Enabling Smart Urban Services with GPS Trajectory Data
暫譯: 利用GPS軌跡數據啟用智慧城市服務
Chen, Chao, Zhang, Daqing, Wang, Yasha
- 出版商: Springer
- 出版日期: 2021-04-02
- 售價: $7,920
- 貴賓價: 9.5 折 $7,524
- 語言: 英文
- 頁數: 347
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 9811601771
- ISBN-13: 9789811601774
海外代購書籍(需單獨結帳)
相關主題
商品描述
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.
商品描述(中文翻譯)
隨著 GPS 設備在日常生活中的普及，記錄人們移動時間和地點的軌跡數據現在已經在大規模上變得易於獲取。作為最典型的代表之一，出租車軌跡數據已廣泛被認識為提供豐富機會以促進有前景的智慧城市服務。然而，現有的原始數據與可提取的可行智慧之間仍然存在相當大的差距。這一差距對於我們如何實現這種智慧提出了根本性的挑戰。這些挑戰包括不準確性問題、大量數據需要處理以及稀疏的 GPS 數據等等。此外，出租車的移動和離開的軌跡數據是多方之間複雜互動的結果，包括司機、乘客、旅客、城市規劃者等。
在本書中，我們展示了在挖掘出租車 GPS 軌跡數據方面的最新研究成果，以促進多項智慧城市服務，並使我們更接近智慧移動的願景。首先，我們專注於軌跡數據挖掘和分析中的一些基本問題，包括數據地圖匹配、數據壓縮和數據保護。其次，根據每個相關方的實際需求和最常見的關注點，我們將每個問題數學化，並提出新穎的數據挖掘或機器學習方法來解決它。還提供了使用真實世界數據集的廣泛評估，以展示使用軌跡數據的有效性和效率。
與其他分別處理人員和貨物運輸的書籍不同，本書還通過引入眾包運輸的概念，即根據實時信息招募出租車進行包裹配送，將智慧城市服務擴展到貨物運輸。由於人員和貨物是智慧城市的兩個基本組成部分，我們認為這一擴展既合乎邏輯又至關重要。最後，我們討論了挖掘 GPS 軌跡數據中最重要的科學問題和未解決的議題。
作者簡介
Chao Chen is a Full Professor of Computer Science at Chongqing University. He received his Ph.D. in Computer Science from Pierre and Marie Curie University and Institut Mines-Télécom/Télécom SudParis, France in 2014. He has authored or co-authored more than 100 papers including 20 ACM/IEEE Transactions. His research interests include pervasive computing, mobile computing, urban logistics, data mining from large-scale taxi GPS trajectory data, and big data analytics for smart cities. Dr. Chen's work on taxi trajectory data mining was featured by IEEE SPECTRUM in 2011, 2016 and 2020, respectively. He was also the winner of the Best Paper Runner-Up Award at MobiQuitous 2011.
Daqing Zhang is a Chair Professor at Peking University, China. He received his Ph.D. from the University of Rome "La Sapienza" and University of L'Aquila in 1996. He has authored or co-authored more than 180 referred journal and conference papers, particularly on practical applications in digital cities, mobile social networks, and elderly care. His research interests include large-scale data mining, urban computing, context-aware computing, and ambient assistive living. He is a recipient of the 10 Years CoMoRea Impact Paper Award at IEEE PerCom 2013, the Best Paper Award at IEEE UIC 2015/2012, and the Best Paper Runner Up Award at MobiQuitous 2011.
Yasha Wang is a Full Professor and Associate Director of the National Research and Engineering Center of Software Engineering at Peking University, China. He received his Ph.D. from Northeastern University, Shenyang, China, in 2003. He also served as the head of the technical special group of the National Big Data Standards Committee of China, and as a standing committee member of the ubiquitous computing special interest group of CCF. He has long been engaged in research in the fields of data analysis, ubiquitous computing, and urban computing, and has published more than 100 papers in international high-level academic conference proceedings and journals such as IEEE TMC, ACM Ubicomp, IEEE ICDE, ACM CSCW, AAAI, and IJCAI. Cooperating with major smart-city solution providers, the results of his work have been adopted in more than 20 Chinese cities.
Hongyu Huang is an Associate Professor of Computer Science at Chongqing University. He received his B.S. degree from Chongqing Normal University in 2002, his M.S. from Chongqing University in 2005, and his Ph.D. from Shanghai Jiao Tong University in 2009. His research interests include mobile crowd-sensing, privacy preserving computing, and vehicular ad hoc networks.
作者簡介(中文翻譯)
趙晨是重慶大學的計算機科學全職教授。他於2014年在法國皮埃爾與瑪麗居里大學及法國礦業電信學院/電信南巴黎獲得計算機科學博士學位。他已發表或共同發表超過100篇論文，包括20篇ACM/IEEE期刊論文。他的研究興趣包括普適計算、移動計算、城市物流、大規模計程車GPS軌跡數據的數據挖掘，以及智慧城市的大數據分析。趙博士在計程車軌跡數據挖掘方面的工作曾於2011年、2016年和2020年分別被IEEE SPECTRUM報導。他還曾獲得2011年MobiQuitous最佳論文亞軍獎。
張大慶是中國北京大學的講座教授。他於1996年在羅馬大學「拉薩比恩扎」及拉奎拉大學獲得博士學位。他已發表或共同發表超過180篇經過審核的期刊和會議論文，特別是在數位城市、移動社交網絡和老年護理的實際應用方面。他的研究興趣包括大規模數據挖掘、城市計算、情境感知計算和環境輔助生活。他是2013年IEEE PerCom 10年CoMoRea影響力論文獎、2015/2012年IEEE UIC最佳論文獎，以及2011年MobiQuitous最佳論文亞軍獎的獲得者。
王雅莎是中國北京大學軟體工程國家研究與工程中心的全職教授及副主任。他於2003年在中國沈陽的東北大學獲得博士學位。他還曾擔任中國國家大數據標準委員會技術專門組的負責人，以及中國計算機學會普適計算特別興趣小組的常務委員。他長期從事數據分析、普適計算和城市計算等領域的研究，並在IEEE TMC、ACM Ubicomp、IEEE ICDE、ACM CSCW、AAAI和IJCAI等國際高水平學術會議和期刊上發表了超過100篇論文。與主要智慧城市解決方案提供商合作，他的研究成果已在20多個中國城市得到應用。
黃洪宇是重慶大學的計算機科學副教授。他於2002年在重慶師範大學獲得學士學位，2005年在重慶大學獲得碩士學位，2009年在上海交通大學獲得博士學位。他的研究興趣包括移動群眾感知、隱私保護計算和車輛自組網。
