental design concepts and emerging applications of nanosensors for the creation of smart city infrastructures. Examples of major applications include logistics management, where nanosensors could be used in active transport tracking devices for smart tracking and tracing, and in agri-food productions, where nanosensors are used in nanochips for identity, and food inspection, and smart storage. This book is essential reading for researchers working in the field of advanced sensors technology, smart city technology and nanotechnology, and stakeholders involved in city management. Nanomaterials based sensors (nanosensors) can offer many advantages over their microcounterparts, including lower power consumption, high sensitivity, lower concentration of analytes, and smaller interaction distance between object and sensor. With the support of artificial intelligence (AI) tools, such as fuzzy logic, genetic algorithms, neural networks, and ambient-intelligence, sensor systems are becoming smarter. - Provides information on the fabrication and fundamental design concepts of nanosensors for intelligent systems - Explores how nanosensors are being used to better monitor and maintain infrastructure services, including street lighting, traffic management and pollution control - Assesses the challenges for creating nanomaterials-enhanced sensors for mass-market consumer products