Mathematical Models Using Artificial Intelligence for Surveillance Systems
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This book gives comprehensive insights into the application of AI, machine learning, and deep learning in developing efficient and optimal surveillance systems for both indoor and outdoor environments, addressing the evolving security challenges in public and private spaces. Mathematical Models Using Artificial Intelligence for Surveillance Systems aims to collect and publish basic principles, algorithms, protocols, developing trends, and security challenges and their solutions for various indoor and outdoor surveillance applications using artificial intelligence (AI). The book addresses how…mehr

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Produktbeschreibung
This book gives comprehensive insights into the application of AI, machine learning, and deep learning in developing efficient and optimal surveillance systems for both indoor and outdoor environments, addressing the evolving security challenges in public and private spaces. Mathematical Models Using Artificial Intelligence for Surveillance Systems aims to collect and publish basic principles, algorithms, protocols, developing trends, and security challenges and their solutions for various indoor and outdoor surveillance applications using artificial intelligence (AI). The book addresses how AI technologies such as machine learning (ML), deep learning (DL), sensors, and other wireless devices could play a vital role in assisting various security agencies. Security and safety are the major concerns for public and private places in every country. Some places need indoor surveillance, some need outdoor surveillance, and, in some places, both are needed. The goal of this book is to provide an efficient and optimal surveillance system using AI, ML, and DL-based image processing. The blend of machine vision technology and AI provides a more efficient surveillance system compared to traditional systems. Leading scholars and industry practitioners are expected to make significant contributions to the chapters. Their deep conversations and knowledge, which are based on references and research, will result in a wonderful book and a valuable source of information.
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Autorenporträt
Padmesh Tripathi, PhD, completed his Ph.D. from Sharda University, Greater Noida, UP, India. Currently, Dr Tripathi is working as Professor of Mathematics in Department of AIDS at Delhi Technical Campus, Greater Noida, UP, India. He has more than 23 years of teaching experience, published 22 papers/book chapters in reputed journals/publishers and 4 Indian innovation patents. His research areas include Data Science, Machine Learning, Inverse Problems, Optimization, Signal/Image Processing, etc. Dr Tripathi has been listed in lifetime achievement by Marquis Who's Who and received the best academician of 2021 award from SEMS Foundation, Noida, India. Dr Tripathi has been associated with several reputed publishers like IGI Global, Wiley-Scrivener, Taylor & Francis, Elsevier, Springer, Inderscience, etc. in various roles like author, reviewer, editor, guest editor, etc. Dr Tripathi received grants from prestigious institutes like Cambridge University, UK; University of California at Los Angeles, USA; INRIA, Sophia Antipolis, France; University of Eastern Finland, Kuopio, Finland; RICAM, Linz, Austria, etc and visited these places. Mritunjay Rai, PhD, has completed his Ph.D. in Thermal imaging applications in the department of Electrical Engineering from IIT-ISM Dhanbad, Master of Engineering (with distinction) in Instrumentation and Control from Birla Institute of Technology-Mesra, Ranchi, and B.Tech in ECE from Shri Ramswaroop Memorial College of Engineering and Management, Lucknow. Currently, Dr. Rai is working as Assistant Professor in Shri Ramswaroop Memorial University, Barabanki, U.P., India. Dr. Rai has more than 12 years of working experience in research as well as academics. In addition, he has guided several UG and PG projects. He has published many research articles in reputed journals published by Springer, Elsevier, IEEE, Inderscience, and MECS. He has contributed many chapters to books published by Intech Open Access, CRC, IGI Global, and Elsevier. He is an editor of books (edited) published by reputed publishers Wiley, AAP, NOVA & IGI, He is an active reviewer and has reviewed many research papers in journals and at international and national conferences. His areas of interest lie in image processing, speech processing, artificial intelligence, machine learning, deep learning, Intelligent Traffic Monitoring System, the Internet of Things (IoT), and robotics and automation. Nitendra Kumar, PhD, an accomplished scholar with a PhD in Mathematics from Sharda University and a master's degree in mathematics and Statistics from Dr. Ram Manohar Lohia Avadh University, boasts over a decade of expertise as an Assistant Professor at Amity Business School, Amity University, Noida. His diverse research interests encompass Wavelets and its Variants, Data Mining, Inverse Problems, Epidemic Modelling, Fractional Derivatives Business Analytics, and Statistical Methods, reflecting a profound commitment to advancing knowledge across multiple domains. Dr. Kumar's prolific contributions to academia are evidenced by his extensive publication record, comprising over 30 research papers in esteemed journals, 16 book chapters, and 12 authored books on engineering mathematics, computation, and Business Analytics and related topics. Notably, his scholarly impact extends beyond traditional research avenues, as evidenced by his involvement in patenting two innovative solutions. Beyond his individual achievements, Dr. Kumar actively engages with the academic community, serving as editor for two edited books and as Guest Editor for reputable journals like the Journal of Information and Optimization Sciences, Journal of Statistical and Management Sciences, and Environment and Social Psychology. His editorial roles underscore his dedication to fostering intellectual discourse and shaping the trajectory of scholarly inquiry. Dr Nitendra Kumar epitomizes academic excellence, blending profound expertise with a steadfast commitment to advancing mathematical knowledge and its interdisciplinary applications. Santosh Kumar, PhD, is Assistant Professor in the Department of Mathematics, Sharda School of Basic Sciences and Research, Sharda University, Greater Noida, India. He obtained his Ph.D. degree from Aligarh Muslim University Aligarh, in 2016. He is actively involved in the research areas, namely nonlinear partial differential equations, diffusion models, wavelet transform, mathematical modeling, image processing, etc. He has taught undergraduate subjects such as linear algebra, differential equations, complex analysis, advanced calculus, and probability and statistics. He has taught real analysis, topology, functional analysis, partial differential equations, and many more at the post-graduation level. Besides attending, presenting scientific papers, delivering invited talks, and chairing sessions at national/international conferences and seminars, he has organized several workshops and conferences as an organizing secretary. He has published many research papers in reputed national and international journals and book chapters published in an edited book published by international publishers. He is also reviewer of many reputed journals.