Data-Driven Smart Cities (DASC 2022)

Workshop Description

Today, cities play a crucial role as the engines of the economy and centres of connectivity, knowledge, and services [1]. Based on the estimation from the United Nations, 66% of the world’s population will live in urban areas by 2050 [2]. Therefore, being the centres of growth and innovation, cities need to take responsibility for environment protection and citizens’ living comfort. In recent years, with the growing interest to Internet of Things (IoT), cities are getting equipped with ICT technologies to improve their efficiency and quality of life of their inhabitants, therefore transforming themselves into Smart cities [3].

There are different perspectives on the development of Smart cities. Some focus on integrating ICT into urban environments and on performing complex analytics, modelling, and optimization for cross-sector collaboration and better operational decisions; others on sustainability, wealth and comfort support and needs of people and community [4]. However, for all these cases, data is the key ingredient and enabler for the vision and realization of Smart cities. Therefore, there is a strong need to share the expertise to use the data in intelligent and efficient way to produce viable long-living solutions.

Workshop Objectives

This workshop on Data-driven Smart Cities (DASC 2022) aims to gather professionals from municipalities, industry, and academia focusing on different aspects of Smart city. The purpose of the session is to discuss the latest scientific results and practical use cases, identify the opportunities and challenges of novel best methods and practices on data-driven Smart cities.

Therefore, the aims of this workshop are to:

Timetable

Important Dates

All deadlines are 11:59PM CEST.

Workshop Format

Keynote Talks

50 minutes for academia expert

Technical Presentation

20 – 30 minutes for each accepted paper with 3 sessions

Interactive Panel Discussion

50 minutes discussion

Notes on Workshop Research Papers

Organizing Committee

Dr. Ekaterina Gilman (ekaterina.gilman@oulu.fi) is Academy of Finland postdoc fellow at the Center for Ubiquitous Computing, University of Oulu, Finland. She has been visiting scholar in Biobank Borealis and Centre for Health and Technology. She has been working in various national and international projects, funded by Tekes Finland, Academy of Finland, Horizon 2020 programme. Her current research interests include data analytics, context modelling and reasoning, and machine learning in ubiquitous computing, IoT, and data-intensive systems. Ekaterina Gilman actively contributes to community as the journals’ reviewer, invited speaker, lecturer, and TPC member. She has 40 publications in international journals and conference proceedings.

Dr. Xiang Su (xiang.su@ntnu.no) is an associate professor at the Department of Computer Science, Norwegian University of Science and Technology, Norway. Prior to NTNU, he was an Academy of Finland postdoc fellow (with ranking No. 1 in all applicants of Computer Science panel) and a senior postdoctoral researcher at Department of Computer Science, University of Helsinki. He has been working in Hong Kong University of Science and Technology, Aalto University, VTT Technical Research Center of Finland, Technical University of Munich, and Carnegie Mellon University as a visiting scholar. He has been involved as a PI, co-PI, scientist and a deliverable leader in several research projects funded by Tekes Finland, Academy of Finland, EU program, and National Natural Science Foundation of China. His research interests cover Internet of Things (IoT), edge computing stream processing, knowledge representations, and context modeling and reasoning. He has published more than 60 peer-reviewed journal and conference articles. Su received a PhD in technology from the University of Oulu.

Dr. Theodoros Anagnostopoulos (thanag@uniwa.gr) was born in Athens, Greece in 1976. He received the B.Eng. degree in computer engineering from the University of West Attica, Greece, in 1997, the B.Sc. and the M.Sc.IS. degrees in applied computer science from the Athens University of Economics and Business, Greece, in 2001 and 2003, respectively. He received the Ph.D. degree in computer science from the National and Kapodistrian University of Athens, Greece, in conjunction with the University of Geneva, Switzerland, in 2012. He also received the M.Ed.Sc. in Education Sciences from the Hellenic Open University, Greece, in 2018. He has worked in private and public sector as well as in industry and academia worldwide. He has also chase funding and involved in national and international academic research and industrial innovation projects. Currently, he holds a Lecturer (Teaching) position in computer science at the DigiT.DSS.Lab at the Department of Business Administration at the University of West Attica, Greece. Dr. Theodoros Anagnostopoulos holds two patents, in U.S. and E.U., where he is the inventor, while IP is with Ordnance Survey: Great Britain’s Mapping Authority, U.K.

Dr. Hao Wang (hawa@ntnu.no) is an associate professor in the Department of Computer Science in Norwegian University of Science & Technology, Norway. He received his Ph.D. degree and a B.Eng. degree, both in computer science and engineering, from South China University of Technology, China in 2006 and 2000, respectively. His research interests include big data analytics, industrial internet of things, high performance computing, and safety-critical systems. He has published 170+ papers in reputable international journals and conferences including IEEE TKDE, TIE, TII, IoTJ, TCAD, TGRS and ACM CSUR. He serves as the editorial board member and guest editors for several international journals. He served as a TPC co-chair for IEEE CPSCom 2020, IEEE CIT 2017, ES 2017, IEEE DataCom 2015, a senior TPC member for ACM CIKM 2019, and reviewers for many prestigious journals and conferences. He is a senior member of IEEE and a member of ACM. He is the Chair for Sub TC on Healthcare in IEEE IES Technical Committee on Industrial Informatics.

References