Mobile Crowdsourcing: Towards Smart Cities

Abstract

Leveraging new Artificial Intelligence (AI) technologies and Internet of Things (IoT) applications, local administrations, and governments aim at managing the city infrastructures and optimize the public services in an efficient and sustainable manner. Furthermore, they adopt intelligent and cost-effective mobile applications to deal with natural disasters, such as pollution and traffic congestion. Mobile crowdsourcing (MCS) is an emerging paradigm for enabling smart cities, which integrates the wisdom of dynamic crowds with ubiquitous mobile devices to provide decentralized applications and services. Using MCS solutions, residents play the role of an active worker to generate a wealth of crowdsourced data which can significantly promote the development of smart cities. This talk highlights research challenges in computing and analyzing mobile crowdsourced data generated by a large amount of participants/devices, and fusing multi-source and heterogeneous urban big data to facilitate applications towards smart cities.

Biography

UDr. Xiangjie Kong received the Ph. D. degree from Zhejiang University, Hangzhou, China in 2009. Currently, he is Full professor of College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China. He was previously an Associate Professor in School of Software, Dalian University of technology, Dalian, China. He has served as Associate Editor of IEEE Access (2017-2019), Editor of PeerJ Computer Science (2018-), Editor of KSII Transactions on Internet and Information Systems (2016-), Editor of SpringerPlus (2015-2016), Guest Editor of several international journals, Workshop Chair or PC Member of a number of conferences. Dr. Kong has published over 140 scientific papers in international journals and conferences including IEEE TKDE, IEEE TII, IEEE COMMUN MAG, IEEE TVT, IEEE IOTJ, IEEE TSMC, IEEE TETC, IEEE TASE, WWWJ, FGCS, JNCA, AD HOC NETW, IJRNC SCIM, WWW, etc. His research interests include big data, mobile computing, and computational social science. He is a Senior Member of IEEE and CCF, and a Member of ACM.