Artificial Intelligence, Machine Learning and Intelligent Systems
Description
This proceedings volume is a collection of 35 chapters presented at the Second International Conference on Artificial Intelligence, Machine Learning and Intelligent Systems (ICAMS-2025), held at the National Institute of Technology Hamirpur, Himachal Pradesh, India, from 7-8 February 2025. It gathers chapters on artificial intelligence, machine learning and intelligence systems. The book discusses how artificial intelligence, machine learning and intelligent systems are revolutionizing engineering and commercial practices through applications of mathematics. Covering diverse topics such as facial recognition security, cryptocurrency and blockchain technologies, automated trading, sustainable inventory management, personalized recommendation systems and IoT-driven smart solutions, the book highlights both theoretical advancements and practical implementations of mathematics across a wide range of disciplines.
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Persons
Kusum Deep is Emeritus Professor in the Department of Mathematics and the Mehta Family School of Data Science and Artificial Intelligence, IIT Roorkee, Uttarakhand, India. She is also visiting professor at Liverpool Hope University, U.K. She received her M.Phil. (Hons.) and Ph.D. degrees in mathematics from the University of Roorkee, in 1984 and 1988, respectively. She carried out postdoctoral research from Loughborough University, U.K., under a bursary from the Commission of European Communities Brussels. Author of two books, she supervised 23 Ph.D. students and published more than 135 research articles. Her research interests include numerical optimization, nature-inspired optimization techniques, soft computing, and artificial intelligence. She received the Gold Medal from the University of Roorkee for the M.Phil. degree. Winning numerous awards during her career, she has been ranked amongst the top 2% of scientists in the world consecutively for four years.
Millie Pant is Professor and the Head of the Department of Applied Mathematics and Scientific Computing, IIT Roorkee, where she is also a joint faculty member of the Mehta Family School of Data Science and Artificial Intelligence. She received her M.Sc. degree in mathematics from Chaudhary Charan Singh University, Meerut, India, and the Ph.D. degree from the Department of Mathematics, IIT Roorkee. Author of more than 350 papers in various journals and conferences of national and international repute, her research interests include numerical optimization, operations research, evolutionary algorithms, supply chain management, swarm intelligence techniques, AI-assisted decision-making, data analysis, and image processing. She is a guest reviewer of the IEEE Transactions on Evolutionary Computation, Applied Mathematics and Computation, and Applied Soft Computing. She is also associate editor of the International Journal of Swarm Intelligence and a guest editor of the International Journal of Memetic Computing (Springer).
Mohammad Khalid Pandit is Assistant Professor in the Department of Computer Science and Engineering, National Institute of Technology (NIT) Hamirpur, Himachal Pradesh, India. He received her B.E. and M.E. degrees in computer science and engineering from Anna University, Chennai, India. He received his Ph.D. degree from the Department of Computer Science and Engineering, National Institute of Technology Srinagar, Jammu and Kashmir, India. His research interests include artificial intelligence, machine learning and edge computing. He was a student member of CSI and a member of IACSIT and IAENG. He has received various research grants and published papers in high-quality journals and conferences like IEEE Transactions and ACM Transactions.
Naveen Chauhan is Associate Professor at NIT Hamirpur. His research interests include wireless communication and sensor networks. He has published various research articles in reputed journals and conferences. He has also completed various government sponsored projects.
Ajay Kumar Mallick is Assistant Professor in the Department of Computer Science and Engineering (CSE) at the NIT Hamirpur. He earned his B.E. in computer science and engineering from the University Institute of Technology, University of Burdwan, West Bengal, India. He completed his M.Tech. and Ph.D. degrees in CSE from the IIT (ISM), Dhanbad, Jharkhand, India. His research interests encompass computer vision, machine learning, content-based image and video retrieval, digital image security and analysis. He has published his papers on video retrieval frameworks, privacy-preserving image retrieval and applications of convolutional neural networks in agriculture. He served as the technical advisory committee and other diverse role in several international conferences. His professional affiliations include membership in IEEE and life membership in the Indian Unit for Pattern Recognition and Artificial Intelligence (IUPRAI) and others.
Content
Chapter 1. Real-time Unconscious Human Behavior Detection Incorporating Enhanced CSPDarknet53 and YOLOv9.- Chapter 2. Exploring Machine Learning and IoT Technologies for Disease Detection in Cows: A Systematic Review.- Chapter 3. Hybrid Butter Flower Algorithm.- Chapter 4. HEAVY-SARS: Harnessing Explainable AI and Generative Models for Visual Synthetic Data Generation of SARS-CoV-2.- Chapter 5. Infected Hyena Optimizer: A Novel Bio-inspired Metaheuristic Algorithm.- Chapter 6. Socio-nomadic Learning Optimization.- Chapter 7. Binary Tree-based Key Management Scheme for a Ground Station Managing IoT Devices in a Satellite Multicast Communication.- Chapter 8. AI-driven Deterrence System Utilizing YOLO Algorithm for Real-time Wildlife Detection and Mitigation.- Chapter 9. Adaptive Social Robot Navigation Using Vision-Language Models.- Chapter 10. Egocentric Perception for Open Vocabulary Object Rearrangement.- Chapter 11. Sentiment Analysis of Sarcastic Hindi Sentences: Analysis of SVM and XGBoost Models.- Chapter 12. Enhanced Intrusion Detection for Cloud-integrated IoT Networks using Autoencoder-driven Unsupervised Deep Learning.- Chapter 13. Segmentation-based Word Spotting in Handwritten Ayurveda Manuscripts using Siamese Convolutional Network.- Chapter 14. AI-enhanced Pediatric Pneumonia Classification.- Chapter 15. Anomaly Detection in Cryptocurrency Prices.- Chapter 16. GEMNet: Gabor Enhanced Multiscale CNN for Breast Tumor Detection using Biorthogonal Wavelet Transform Features.- Chapter 17. Enhanced Ensemble Learning and Feature Selection for Plant Disease Identification.- Chapter 18. A Novel Review of Obstructive Sleep Apnea Detection using Photoplethysmography.- Chapter 19. Early Detection of Ovarian Cancer from Histopathological Images using Deep Learning Models and Explainable AI.- Chapter 20. Navigating Robot Paths: A Comparative Study of Ant Colony Optimization and Firefly Algorithm for Optimization.- Chapter 21. Adaptive Brake Control for Sustaining Dynamic Stability of Autonomous Vehicles using Markov Decision Process.- Chapter 22. Enhanced IoT Intrusion Detection: Leveraging Dense Autoencoders with Mahalanobis Distance and Gamma-based Thresholding.- Chapter 23. Lidar Point Cloud Quality Assessment in Autonomous Vehicles using Deep Learning Techniques.- Chapter 24. Effective Computer Vision Approach for Surveillance Systems to Detect Stone Crushers.- Chapter 25. Enhancing PCOS Diagnosis with Hybrid ML: Integrating Ultrasound and Clinical Data.- Chapter 26. DNA Splice Junction Prediction using Hybrid Approach of LSTM-GRU Model.- Chapter 27. Machine Learning Techniques-based Predictive Modeling for Wind Speed Forecasting.- Chapter 28. Unsupervised Fabric Defect Detection via Autoencoder Reconstruction and One-class SVM Analysis.- Chapter 29. Predicting Mental Health Issues using Social Media Data: A Machine Learning Approach.- Chapter 30. A Threat Monitoring and Control Unit for Secure Embedded Systems.- Chapter 31. Quantum Steganography-based Least Significant Bit Algorithm for Confidential Data Communication.- Chapter 32. A Survey on Securing the Future of Electric Vehicles and its Charging Stations.- Chapter 33. Automatic Speech Recognition for Telugu Language using Pre-trained Wave2Vec 2.0 Model.- Chapter 34. Secure Biological Data Transfer Using Network Coding.- Chapter 35. MedSum: Medical Video Summarization using Reinforcement Learning.