Advances in IoT and Security with Computational Intelligence
Description
The book is a collection of peer-reviewed best-selected research papers presented at the International Conference on Advances in IoT and Security with AI (ICAISA 2025), organized as a joint collaborative event between Deen Dayal Upadhyaya College, University of Delhi, India, CQ University (CQU), Sydney, Australia, University of KwaZulu-Natal, Durban, South Africa, IIIT Bhopal and NIT Arunachal Pradesh, India, during April 4-5, 2025. The book includes various applications and technologies in this specialized sector of Industry 4.0. The book is divided into two volumes. It focuses on recent advances in Internet of Things and security with its applications using artificial intelligence.
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Persons
Prof. Anurag Mishra is an accomplished academician and researcher with over 30 years of teaching and research experience in Computer Science, Electronics, and related fields. With a robust background in Physics (B.Sc. and M.Sc.) and advanced degrees in Computer Technology and Applications (M.E.) and Electronics (Ph.D.) from the University of Delhi, he has contributed significantly to both academia and industry. Prof. Mishra has published over 70 refereed papers in high-impact journals, international conferences, and book chapters, focusing on Information Security, Digital Rights Management, and image classification for forensic applications.
Dr. Deepak Gupta is an Assistant Professor in the Department of Computer Science & Engineering of Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India. Previously he has worked in the Department of Computer Science & Engineering of National Institute of Technology Arunachal Pradesh. He received a Ph.D. degree in Computer Science & Engineering from the Jawaharlal Nehru University, New Delhi, India. His research interests include support vector machines, ELM, RVFL, KRR, biomedical applications and other machine-learning techniques. He has published over 80 referred journal and conference papers of international repute.
Prof. Meena Jha, professes in computer science and Head of the Technology and Pedagogy Cluster at Central Queensland University, Australia is a passionate advocate for gender equality. She has been a visiting professor at NetaJi Subhash University of Technology, Delhi, India. She holds a Bachelor's and Master's degree in Electronics and Communication Engineering and Computer Science from India, as well as a PhD in Computer Science and Engineering from the University of New South Wales (UNSW), Australia.
Prof. Upasana Singh is the Academic Leader and Associate Professor in the Discipline of Information Systems and Technology at the University of KwaZulu-Natal, Westville Campus, Durban, South Africa. Additionally, she holds the esteemed position of Adjunct Senior Lecturer at the Victorian Institute of Technology, Australia. She earned her Ph.D. in Information Systems from the University of South Africa, complemented by a Master's and a B.Com Hons degree in Information Systems and Technology from the University of KwaZulu-Natal and the University of Natal, respectively. Prof Singh's interdisciplinary research has yielded an impressive publication record, including 4 edited books, 25 journal papers, 13 book chapters, and 26 peer-reviewed conference papers.
Dr. Rajat Subhra Goswami received his B.Tech in Information Technology in 2005 from West Bengal University of Technology, West Bengal. He received his M.E. in Multimedia Development from Jadavpur University, West Bengal in 2009 and then joined in Bengal Institute of Technology Shantiniketan, Bolpur, West Bengal as an Assistant Professor in the CSE department. He became Assistant Professor of the CSE department at the National Institute of Technology, Arunachal Pradesh, Govt. of India in 2011. He received PhD in Computer Science & Engineering from the National Institute of Technology Arunachal Pradesh in 2015. Currently, he is working as an Associate Professor in the Department of Computer Science and Engineering at the National Institute of Technology, Arunachal Pradesh, Govt. of India.
Content
A Hybrid Approach for plant leaf detection using AlexNet-Extreme Learning Machine (AlexNet-ELM) classifier.- Benchmarking Conventional Agricultural Practices: A Parameter-Driven Comparative Analysis.- Banana Leaf Diseases Detection Using YOLOv11.- Pineapple Harvesting: Efficient Detection and Classification using YOLOv9 with Machine Learning.- Evaluation of various CAM methods for Medical Image Analysis.- Integrating Blockchain with Federated Learning for Detecting Alzheimer Disease.- A resilient Gesture Recognition system for Agricultural Practices.- Bridging Thought and Image: Conditional GANs for Image Synthesis from EEG Signals.- Heart Disease Prognosis using Machine Learning Approaches: A Comprehensive Analysis.- Deep Learning Architectures for Early Detection of Skin Cancer.- Research Trends and Patterns for Leaf Disease Severity Assessment Using Deep Learning Techniques.- Integrating Deep Convolutional Neural Networks and IoT Technology for Advancements in Healthcare.- Emotion Extraction Applied in Mental Health Monitoring.- Advanced Deep Learning Techniques for Integrating Multi-Omics Data in Cancer Research and Precision Medicine.- Advanced Deep Learning Techniques for Enhancing Speech and Language Therapy in Neurological Disorder Rehabilitation.- AI-Powered Deep Learning Framework for Early Detection and Classification of Autism Spectrum Disorder.- Leveraging Convolutional Neural Networks for Precision Weed Detection and Management in Smart Farming.- Advancements in Sentiment Analysis: Applications, Challenges, and Hybrid Machine Learning Approaches.- Prediction of Spectra of a Metal Nanoparticle using Deep Learning for Biomedical Applications.- Optimizing Skin Cancer Detection with EfficientNetB7: A Deep Learning Approach.- Predicting Health Insurance Claims Using Machine Learning-Based Framework.- Benign and Malignant Skin Lesion Classification from Melanoma Skin Cancer Images Using Machine Learning Models.- A Deep Learning Framework for Stress and Depression Detection.- Investigating the Effect of Musical Stimulus through Spectral P and T Wave Features in ECG Signal.- Advanced Tuberculosis Detection Algorithm using CNN.- Emotion Detection from Gujarati Text Stories using Lexicon Based Approach.- Exploring Deep Learning Methods for Accurate ECG Arrhythmia Classification.- Transforming Rural Healthcare: A Study on Skin Disease Detection in India.- Improved Splice Site Prediction in Genomic DNA using Machine Learning Approaches.- Investigating the Use Of Ingestible Sensors And Smart Pills To Monitor Patient Compliance And Gather Health Data.- Sentiment Analysis of Reviews on Amazon Alexa.- Automated Diagnosis of Schizophrenia through EEG Signals using a hybrid model of CNN with LSTM and Attention Networks.- A-VAE: Attention-based Variational Autoencoders for De Novo Drug Design.- EEG-Based Schizophrenia Detection Using a Hybrid 1D CNN-SVM Model.- Hybridization of CNN and ViT Features for Enhanced Brain Tumor Classification.- Deep Learning for Blood Cell Classification: A Comparison of Fine-Tuned Architectures on BloodMNIST.- Privacy Preserved and Practical Implementation for Distributed Machine Learning in Radiology.- Malaria pathogen detection in microscopy images- transfer learning challenges.- Real-Time Emotion Detection from Video for Autism Support Using CNN with Gujarati Audio Output.- Technological Advancements and Trends in Cyber-Physical Systems for Healthcare: A Systematic Review.- Confidence-Weighted Ensemble Learning: A Case Study in Parkinson's Detection Using Keystroke Dynamics.