Freshly Printed - allow 7 days lead
Couldn't load pickup availability
Mathematical Models Using Artificial Intelligence for Surveillance Systems
Padmesh Tripathi (Edited by), Tripathi (Author), Mritunjay Rai (Edited by), Nitendra Kumar (Edited by), Santosh Kumar (Edited by)
9781394200580, Wiley
Hardback, published 2 September 2024
368 pages
22.9 x 15.2 x 2.3 cm, 2.082 kg
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.
Preface xv 1 Elevating Surveillance Integrity-Mathematical Insights into Background Subtraction in Image Processing 1 2 Machine Learning and Artificial Intelligence in the Detection of Moving Objects Using Image Processing 19 3 Machine Learning and Imaging-Based Vehicle Classification for Traffic Monitoring Systems 51 4 AI-Based Surveillance Systems for Effective Attendance Management: Challenges and Opportunities 69 5 Enhancing Surveillance Systems through Mathematical Models and Artificial Intelligence: An Image Processing Approach 91 6 A Study on Object Detection Using Artificial Intelligence and Image Processing—Based Methods 121 7 Application of Fuzzy Approximation Method in Pattern Recognition Using Deep Learning Neural Networks and Artificial Intelligence for Surveillance 149 8 A Deep Learning System for Deep Surveillance 169 9 Study of Traditional, Artificial Intelligence and Machine Learning Based Approaches for Moving Object Detection 187 10 Arduino-Based Robotic Arm for Farm Security in Rural Areas 215 11 Graph Neural Network and Imaging Based Vehicle Classification for Traffic Monitoring System 241 12 A Novel Zone Segmentation (ZS) Method for Dynamic Obstacle Detection and Flawless Trajectory Navigation of Mobile Robot 271 13 Artificial Intelligence in Indoor or Outdoor Surveillance Systems: A Systematic View, Principles, Challenges and Applications 293 References 330 Index 335
S. Priyadharsini
K. Janagi, Devarajan Balaji, P. Renuka and S. Bhuvaneswari
Parthiban K. and Eshan Ratnesh Srivastava
Pallavi Sharda Garg, Samarth Sharma, Archana Singh and Nitendra Kumar
Tarun Kumar Vashishth, Vikas Sharma, Bhupendra Kumar, Kewal Krishan Sharma, Sachin Chaudhary and Rajneesh Panwar
Vidushi Nain, Hari Shankar Shyam, Nitendra Kumar, Padmesh Tripathi and Mritunjay Rai
M. Geethalakshmi, Sriram V. and Vakkalagadda Drishti Rao
Aman Anand, Rajendra Kumar, Nikita Verma, Akash Bhasney and Namita Sharma
Apoorv Joshi, Amrita, Rohan Sahai Mathur, Nitendra Kumar and Padmesh Tripathi
Canute Sherwin, Shahid D. P., N. R. Hritish, Sujan Kumar S. N., Nikhil R. and K. Raju
Shivam Sinha, Nilesh kumar Singh and Lidia Ghosh
Rapti Chaudhuri, Jashaswimalya Acharjee and Suman Deb
Varun Gupta, Tushar Bansal, Vinay Kumar Yadav and Dhrubajyoti Bhowmik
Subject Areas: Computer science [UY]
