Data Science and Internet of Things: Research and Applications at the Intersection of DS and IoT - Tapa blanda

Acerca del autor

Giancarlo Fortino (SM’12) is Full Professor of Computer Engineering at the Dept. of Informatics, Modeling, Electronics and Systems (DIMES) of the University of Calabria (Unical), Rende (CS), Italy. He has a Ph. D. degree and Laurea (MSc+BSc) degree in Computer Engineering from Unical. He is High-end Foreign Expert of China (term 2015-2018), Adjunct and Guest Professor at the Wuhan University of Technology (China), High-end Expert of HUST (China), CAS PIFI Visiting Scientist at Shenzhen (2019-2021), Distinguished Professor of Huazhong Agricultural University (China) and Associated Senior Research Fellow at the Italian National Research Council - ICAR Institute. He has been also Visiting Researcher and Professor at the International Computer Science Institute (Berkeley, USA, 97-99) and at the Queensland University of Technology (Australia, 2009), respectively. He is in the list of Top Italian Scientists (TIS) by VIA-academy and Guide2Research, with h-index=52 and 10000+ citations according to GS. According to the SciVal tool based on the Scopus database, in the last 5 years (2015-19), he is ranked N. 39 in the Computer Science field in the ranking of Top 500 authors, by Scholarly Output in the World, based on the FWCI index, is N. 1 in the Research Area “Hardware and Architecture” and N. 1 in the topic “Body Sensor Network; Smart Object; Interoperability”. According to WoS, he has currently 12 highly cited papers and has been recently nominated Highly Cited Researcher 2020 by Clarivate. He is the director of the SPEME (Smart, Pervasive and Mobile Systems Engineering) Lab at DIMES, Unical and co-director of three joint-labs on Smart IoT technologies established with Wuhan University of Technology, Shanghai Maritime University, and Huazhong Agricultural University, respectively. He is also the director of the postgraduate master in “INTER-IoT: Integrator of Internet of Things Systems” and the Rector’s delegate to international relations at Unical. His main research interests include Human-Machine Systems, Wearable Computing, Internet of Things computing and technology, agent-based computing, body area networks, wireless sensor networks, pervasive and cloud computing, multimedia networks, and mobile health systems. He participated to many local, national and international research projects and was also the deputy coordinator and scientific & technical project manager of the EU-funded (8M) H2020 INTER-IoT project. He authored 450+ publications in journals (200+ in ISI-impacted journals), conferences and books. He chaired 100+ Int'l conferences/workshops (he is the general chair of the 1st edition of the 2020 IEEE Human-Machine Systems conference), organized 60+ special issues in well-known ISI-impacted Int'l Journals, and participated in the TPC of about 500 conferences. He is the founding editor in chief of the IEEE Book Series on “Human-Machine Systems” and of the Springer Book Series on "Internet of Things: Technology, Communications andComputing”, and currently serves (as associate editor) in the editorial board of IEEE Transactions on Human-Machine Systems, IEEE Transactions on Affective Computing, IEEE IoT Journal, IEEE Sensors Journal, IEEE SMC Magazine, IEEE Access, Information Fusion, Engineering Applications of Artificial Intelligence, Journal of Networks and Computer Applications and others. He is the recipient of the 2014 Andrew P. Sage SMC Best Transactions Paper award. He is Distinguished Lecturer of the IEEE Sensors Council for the period 2021-2023. He is the Chair of the IEEE SMC Italian Chapter, Member-at-large of the IEEE SMCS BoG, Member of the IEEE Press Board of Directors, and founding chair of the IEEE SMC Technical Committee on “Interactive and Wearable Computing and Devices”. He is co-founder and CEO of SenSysCal S.r.l., a spin-off of Unical, developing innovative human-oriented IoT-based systems for e-health and domotics. 

Antonio Liotta is Professor of Data Science and Intelligent Systems at Edinburgh Napier University, where he is coordinating multi-disciplinary programs in Data Science and Artificial Intelligent across the university. He has recently been awarded a prestigious fellowship in China, where he is the founding director of the Joint Intellisensing Lab and holds a Visiting Professorship at Shanghai Ocean University. Previously, he was Professor of Data Science and the founding director of the Data Science Research Centre, University of Derby, UK. He was leading all university-wide research, educational, and infrastructure programs in data science and artificial intelligence. His team is at the forefront of influential research in data science and artificial intelligence, specifically in the context of smart cities, Internet of Things, and smart sensing. Antonio is a member of the U.K. Higher Education Academy, IEEE Senior Member, and serves the Peer Review College of the U.K. Engineering and Physical Sciences Research Council. He is the Editor-in-Chiefof the Springer Internet of Things book series; associate editor of the Journals JNSM, IJNM, JMM, and IF; and editorial board member of 6 more journals. He has 6 patents and over 300 publications to his credit, and is the author of the book Networks for Pervasive Services: six ways to upgrade the Internet. He is renowned for his contributions to miniaturized machine learning, particularly in the context of the Internet of Things. He has led the international team that has recently made a breakthrough in artificial neural networks, using network science to accelerate the training process.

 

Raffaele Gravina received the PhD degree in computer engineering from the University of Calabria, Italy, in 2012. He is the main designer of the SPINE Framework and responsible for the open-source contributions. He spent two years as researcher at the Telecom Italia WSN Lab at Berkeley, California. He is involved in several research projects on WSNs, including H2020 Inter-IoT, AD-PERSONAS, BodyCloud, MAPS and the REWSN Cluster of FP7 CONET. He is co-founder of SenSysCal S.r.l. and Talent Garden Cosenza S.r.l. He is IEEE member since 2016. He is author of more than 70 papers in international journals, conferences, and book chapters. He is currently serving as Assistant Professor in Computer Engineering at the University of Calabria, Italy. His research interests are focused on high-level programming methods for Wireless Body Sensor Networks and on the Internet-of-Things.

 

Alessandro Longheu works as research fellow at the Department of Electrical, Electronics and Informatics Engineering (DIEEI, formerly known as DIIT) at the University of Catania. He received his PhD in Electronics, Informatics and Telecommunications Engineering from the University of Palermo in 2001 and his MS in Informatics Engineering at the University of Catania in 1997. From 1997 to 2020 he was involved in more than 18 research activities and projects (DSS-DROUGHT, OSIRID, SMIT, SMARTHEALTH) concerning information modeling and retrieval, workflow management, e-learning, trust and reputation, healthcare systems, complex networks, NLP and sentiment analysis, spreading models, online social networks. Since 2000 he has been an adjunct professor of several Computer Science courses both at the University of Catania and at the University Kore of Enna. He has participated in many conferences including ETFA, TAKMA, SPEL, IDC, SITIS, Complenet, WSCE, Complex Networks, ISI&CDN 2018, DSIoT 2019. He has authored/co-authored more than 100 scientific papers in refereed Journals and Conferences.

De la contraportada

This book focuses on the combination of IoT and data science, in particular how methods, algorithms, and tools from data science can effectively support IoT. The authors show how data science methodologies, techniques and tools, can translate data into information, enabling the effectiveness and usefulness of new services offered by IoT stakeholders. The authors posit that if IoT is indeed the infrastructure of the future, data structure is the key that can lead to a significant improvement of human life. The book aims to present innovative IoT applications as well as ongoing research that exploit modern data science approaches. Readers are offered issues and challenges in a cross-disciplinary scenario that involves both IoT and data science fields. The book features contributions from academics, researchers, and professionals from both fields.