Frontiers of Data and Knowledge Management for Convergence of ICT, Healthcare, and Telecommunication Services

This book provides a range of application areas of data and knowledge management and their solutions for the fields related to the convergence of information and communication technology (ICT), healthcare, and telecommunication services. The authors present approaches and case studies in future technological trends and challenges in the aforementioned fields. The book acts as a scholarly forum for researchers both in academia and industry.

Suman Paul  is currently an Assistant Professor, Department of Electronics and Communication Engineering, Haldia Institute of Technology, India. He interests in scheduling, QoS in communication networks, application of soft computing techniques in networking, applications of IoT.  Professor Paul worked as associate researcher in the Indian Institute of Management (IIM), Calcutta in a project on Zigbee based wireless sensor network, funded by DIT, Govt.of India.  He is a regular reviewer of SCIE/Scopus indexed journals. Professor Paul has published books on Mobile Ad Hoc Network, research articles in science citation index journals of repute including Springer, transaction of  Korean Society for Internet Information etc., book chapters of Springer and presented papers in IEEE International conferences. He was the  joint convener of the International Conference, ICCDC 2019, Haldia, India. He is a member of ACM, Machine Intelligence Research Labs, USA and qualified Cisco Certified Network Associate.

Sara Paiva is an Assistant Professor at the Polytechnic Institute of Viana do Castelo, a PhD in Informatics Engineering from University of Vigo in 2011 and a Postdoctoral Researcher at the University of Oviedo, under advanced driving assistants. Her main line of research is smart inclusive mobility in smart cities. She is currently Vice-Chair of the IEEE Smart Cities Marketing Committee, Editor in Chief of EAI Endorsed Transaction on Smart Cities, Associate Editor in several IF journals such as MONET and WINET and member of the Editorial Board of the 5.2 IF International Journal of Sustainable Cities and Society. She is General Co-Chair of the EAI International Convention on Smart Cities 360º since the 2020 edition and is part of the Organizing Committee of IEEE Smart Cities 2021. She acts as Scientific Evaluator of Individual Scientist Project Proposals for Fundamental and Applied Research for the Latvian Council of Science, she is Founding Fellow of AI Live Talks, in partnership with IEEE. She is also editor of books with Springer, CRC Press, Cambridge Scholar, and special issues in several impact factor journals. She has authored and co-authored several scientific publications in journals and conferences and is a frequent reviewer of international journals and international conferences.

Dr. Bo Fu is an Assistant Professor in the Department of Computer Engineering and Computer Science at California State University Long Beach (CSULB), California, USA. Dr. Fu received her B.Sc. (Joint Hons.), M.Sc., and Ph.D. in Computer Science from Trinity College Dublin, Ireland. Prior to  joining  CSULB, Dr. Fu was a Research Scientist at the National Center for Biomedical Ontology, and a Postdoctoral Fellow at the University of Victoria, Canada.

Dr. Fu’s  research intersects Web Semantics and Human Data Interaction. She is interested  in

accelerating research and innovation in semantic-oriented intelligent systems and interactive visual analytics that facilitate human decision-making. Through semantics and interaction, the overall  goal of her research is to help people make sense of complex datasets during the process of turning data to information, to knowledge,  and to wisdom in collective intelligence.

Dr. Fu has published her research at premier journals and conferences including the Semantic Web Journal, the Journal of Web Semantics, the International Semantic Web Conference, and the Extended Semantic Web Conference. She has chaired and reviewed numerous scientific panels and committees, such as National Science Foundation programs, Big Data Research, Artificial Intelligence in Medicine, and BMC Bioinformatics.