Communication based on the internet of things (IoT) generates huge amounts of data from sensors over time, which opens a wide range of applications and areas for researchers. The application of analytics, machine learning, and deep learning techniques over such a large volume of data is a very challenging task. Therefore, it is essential to find patterns, retrieve novel insights, and predict future behavior using this large amount of sensory data. Artificial intelligence (AI) has an important role in facilitating analytics and learning in the IoT devices.

Applying AI-Based IoT Systems to Simulation-Based Information Retrieval provides relevant frameworks and the latest empirical research findings in the area. It is ideal for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society and trust at the levels of the global economy, networks and organizations, teams and work groups, information systems, and individuals as actors in the networked environments. Covering topics such as blockchain visualization, computer-aided drug discovery, and health monitoring, this premier reference source is an excellent resource for business leaders and executives, IT managers, security professionals, data scientists, students and faculty of higher education, librarians, hospital administrators, researchers, and academicians.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

AI Algorithms
Automatic Boom Barrier
Blockchain Visualization
Cancer Detection
Computer-Aided Drug Discovery
Data Analytics
Deep Learning Techniques
Health Monitoring
Machine Learning-Based Disease Diagnosis
Surveillance Security

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Editor/Author Biographies

Madhulika Bhatia is an Associate Professor at Amity University.

Surbhi Bhatia completed her PhD in Computer Science and Engineering in 2018 from Banasthali Vidyapith University, Vanasthali, India. She is currently Assistant Professor in the Department of Information Systems at King Faisal University, Hofuf, Saudi Arabia. She has authored/edited 3 books, holds 7 patents, and has more than 25 research publications. Her research interests including data mining, machine learning, database management systems, and computer languages: C, C++, Python.

Poonam Tanwar has 18 years of Teaching Experience working as associate Prof. in Manav Rachna International Institute of Research & Studies, Faridabad. She has published more than 50 research papers in various International Journals and Conferences. She has one copyright and filled 6 patents. She has edited 3 books and 2 in process. The book titled “Big Data Analytics and Intelligence: A Perspective for Health Care” in 2019 by Emerald, Natural Language processing and AI application for Industry 4.O by IGI Globe & Computational Intelligence & Predictive Analysis for Medical Science A Pragmatic Approach by Degurter. She was Guest Editor for Special issue of “Advancement in Machine Learning (ML) and Knowledge Mining (KM)” for International Journal of Recent Patents in Engineering (UAE) & one more is in process. She has been awarded woman researcher award by VDGOODS Academy Chennai. She has organized various Science & Technology awareness program for rural development. She received Certificate of RECOGNITION (Silver Category) for OUTSTANDING Contribution to Campus Connect Program for all academic years since 2011 to 2017 by INFOSYS, Chandigarh. Beside this she is Technical program committee member for various International Conferences Like ICIC 2018, ICFNN, Rome(Italy ), European Conference on Natural Language Processing and Information Retrieval, Berlin(Europe) Etc.

Kuljeet Kaur received the B.Tech degree in computer science and engineering from Punjab Technical University, Jalandhar, India, in 2011 and the M.E. (Information Security) and Ph.D. (Computer Science and Engineering) degrees from Thapar Institute of Engineering and Technology (Deemed to be University), Patiala, India, in 2015 and 2018, respectively. She worked as a NSERC Postdoctoral Research Fellow at the École de technologie supérieure (ÉTS), Université du Québec, Montréal, Canada from 2018 till 2020. She is currently working as an Assistant Professor in the Electrical Engineering Department at ÉTS, Montreal and a Visiting Researcher in the School of Computer Science and Engineering (SCSE) at the Nanyang Technological University (NTU), Singapore. Her main research interests include Cloud Computing, Energy Efficiency, Smart Grid, Frequency Support, and Vehicle-to-Grid. Dr. Kaur has secured a number of research articles in top- tier journals such as IEEE Wireless Communications, IEEE TII, IEEE TCC, IEEE TVT, IEEE TMM, IEEE TSG, IEEE Systems Journal, IEEE IoT Journal, IEEE Communications Magazine, IEEE Wireless Communications, IEEE Network, IEEE PS, FGCS, JPDC, Springer PPNA, etc., and various International conferences including IEEE Globecom, IEEE ICC, IEEE PES GM, IEEE WCNC, IEEE Infocom Workshops, ACM MobiCom Workshops, ACM MobiHoc workshops, etc. During her PhD, she received two prestigious fellowships, i.e., INSPIRE fellowship from Department of Science & Technology, India (in 2015) and research scholarship from Tata Consultancy Services (TCS) (from 2016–2018). Dr. Kaur also received the IEEE ICC best paper award in 2018 at Kansas City, USA and 2019 Best Research Paper Award from Thapar Institute of Engineering and Technology, India. She serves as an Associate Editor of Wiley’s Security and Privacy (SPY) and Journal of Information Processing Systems (JIPS), Springer’s Human-centric Computing and Information Sciences (HCIS), and guest editor for special issues in IEEE Transaction on Industrial Informatics and IEEE Open Journal of the Computer Society. She is a website co-chair of N2Women community. She also serves as the Vice-Chair of the IEEE Montreal Young Professionals Affinity Group. She has also been a TPC Co-chair for IEEE Infocom 2020 and ACM MobiCom 2020 workshops on DroneCom. She is a member of IEEE, IEEE Communications Society, IEEE Computer, IEEE Women in Engineering, IEEE Software Defined Networks Community, IEEE Smart Grid Community, ACM, and IAENG.

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