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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Enabling Smart Urban Services with GPS Trajectory Data
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Enabling Smart Urban Services with GPS Trajectory Data
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Enabling Smart Urban Services With Gps Trajectory Data
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Enabling Smart Urban Services With Gps Trajectory Data
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Enabling Smart Urban Services with GPS Trajectory Data
Language: English
Published by Springer Nature Singapore, 2022
ISBN 10: 9811601801 ISBN 13: 9789811601804
Condition: Hervorragend. Zustand: Hervorragend | Seiten: 368 | Sprache: Englisch | Produktart: Bücher | 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 tothe 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 openissues in mining GPS trajectory data.
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Add to basketHardcover. Condition: Brand New. 366 pages. 9.25x6.10x1.10 inches. In Stock.
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Add to basketPaperback. Condition: Brand New. 366 pages. 9.25x6.10x0.91 inches. In Stock. This item is printed on demand.
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Enabling Smart Urban Services with GPS Trajectory Data
Language: English
Published by Springer, Berlin|Springer Nature Singapore|Springer, 2022
ISBN 10: 9811601801 ISBN 13: 9789811601804
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 d.
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.  Addresses fundamental issues in trajectory data, including data map-matching, data compression, and data protectionPromotes smart mobility services to benefit a wide range of people including drivers, travellers, passengers, and urban planners.
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Condition: New. PRINT ON DEMAND.
