Advances in Data-driven Computing and Intelligent Systems

Selected Papers from ADCIS 2025, Volume 6
Erscheinungsjahr 2026
ISBN: 978-3-032-35803-5
Verlag: Springer Nature Switzerland AG

Buch, Englisch, 226 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Networks and Systems

This book is a collection of best-selected research papers presented at the International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2025) held at Christ University, Kengeri Campus, Bengaluru, India, during September 15–16, 2025. It includes state-of-the-art research work in cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book is useful for academicians, research scholars, and industry persons.

Zielgruppe

Research

Autoren/Hrsg.

Kumar, Sandeep

Mary Anita, E. A.

Coello, Carlos A. Coello

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Bauelemente, Schaltkreise
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Chapter 1: AI-Powered Earthquake Prediction and Response System using Multimodal Data Analytics.- Chapter 2: Beyond the Hash: A Critical Framework for Blockchain-Based Cybersecurity in a Quantum-Ready World.- Chapter 3: Exploring Real-Time Classification of Encrypted Streaming Traffic Using Feed Forward Neural Networks.- Chapter 4: Real-Time Non-Invasive Eco Doppler System for Fetal Health Monitoring.- Chapter 5: Adversarial Robustness in Multi-Agent Reinforcement Learning : An Empirical Study with FGSM Attacks.- Chapter 6: AI-Driven Real-Time Water Management: Integrating IoT, Satellite Data, and Deep Learning.- Chapter 7: Portable Solar Radio Telescope with Track Dashboard.- Chapter 8: An Effective PSO-Based Energy Management System Between G2v And V2g.- Chapter 9: GSM-based Remote Motor Control using Missed Calls.- Chapter 10: Dynamic Pre-Emptive Video Summarization with Integrated Causal Prediction and Memory Networks.- Chapter 11: Multi-Scale Transformer for Protein Interaction Site Prediction.- Chapter 12: RL-AAPF*: Reinforcement Learning-based Adaptive Artificial Potential Field Algorithm for Autonomous Vehicle Navigation.- Chapter 13: Differential Privacy-Aware MLPs for Smart Meter Energy Consumption Forecasting.- Chapter 14: Interictal Epileptiform Discharge Detection using Multi Layered Multi-Head Tunable Convolutional Neural Network.- Chapter 15: Robust Deepfake Audio Detection Under Adversarial and Environmental Noise Conditions.- Chapter 16: Analysis of Conjunctiva Images for Anemia Detection Using MobileNetV3-Small.- Chapter 17: Cloud-Native Renewable Energy Forecasting via Automated Machine Learning and Scalable Pipelines.- Chapter 18: Credit Card Fraud Detection based on ANN and Enhanced Particle Swarm Optimization for Secure Transaction.

Über Autor(innen)

Dr. Sandeep Kumar is currently a professor at CHRIST (Deemed to be University), Bangalore. He recently completed his post-doctoral research at Imam Mohammad ibn Saud Islamic University, Riyadh, Saudi Arabia, in sentiment analysis. He is an associate editor for Springer's Human-centric Computing and Information Sciences (HCIS) journal. He has published more than hundred research papers in various international journals/conferences and attended several national and international conferences and workshops. He has authored/edited twelve books in computer science. Also, he has been serving as General Chair of the Congress on Intelligent Systems (CIS), the International Conference on Communication and Computational Technologies (ICCCT), International Conference on Sustainable and Innovative Solutions for Current Challenges in Engineering & Technology (ICSISCET) and IEEE International Conference on Contemporary Computing and Communications (InC4). His research interests include nature-inspired algorithms, swarm intelligence, soft computing, and computational intelligence.

Dr E. A. Mary Anita holds a B.E and M.E from the Government College of Engineering, Tirunelveli, India, and a Ph.D. in Information and Communication from Anna University, Chennai. She is presently Professor and Associate Dean, School of Engineering & Technology, CHRIST (Deemed to be University), Bangalore. She is a passionate researcher and has served in various teaching and administrative capacities over three decades. She has published over 90 research papers in International and national journals and conferences. She has completed one research project for CVRDE, DRDO, and Chennai and has undertaken various consultancy projects. She has guided 7 PhD scholars and is currently guiding eight scholars. She has published three books and has two patents to her credit. She has received grants worth 75 lakhs from various funding agencies for research and organizing events. Her main research interests are in wireless networks, security, and privacy. She is a Life member of the Indian Society for Technical Education (ISTE), Computer Society of India (CSI), Senior IEEE Member, IAENG, and ACM. She is a peer reviewer for refereed International Journals. Her biography has been included in the 2014 edition of Who's Who in the World, USA.

Prof. Carlos A. Coello Coello (Fellow, IEEE) received the Ph.D. degree in computer science from Tulane University, New Orleans, LA, USA, in 1996. He is currently a Professor with Distinction (CINVESTAV-3F Researcher), Computer Science Department, CINVESTAV-IPN, Mexico City, Mexico. He has authored and co-authored over 500 technical papers and book chapters. He has also co-authored the book Evolutionary Algorithms for Solving Multiobjective Problems (2nd ed., Springer, 2007) and has edited 3 more books with publishers such as World Scientific and Springer. His publications currently report over 78000 citations in Google Scholar (his H-index is 106). His major research interests are evolutionary multiobjective optimization and constraint-handling techniques for evolutionary algorithms.