Artificial Intelligence of Things for Weather Forecasting and Climatic Behavioral Analysis

Weather forecasting and climate behavioral analysis have traditionally been done using complicated physics models and accompanying atmospheric variables. However, the traditional approaches lack common tools, which can lead to incomplete information about the weather and climate conditions, in turn affecting the prediction accuracy rate. To address these problems, the advanced technological aspects through the spectrum of artificial intelligence of things (AIoT) models serve as a budding solution. Further study on artificial intelligence of things and how it can be utilized to improve weather forecasting and climatic behavioral analysis is crucial to appropriately employ the technology. Artificial Intelligence of Things for Weather Forecasting and Climatic Behavioral Analysis discusses practical applications of artificial intelligence of things for interpretation of weather patterns and how weather information can be used to make critical decisions about harvesting, aviation, etc. This book also considers artificial intelligence of things issues such as managing natural disasters that impact the lives of millions. Covering topics such as deep learning, remote sensing, and meteorological applications, this reference work is ideal for data scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Arti Jain is working as Assistant Professor (Sr. Grade), CSE at Jaypee Institute of Information Technology, Noida, India. She has academic experience of over eighteen years. She completed her Ph.D. (CSE) in 2019 at JIIT Noida. She is member of IEEE, INSTICC, IAENG, IASSE, IFERP, and Life Member of TERA. She has more than twenty research papers in peer-reviewed international journals, book chapters, and international conferences. She has supervised one M. Tech Thesis and around 100 B. Tech projects. Currently, she is supervising one Ph.D. candidate in the area of social network analysis. She is an editorial board member of the American Journal of Neural Networks and Applications. She has served as International advisory committee member of ICASETM-2020, Dubai and ICRTMDR-2020, Maldives. She is an outreach committee member of ICRAET 2021, India. She is also a reviewer of International Journals-Taylor & Francis, IGI Global, Wiley, TISA and Inderscience. She is a TPC member and reviewer of several International Conferences within India and abroad. She is a session organizer in ICICC 2020-2021, Springer. Her research interests include NLP, machine learning, deep learning, social media analysis, big data and data mining.

John Wang is a professor in the Department of Information & Operations Management at Montclair State University, USA. Having received a scholarship award, he came to the USA and completed his PhD in operations research from Temple University. Due to his extraordinary contributions beyond a tenured full professor, Dr. Wang has been honored with a special range adjustment in 2006. He has published over 100 refereed papers and seven books. He has also developed several computer software programs based on his research findings.He is the Editor-in-Chief of International Journal of Applied Management Science, International Journal of Operations Research and Information Systems, and International Journal of Information Systems and Supply Chain Management . He is the Editor of Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (six-volume) and the Editor of the Encyclopedia of Data Warehousing and Mining, 1st (two-volume) and 2nd (four-volume). His long-term research goal is on the synergy of operations research, data mining and cybernetics.