This book gathers outstanding research papers presented in the 3rd International Conference on Artificial Intelligence: Advances and Application (ICAIAA 2022), held in Poornima College of Engineering, Jaipur, India, during April 2324, 2022. This book covers research works carried out by various students such as bachelor, master and doctoral scholars, faculty and industry persons in the area of artificial intelligence, machine learning, deep learning applications in health care, agriculture, and business, security. It also covers research in core concepts of computer networks, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, SDN, NFV, etc.

Presents research works in the field of artificial intelligence Discusses results of ICAIAA 2022 held in Jaipur, India Serves as a reference for researchers and practitioners in academia and industry

Autorentext

Garima Mathur is currently working as the head of Department, Poornima College of Engineering, Jaipur, since July 1, 2016. Previously, she was working as the head of Department in Electronics & Communication Engineering at Jaipur Engineering College, Jaipur, Rajasthan, India, since October 2000 to December 2015. She has total 21 years of experience in teaching and research. She is working on various research projects sponsored by various agencies. She did her doctoral degree in Performance Evaluation of Modified Sphere Decoding Scheme for MIMO Systems. Dr. Mathur published and presented international, national journals, conferences, symposium, and seminar more than 30 research papers. She has guided more than 15 M.Tech. Dissertation theses. Her area of interest is wireless channel, channel modeling, and ad hoc networks. Dr. Mathur is a life member of the Institution of Electronics and Telecommunication Engineers (IETE), The Indian Society for Technical Education (ISTE), India, and many other professional bodies. Mahesh Bundele is currently working as the principal and the director of Poornima College of Engineering, Jaipur, since September 1, 2018. He has total of 34 years of experience in teaching and research. He has developed many unique research methodology concepts and implemented. He is the mentor and controller of quality research and publications at the Poornima. He is also responsible for inculcation of innovative and critical analysis concepts across the university and across the Poornima Foundation involving three other campuses. He did his doctoral degree in Wearable Computing and guiding research in pervasive & ubiquitous computing, computer networks, and software-defined networking. His areas of interests are also wireless sensor networks, algorithmic research, mathematical modeling, and smart grids. He has more than 60 publications in reputed journals and conferences. He has been the reviewer offew IEEE Transactions. He is actively involved in IEEE activities in Rajasthan Subsection and Delhi Section and holding the responsibility on Standing Committee of IEEE Delhi Section for Technical & Professional activities for controlling quality of conferences and publications in IEEE. He is also a member of IEEE Delhi Section Execom. He has organized 5 editions of IEEE ICRAIE in India and Malaysia with conference position as the general co-chair. He has organized PerCAA 2019 with Elsevier Computer Science Procedia as the program chair. He is the general chair and the advisor in many other international conferences including Springer ICAIAA 2019, 2021, IOP publication ICGSSET 2021 and an IEEE Delhi Section Oversight committee member of all IEEE International Conferences being organized in IEEE Delhi Section jurisdiction since last 3 years. He is the editorial manager for Elsevier's Computers and Electronics in Agriculture, Environmental Science and Pollution Research, Renewable and Sustainable Energy, Applied Mathematical Modeling, etc. He has received Excellence in Leadership award by ITSR foundation in 2020. Ashish Kumar Tripathi (Member, IEEE) received his M.Tech. and Ph.D. degrees in Computer Science and Engineering from the Department of Computer Science and Engineering, Delhi Technological University, Delhi, India, in 2013 and 2019, respectively. He is currently working as an assistant professor with the Department of Computer Science & Engineering, Malviya National Institute of Technology (MNIT), Jaipur, India. His research interests include big data analytics, social media analytics, soft computing, image analysis, and natural language processing. Dr. Tripathi has published several papers in international journals and conferences including IEEE transactions. He is an active reviewer for several journals of repute. Marcin Paprzycki is an associate professor at the Systems Research Institute,Polish Academy of Sciences. He has an MS from Adam Mickiewicz University in Poznan, Poland, a Ph.D. from Southern Methodist University in Dallas, Texas, and a D.Sc. Degree from the Bulgarian Academy of Sciences. He is a senior member of IEEE, a senior member of ACM, a senior fulbright lecturer, and an IEEE CS distinguished visitor. He has contributed to more than 450 publications and was invited to the program committees of over 500 international conferences. He is on the editorial boards of 12 journals and a book series.

Inhalt
Prediction of Polycystic Ovary Syndrome (PCOS) using Optimized Machine Learning Classifiers.- Literature Review: A Comparative Study of Software Defect Prediction Techniques.- Crop Recommendation using Machine Learning Algorithms and Soil Attributes Data.- Application of Machine Learning Models to Improve the Accuracy of Earnings Management Prediction.- Ensemble of Parametrized Quantum LSTM Neural Networks for Multimodal Stress Monitoring.- Evolutionary Algorithms for Marine Dynamical Systems: Towards Sustainable Renewable Energy Harvesting from Oshore Environment.- Comparison of Different Swarm Based Nature Inspired Algorithm for solution of Optimization Problem.- Assessment of Firm's Performance by Employing Text Mining Techniques.- Decisions Prediction Techniques using Language Processing and Learning Algorithms.- Machine Learning-based Tool to Classify Online Toxic Comments.