Computational Intelligence and Autonomous Systems

1. Auflage 2026
ISBN: 978-1-041-44676-7
Verlag: Taylor & Francis Ltd

Buch, Englisch, 710 Seiten, Format (B × H): 210 mm x 280 mm

Reihe: Taylor and Francis Proceedings in Computer Science and Engineering

As artificial intelligence and autonomous systems reshape industries at an unprecedented pace, Computational Intelligence and Autonomous Systems offers a timely window into the research driving that transformation. Compiling the proceedings of the International Conference on Computational Intelligence and Autonomous Systems (ICIAS) 2025, hosted by Sir Padampat Singhania University, the book brings together contributions from researchers, academicians, and industry practitioners working at the frontier of intelligent computing.

Organized across ten thematic tracks, the book offers a structured exploration of topics ranging from Digital Transformation Frontiers and Computational Intelligence Horizons to Quantum Computing and Sustainable Management. Readers will find empirical studies, comparative model analyses, and real-world framework evaluations. The book balances theoretical depth with real-world relevance, translating advanced concepts in AI, robotics, and networking into applications that matter across healthcare, business, and urban systems.

This book is a valuable reference for academic researchers, computer scientists, data engineers, software architects, and graduate students working in artificial intelligence, intelligent systems, and robotics. It also serves as an essential reference for tech innovators and industry professionals seeking to deploy sustainable, scalable computational solutions.

Zielgruppe

Academic and General

Autoren/Hrsg.

Goel, Amit Kumar

Goswami, Chandrashekhar

Bhaskar, Anandkumar Atalbihari

Kumar, Rahul

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Mathematik | Informatik EDV | Informatik Technische Informatik Quantencomputer, DNA-Computing
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing

Inhaltsverzeichnis

Multi-Domain Machine Learning Framework for Real-Time Depression Risk Screening. Implications of Virtual Classrooms & Ai Tutors: Towards Achieving Quality Education. An Integrated Approach to Social Media Content Optimization Using NLP and Computer Vision. Varnika - Vernacular Air Writing Interpreter. Disease Detection in Tomato Leaf: Review and Analysis of Recent Technologies. Aarogya: An Ayurvedic Healthcare Solution. A Data-Driven Approach to Predict Soybean Leaf Diseases Using IoT Sensor Networks. Enhancement Of Breast Cancer Research Outcomes through Inclusive Data — A Comprehensive Investigation. Quantifying Emotional Brain Dynamics with Entropy Measures - An EEG Based Classification. Biometric Authentication and Smart Helmet System for Preventing Underage Driving and Ensuring Safety. An Efficient Deep Learning Framework for Analysis and Classification Of PET/CT Lung Cancer Images. Optimizing Battery Energy Arbitrage: A Deep Reinforcement Learning Approach with Hybrid CNN-LSTM Price Forecasting. A Survey on Brain Tumor Diagnosis System with a Personalized Medical Assistance Chatbot. Enhancing Text Summarization and Sentiment Classification Using Transformer- Based Large Language Models (LLMs). A Hybrid Deep Learning Approach for Efficient Classification of Plant Leaf Diseases. Tesseract OCR on a Raspberry Pi 4 for Multilingual Text Recognition. Personalize Diabetes Risk Predictor Using Machine Learning. Accounting for Business Transactions in Electronic Money and Digital Currencies. Machine Learning Based Number Plate Detection And Recognition. Multimodal detection of unsafe practices on construction sites using CNN and social models. Safeguarding IIoT Against Machine Learning-Driven False Data Injection Attacks. Does Perceived Financial Risk Affect the Adoption of Buy Now, Pay Later Technology among Gen Z? A Review on Tomato Plant Disease Detection Using Deep Learning Trends, Challenges and Future Prospects. Enhancing GPSR With Trust Evaluation And Mobility Prediction For Reliable Routing In High-Density Flying Ad Hoc Networks. A Digital Ledger for Secure and Decentralized Access to Medical Records. Automated Code Review with Artificial Intelligence: Enhancing Code Quality and Development Efficiency. Tomato Leaf Disease Detection Using a Hybrid of Convolutional Neural Network and Dragonfly Algorithm. Sukoon: An AI-Driven Therapeutic Chatbot and Research Framework for Mental Health Support. Tooth Segmentation and Detection using U-Net and Attention-based U-Net Technique. Harnessing IoT Data at Scale: Toward Smarter Cities. An Under-Explored Application for Explainable Multimodal Misogyny Detection in Code-Mixed Hindi-English. Revolutionizing Dyscalculia Education by Exploring a Cloud Based Framework. Cost Impact of Post-Quantum Cryptography in Blockchain-Based Cloud Computing for Securing Data. Torque Ripple Sources and Suppression Techniques in BLDC Motors for EV Applications: A Systematic Review. Advancements in Brain–Computer Interfaces Through Artificial Intelligence: A Review. Securing AI Systems: A Cross-Domain Perspective on Adversarial Vulnerabilities and Solutions. Educational Technology Distractions: Impact of Smartphone Addiction on Academic Performance and its mental health effects among Engineering Students from Universities in Thanjavur District: A Bayesian Algorithm Approach. Optimizing Peer-to-Peer Knowledge Exchange Through Adaptive Academic Content Structuring and Discovery. Iris, Face and Fingerprint Spoofing Detection Using Arduino and Matlab. Lung Sound Investigation by Diverged Frequency-depending Strategy. Detecting Financial Fraud Anomalies Using Machine Learning Techniques. A Journey Through the Evolution of Cryptography from Caesar's Cipher to Quantum Keys. An optimization study on nonlinear SMA-SDOF system as a sustainable damping device for blast induced ground motion (BIGM) and future potential of AI-Enhanced SMA Dampers. Computational Intelligence Applications in Electric Vehicles: A Comparative Review of AI-Driven Optimization Strategies. Implementation of Synthetic Minority Over Sampling Technique for better Prediction of Cardiovascular Disease using Machine Learning. A Survey on Skin Conditions and Their Treatments: A Review of Recent Medical Advances. Using Generative AI Intelligence to Support Blind or Visually Impaired People: Managing Textual Concerns. A Comprehensive Survey on Deep Learning Approaches for Diabetic Foot Ulcer Assessment. Deep Learning Based Classification of Handwritten Mathematical Symbols. Real-Time Deep Learning Speech Recognition for Human-Computer Interaction. Leveraging Machine Learning Techniques for Efficient Credit Card Fraud Detection. Multimodal Visual Sentiment Analysis: Integrating Image and Text Features through Deep Fusion and Classifier Ensemble. Towards a HIPAA-Compliant Cloud-Based Healthcare System: A Scalable and Secure AI-Driven. Critical Comparative Analysis of Machine Learning Models for Crop Yield Prediction in Smart Agriculture. Enhancing the Software Bug Prediction using CatBoost. Multi-Objective Optimization with Explainability: A Novel XAI-Driven Metaheuristic (XAI-MO) Framework. Study of Human Capital Valuation Models Implemented in Selected Automobile Companies with Reference to Pune District. Efficient Lung Sound Diagnosis: Multi-Feature Integration in a Lightweight CNN Model. A Hybrid Deep Learning Approach for Intelligent Intrusion Detection. Cerebral Tumor Classification Using Deep Learning With Vision Transformer. Internal Route Optimization in IoT-Enabled Wireless Sensor Networks Using Cluster-Based Architecture and Adaptive Cluster Head Communication. Multi-Label Deep Learning Framework for Smart Grid Environments to Identify False Data Injection Attacks. Deep Neural Network-Based Framework for Lung Carcinoma Detection: A Medical Imaging Perspective. Identification and Classification of Key Genes Involved in Paclitaxel Resistance in Breast Cancer: A Comparative Clustering Analysis. IoT-Enabled Intravenous Therapy System: Flow Control, Backflow Prevention, and Automated Alerts. "EEG-Based Epileptic Seizures: A Comparative Analysis of Deep Architectures, Machine Learning Methods, and Mobile Health Integration". TransformoDocs: A Comprehensive System for Automated Document Conversion and Semantic Retrieval Using Advanced OCR and Vector-Based Embedding Techniques. The Creative Cost of Generative AI (GAI): The Dark Side of Technological Progression. ViT-ConvNet: An Early Alzheimer's MRI Identification Hybrid Model Using CNN and Vision Transformer. Artificial Intelligence Approach for Adolescent Mental Health: A Review. Mobile Application-Feature Analysis and Comment-Driven Rating System. Robust Fabric Defect Detection Using Convolutional Neural Networks: A Model-Level Evaluation. Attention-Based Bidirectional Gated Recurrent Unit for Explainable Clickbait Detection with Focal Loss and Domain-Tuned Embeddings. Enhancing Museum Accessibility in India: A Comprehensive Web Platform for Customized Visitor Experiences. Traffic Prediction Using LSTM Network Architecture Combined with Deep Convolutional Network networks for SDN. Evaluating the Utility of Synthetic Image Generation for Medical AI: A Review. A Conceptual Framework for Analysing the Moderating and Mediating Role of AI in the Corporate Governance–Executive Compensation Relationship. E-Commerce Analytics using Business Intelligence in India: A Systematic Literature Review. Digital Connectivity and Economic Growth: An Indian Perspective. Urban Traffic Crash Risk and Its Impact on Mode Choice in Mumbai Using Safety Performance Functions: A Systematic Review. AI-Powered Robo-Advisors: Enhancing Financial Inclusion and Investor Decision-Making in Emerging Markets. An Under-Explored Application for Explainable Multimodal Misogyny Detection in code-mixed Hindi-English. A Comprehensive Security Analysis of Hybrid Cryptosystems for Enterprise Networks. Privacy-Preserving EHR Systems: Blockchain with Self-Sovereign Identity and ZKPs. Comparing the effect of automated vehicles on the safety of unconventional intersection designs compared to conventional intersections. Travel time reliability and variability before, during and after the COVID-19 pandemic: Exploring the effects by different phases of COVID-19 and speed limit. Design and Experimentation of Forging process - Cup-shaped Forged Component. Leveraging Big Data Infrastructure for Deep Learning Applications. A Decade of Progress in Real-Time Vision Systems: The YOLO family and the Development of YOLOv12. AI-Driven Augmented and Virtual Reality Based on Emotional Intelligence in Human-AI Collaboration. Artificial Intelligence in Computational Design: A New Frontier for Creative Automation. Dimensionality Reduction and Transfer Learning-Based Hybrid Framework for Brain Tumor Classification. Deep Learning Based Diabetic Retinopathy Detection Using DenseNet-121. Exploration–Exploitation Balanced Hybrid DGH-BWO with Lagrangian Constraint Handling for Cloud Scheduling. Mapping the Intellectual Landscape of Robo-Advisory: A Bibliometric Analysis of Global Research Trends (2000–2025). An Intelligent Prognosis of Breast Cancer using Machine Learning Algorithms. Comparative Advantages of One-Part over Two-Part Geopolymer Concrete – A Brief Review. Waste Material Incorporation in Concrete: Performance Evaluation and Strength Analysis. Prevalence and Risk Factors of Diabetic Neuropathy: A Survey-Based Study in the Haryana Region. Low-cost SHM system using MEMS-based sensors for real-time performance monitoring. Quantum-Inspired Tom and Jerry (QITNJ) Optimization: A Breakthrough Metaheuristic for Ultra-Accurate Heart Disease Prediction. An Industrial IoT Security Intrusion Detection Model Based on Ensemble Learning Employing Voting and Stacking Classifiers. A Review of Anomaly Detection Techniques Securing TCP, UDP, and ICMP Protocols in network. Hybrid Cardiovascular Diagnostics: A Hierarchical Multi-Modal Multi-Task Learning Model with AI Feature Extraction. An OLAP-Based Framework for Multidimensional Analysis of Listener Preferences. Deep Learning Framework for Pathogen-Driven Tomato Disease Forecasting: A Comparative Study of CNN Models.

Über Autor(innen)

Amit Kumar Goel is a distinguished academician and administrator with over 27 years of experience, comprising 24 years in teaching and 3 years in industry. He holds a Ph.D. in Engineering from Birla Institute of Technology, Mesra, along with M.Tech. and B.E. degrees in Computer Science and Information Technology. He currently serves as Dean, School of Engineering & Sciences at Sir Padampat Singhania University, where he leads strategic planning, curriculum development, and academic excellence initiatives. He has previously held key leadership positions at Galgotias University, SGT University, and other reputed institutions, overseeing thousands of students and faculty members. His contributions include the design of industry-oriented curricula, development of research ecosystems, and a central role in NAAC and NBA accreditation processes. He has authored 60+ research papers in Scopus, ESCI, and SCI-indexed journals and holds multiple patents in Artificial Intelligence, IoT, and Cybersecurity. A dedicated mentor, he has guided several Ph.D. scholars, collaborated on international research projects, and actively contributed to the organization of conferences, workshops, and technical events, establishing himself as a key figure in academic leadership and innovation.

Chandrashekhar Goswami serves as Deputy Dean and Associate Professor in the Department of Computing & Informatics, School of Engineering & Sciences, Sir Padampat Singhania University, Udaipur. He brings over 15 years of teaching, research, and institutional experience. He completed his Ph.D. from the Vellore Institute of Technology (VIT), Vellore, and holds an M.Tech. in Computer Science and Engineering from Chhattisgarh Swami Vivekanand Technical University, an MBA in Human Resource Management, and a B.E. in Information Technology from Rashtrasant Tukadoji Maharaj Nagpur University. He has presented extensively at international conferences, published 24 research papers in Scopus and Web of Science-indexed journals, and holds four filed patents along with one granted copyright. He is a Life Member of the Computer Society of India (CSI) and the International Association of Engineers (IAENG). His research interests include Database Systems, Mobile Ad Hoc Networks, the Internet of Things, Deep Learning, Wireless Sensor Networks, and Smart City applications. Prior to his current role, he served as Assistant Professor at the National Institute of Technology, Patna, and has delivered numerous technical talks at prestigious academic and industrial forums.

Anandkumar Atalbihari Bhaskar is a distinguished researcher specializing in Embedded Systems, Wireless Sensor Networks, and the Internet of Things, with over 19 years of experience in academia and research. His Ph.D. in Electronics (Embedded Systems) from Saurashtra University focused on the design and development of microcontroller-based embedded circuits and applications. He has successfully supervised ten Ph.D. scholars and continues to lead multiple ongoing research projects in energy-efficient wireless sensor networks, IoT security, and real-time data analytics. He has published 40+ research papers in Scopus-indexed journals and international conferences, covering IoT-enabled smart systems, energy-efficient routing in WSNs, and AI-driven embedded technologies, earning recognition including Best Paper Awards. His research initiatives have secured government and private-sector funding, leading to the establishment of an IoT research laboratory at Sir Padampat Singhania University, and he has served as an International Consultant on IoT projects for organizations in the UK, UAE, and France. He also serves as a reviewer for reputed journals including IEEE Access and ACM Embedded Computing, continuing to advance innovation in smart technologies and sustainable computing.

Rahul Kumar is an accomplished academician and researcher in the Department of Computing & Informatics, School of Engineering & Sciences, Sir Padampat Singhania University. He holds a Ph.D. in Computer Science and Engineering and completed a Postdoctoral Fellowship at the Research Institute of IoT Cybersecurity, National Kaohsiung University of Science and Technology, Taiwan, where his work focused on privacy-preserving feature selection for federated machine learning. With over a decade of teaching and research experience across institutions including Amity University and KL University, his research spans Machine Learning, Federated Learning, and Privacy-Preserving Artificial Intelligence. He has authored 17+ journal publications in SCI and Scopus-indexed venues, 18+ international conference papers, and holds four patents along with one copyright in Artificial Intelligence and Green Computing. He has held key academic leadership roles including Deputy Controller of Examinations and Ph.D. Co-Coordinator and serves as a reviewer for IEEE Xplore and Web of Science-indexed journals.