Mathematical Models Using Artificial Intelligence for Surveillance Systems

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.

Table of Contents:
Preface xv 1 Elevating Surveillance Integrity-Mathematical Insights into Background Subtraction in Image Processing 1 S. Priyadharsini 2 Machine Learning and Artificial Intelligence in the Detection of Moving Objects Using Image Processing 19 K. Janagi, Devarajan Balaji, P. Renuka and S. Bhuvaneswari 3 Machine Learning and Imaging-Based Vehicle Classification for Traffic Monitoring Systems 51 Parthiban K. and Eshan Ratnesh Srivastava 4 AI-Based Surveillance Systems for Effective Attendance Management: Challenges and Opportunities 69 Pallavi Sharda Garg, Samarth Sharma, Archana Singh and Nitendra Kumar 5 Enhancing Surveillance Systems through Mathematical Models and Artificial Intelligence: An Image Processing Approach 91 Tarun Kumar Vashishth, Vikas Sharma, Bhupendra Kumar, Kewal Krishan Sharma, Sachin Chaudhary and Rajneesh Panwar 6 A Study on Object Detection Using Artificial Intelligence and Image Processing—Based Methods 121 Vidushi Nain, Hari Shankar Shyam, Nitendra Kumar, Padmesh Tripathi and Mritunjay Rai 7 Application of Fuzzy Approximation Method in Pattern Recognition Using Deep Learning Neural Networks and Artificial Intelligence for Surveillance 149 M. Geethalakshmi, Sriram V. and Vakkalagadda Drishti Rao 8 A Deep Learning System for Deep Surveillance 169 Aman Anand, Rajendra Kumar, Nikita Verma, Akash Bhasney and Namita Sharma 9 Study of Traditional, Artificial Intelligence and Machine Learning Based Approaches for Moving Object Detection 187 Apoorv Joshi, Amrita, Rohan Sahai Mathur, Nitendra Kumar and Padmesh Tripathi 10 Arduino-Based Robotic Arm for Farm Security in Rural Areas 215 Canute Sherwin, Shahid D. P., N. R. Hritish, Sujan Kumar S. N., Nikhil R. and K. Raju 11 Graph Neural Network and Imaging Based Vehicle Classification for Traffic Monitoring System 241 Shivam Sinha, Nilesh kumar Singh and Lidia Ghosh 12 A Novel Zone Segmentation (ZS) Method for Dynamic Obstacle Detection and Flawless Trajectory Navigation of Mobile Robot 271 Rapti Chaudhuri, Jashaswimalya Acharjee and Suman Deb 13 Artificial Intelligence in Indoor or Outdoor Surveillance Systems: A Systematic View, Principles, Challenges and Applications 293 Varun Gupta, Tushar Bansal, Vinay Kumar Yadav and Dhrubajyoti Bhowmik References 330 Index 335

About the Author :
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.