Next-Generation Computing and Information Systems

1. Auflage 2026
ISBN: 978-1-041-09216-2
Verlag: Taylor & Francis

Buch, Englisch, 284 Seiten, Format (B × H): 174 mm x 246 mm

This book compiles the proceedings of the Third International Conference on Next-Generation Computing and Information Systems (ICNGCIS 25). It combines high-quality research, practical insights, and scholarly debate spanning traditional domains like distributed computing, networks, and cybersecurity, alongside emerging areas such as AI, IoT, quantum security, and edge computing.

The proceedings include papers addressing currently relevant research issues such as smart contract security, interoperability in the metaverse, AI applications in healthcare, agriculture and related domains. The proceedings present findings with real-world implications for modern computing and information systems, addressing key challenges in design, deployment, operations, performance optimization, and limitation mitigation.

This book targets researchers from academia and industry, practitioners, students, technology enthusiasts, and general audiences seeking to understand cutting-edge applications, practical use cases, and core principles of modern computing and information systems.

Zielgruppe

Academic, General, Postgraduate, Professional Reference, and Undergraduate Advanced

Autoren/Hrsg.

Gupta, Ankur

Inhaltsverzeichnis

Section 1: Keynote Addresses 1. Record Linkage 2. Multiobject Tracking: Challenges, Opportunities and Applications 3. The Future Computational Camera  4. AI For Applications Using Python Language  5. Computing Concepts for Enhancing Artificial Intelligence at the Edge  Section 2: Regular Papers 6. Post Quantum Security for Fog Computing based IoT Systems against Eaves-dropping Attacks 7. Intelligent Traffic Violation Detection Using Deep Learning and YOLOv8n: Sys-tem Design and Performance Analysis  8. Cross-Device Behavioral Fusion in Personal IoT for Early Stress Detection: A Blockchain-Enabled, Privacy-Preserving Architecture 9. Real-Time Hybrid AI Framework for Anomaly Detection in GraphQL APIs un-der Nested-Query Attacks 10. Lightweight Anomaly Detection Using TinyML Models on Simulated IoT Net-works 11. Synergizing Fog and Cloud Computing: Intelligent Task Offloading for Real-Time IoT Applications 12. A learning-based traffic-sensitive optimal route selection method in SDNs 13. Congestion-Aware Multi-Agent Path Planning for Smart Healthcare 14. Performance Analysis of MFCC-GMM and MFCC-CNN Approaches for Isolated Word Recognition in Dogri Language 15. A Privacy-Preserving Federated Meta-Learning Framework for Rare Disease Histopathology 16. Machine Learning Framework for Diabetes Mellitus Classification 17. Deep learning-based multichannel Model for Human Activity Recognition Tech-nology from Wearable Devices 19. Temporal–Spatial Deep Learning Models for Multi-Class DDoS Detection: A Comparative Evaluation 20. Mach–Zehnder Interferometer-Based Photonic Matrix Multiplication for AI Ac-celeration and High-Speed Communication Applications 21. Hybrid Imitation Learning Framework for Optimizing Decision-Making in Con-sumer Electronics Using Lightweight AI 22. Hybrid AI Framework for Real-Time Traffic Violation Detection and Road Safe-ty Enhancement 23. Leveraging the Machine Learning Models to Predict the Impact of Rising Elec-tricity Bill and its expense on the Customers’ Annual Disbursement 24. Cancer Diagnosis Prediction using Borderline-SMOTE Balanced RNA-Seq Data 25. Detection of lumpy skin disease using machine learning based approaches 26. DWT and PCA based Color Image Watermarking using Genetic Algorithm 27. Ensemble Transfer Learning Framework for Early Autism Identification using Structural MRI 28. A Novel Approach for Citrus Greening Disease Severity Assessment: Hybrid Deep Learning Using Autoencoder and Random Forest 29. Deep Learning in Digital Pathology for Prostate Cancer: A Comprehensive Review of Detection, Segmentation, and Grading Methodologies 30. DenCeptionNet-PD: A Transfer Learning–Based Ensemble Framework for Early Prediction of Parkinson’s Disease 31. A Review of Automatic Pronunciation Mistake Detector 32. DANN-Based Harmonization of Multi-Center fMRI for ASD Classification Using ABIDE I and II 33. Early Detection of Lung Cancer Using Convolutional Neural Networks and DNA Methylation Biomarker Analysis 34. Deep Learning Pipeline for Precise Autoimmune Disease Prediction 35. AI-Driven Assistant for Legal Empowerment in India: Leveraging Indian Legal Datasets to Promote Access to Justice

Über Autor(innen)

Ankur Gupta is currently serving as Director at the Model Institute of Engineering and Technology, Jammu (India), besides being a Professor at the Dept. of Computer Science and Engineering. He has 25+ years of experience spanning industry and academia. Prior to joining MIET, he worked as a Team Leader at Hewlett-Packard, India at Bengaluru. He has over 100 published research papers in international journals/conferences. He holds B.E (Hons.) CS and MS degrees from BITS, Pilani and PhD from NIT, Hamirpur. He has 24 patents granted and 75 patents filed at the Indian Patents Office. He is the inventor of the Performance Insight 360, quality analytics framework for higher education which has received several accolades. He has received the DSFT-FIST Grant in 2012, first in the private sector in J&K and received competitive grants over Rs. 2.5 Crore from various funding agencies. He is a recipient of the AICTE Career Award, faculty awards from IBM, EMC and Rs. 2 crores in funding from Govt. agencies. He is also Senior member IEEE and ACM and founder of the International Journal of Next-Generation Computing. His research interests are in cloud computing, P2P networks, network management, artificial intelligence and metaverse.