Smart and Distributed Computing

1. Auflage 2026
ISBN: 978-1-041-37651-4
Verlag: Taylor & Francis

Buch, Englisch, 398 Seiten, Format (B × H): 210 mm x 280 mm

Reihe: Taylor and Francis Proceedings in Computer Science and Engineering

The book presents a forward-thinking and interdisciplinary collection of research contributions that seamlessly integrate technological innovation with the principles of sustainability. The core purpose of the book is to foster dialogue and collaboration focused on building intelligent, secure, and environmentally responsible computing systems. As the digital landscape rapidly evolves, ICSDC 2025 addresses the critical need for advanced distributed and intelligent technologies that align with global sustainable development goals.

A prominent feature of ICSDC 2025 is its emphasis on Digital Twin technologies. These virtual counterparts of physical systems allow for continuous monitoring, simulation, and lifecycle management of assets. They are increasingly being adopted in sectors such as industrial automation, infrastructure development, environmental monitoring, and healthcare. By providing real-time feedback and scenario modeling, digital twins promote more informed decision-making and efficient use of energy, materials, and human resources. The conference is deeply aligned with the vision of Industry 5.0, which emphasizes human-centric design, ethical AI, and intelligent automation. ICSDC 2025 highlights innovations that prioritize sustainability, resilience, and collaboration between humans and machines. Topics such as federated learning, cyber-physical systems, and context-aware computing are featured prominently, showcasing the potential of emerging technologies to enable a more inclusive and sustainable industrial future. The book includes research on low-power computing architectures, green AI models, edge intelligence, privacy-preserving mechanisms, and secure distributed systems.

The intended audience of ICSDC 2025 includes academic researchers, industry practitioners, system architects, and policy decision-makers who are working at the intersection of technology and sustainability. It serves as a strategic reference point for those seeking to design, implement, and scale digital ecosystems that are not only smart and secure but also equitable, human-centric, and environmentally sustainable.

Zielgruppe

Academic and Undergraduate Core

Autoren/Hrsg.

Rathore, Pramod Singh

Kumar, Sunil

Inhaltsverzeichnis

1. Impact of Environmental and Host Factors on Mustard Plant Diseases: A DenseNet-Based Deep Learning Framework for Early Detection of Alternaria Blight

2. Vision-Based Techniques for Structural Damage Assessment: Opportunities and Challenges

3. Edge AI and Computer Vision for Real Time Surgical Guidance

4. Agent AI Framework for Intelligent Talent Acquisition and Employee Retention in Smart Organizations

5. AI Powered Customer Behavior Prediction in E Commerce Using Hybrid Deep Learning and IoT Analytics

6. Agent-Based AI for Corporate Social Responsibility (CSR): Towards Data-Driven Sustainability

7. A Hybrid IoT–ML Framework for Forecasting, Anomaly Detection, and Economic Control in Urban Supply Chains

8. AI-Augmented Workforce Analytics: A Deep Learning Framework for Talent Optimization

9. Explainable AI Framework for Predicting Socio-Economic Indicators in Emerging Markets

10. AI-Driven Adaptive Learning Systems Using Reinforcement Learning for Personalized Student Modeling and Instructional Adaptation

11. Attention Enhanced Deep Learning Framework for Multi-Crop Disease Classification Using Real-Time UAV Imagery

12. Intelligent Agent–Driven AI Framework for Talent Acquisition and Workforce Retention in Smart Organizations

13. A 5G-Integrated IoT Framework for Real-Time Crop Disease Detection and Farmer Advisory Services

14. Augmented Human Resource Analytics: A Deep Learning Approach for Talent Optimization

15. Blockchain IoT Integration for Transparent and Secure Financial Transactions

16. Hybrid Deep Learning and Bioelectrical Signal Analysis for Accurate Prediction of Kidney Function Anomalies

17. IoT and AI Driven Smart Agriculture: Predictive Models for Crop Yield and Resource Efficiency

18. Explainable AI-Driven Edge IoT System for Continuous Cardiovascular Health Monitoring

19. Transformers in Education: Personalized Learning Systems with AI-Driven Recommendations

20. Explainable Machine Learning Models for Demand Forecasting and Inventory Management in Smart Commerce

21. IoT-Enabled Smart Irrigation Systems with AI-Driven Crop Yield Prediction

22. Edge IoT Integrated Cardiovascular Monitoring System Using Wearable Sensors and Explainable AI

23. Fraud Detection in Digital Banking and E-Commerce Using Deep Learning Models

24. Digital Twin Frameworks for Remote Patient Monitoring and Predictive Healthcare

25. Explainable NLP Models for Sentiment and Thematic Evolution in Post-Colonial English Literature

26. Machine Learning for Financial Forecasting and Risk Assessment in Global Markets

27. Federated Learning–Based Predictive Analytics for Decentralized Solar Energy Forecasting in Smart Grids

28. Blockchain-Backed Certification Framework for Secure and Verifiable Online Education Systems

29. Generative AI Models for Automated Curriculum Structuring and Intelligent Content Delivery in ICT Education

30. Generative AI for Automated Curriculum Design and Intelligent Content Delivery in ICT Education

31. Lightweight Security Mechanisms for MQTT in Resource-Constrained IOT Environment

32. Integrated Real-Time Object Detection System for Robust Autonomous Vehicle Navigation

33. Cyber-Physical Framework for Smart Ambulance Coordination

34. CipherBox – Advanced Secure File Transmission Using Symmetric Cryptography

35. Integrating Deep Belief Nets for Enhanced Chronic Kidney Disease Prediction using Cat Boost, Random Forest with Logistic Regression as Meta Model

36. An NLP Tool for Translating Welfare Information: A Hybrid Controlled-Language and Domain-Adapted NMT Approach

37. Pomegranate Fruit Disease Identification Using Deep Learning: Validating Public Datasets with Observational Studies from Maharashtra

38. Multilingual automatic speech recognition using wav2vec2 xls-r and transformer

39. Assessing AI Algorithms for Performance Optimization in Satellite Communication

40. Geophysical Waveform Inversion

41. Analysis of the Power-Delay Product in a Full Adder using the Quantum Logic Technique

42. A Symptom-Aware Knowledge Retrieval System Using LLMs and RAG

43. Smart Computing in Society 4.0

44. Comparative Study of Models based on Machine Learning and Deep Learning for Brain Tumor Segmentation

45. Finnlet: An Algo Trading Platform

46. Enhancing Congestion Management in Satellite Networks: A Comparative Study of Traditional and AI-Driven Approaches

47. Making ViTs Practical: Efficient Designs and Edge Deployment Strategies

48. CoSRaK: A Deep Learning Framework for Handwritten Digit Classification

49. Exploiting Trust: A Comprehensive Review of SSL Certificate Abuse in Modern Phishing Attacks

50. Crime Rate Detector: A Data Driven Approach to Streamlining Investigations

51. Blockchain Integrated IoT Architecture for Energy Management in Smart City

52. Effort Estimation in Software Projects Using Machine Learning Techniques

53. Sleep Quality Analysis and Health Monitoring Using IOT

54. Fertilizer Recommendation System Using Deep Learning for Rice Crop

55. AI-Driven Multimodal Fusion of Speech and MRI for Early Detection of Alzheimer’s Disease

56. A Unified Explainable Multimodal Deep Learning Framework for Reliable Cardiovascular Diagnosis and Risk Prediction

57. Explainable Deep Learning in Medical Imaging for Asthma Diagnosis and Phenotyping: A Novel Integrative Framework

58. Deep Learning Based Course Recommender System for Massive Open Online Courses (MOOCs)

59. Enhanced Real-Time ASL Alphabet Recognition and Text Conversion System

60. ICRF: Isotonic Calibrated Random Forest Framework for Diabetes Prediction

61. Sentiment Analysis Using Long Short-Term Memory on Twitter Dataset

62. Learning Activity IOT based Monitor for Special Need Education

63. IoT-Based Gas Leak Detection and Notification System: A Scalable Solution using ESP32, Firebase, and Mobile Integration

64. Topology-Aware Multimodal Fusion of Transformer, GNN, and IoT Streams for Predictive Customer Modelling in E-Commerce Platforms

65. AI-Enhanced Edge Devices for Real-Time Monitoring in Smart Agricultural Systems

Über Autor(innen)

Pramod Singh Rathore is working in the Department of Computer and Communication Engineering, Manipal University Jaipur. He has completed his Ph. D. in Computer Science & Engineering from the University of Engineering and Management, Jaipur (UEM) and done M. Tech in Computer Sci. & Engineering from the Government Engineering College Ajmer, Rajasthan Technical University, Kota, India. With over 15 years of academic teaching experience, he has published more than 95 papers in reputable, peer-reviewed national and international journals, books, and conferences. He has co-authored and edited numerous books with well-known publishers. His research interests include computer networks, data mining, and DBMS. He is a senior member of IEEE. He also serves on the editorial and advisory committees of the Global Journal Group. He is a senior member of reputed technical societies like IEEE. He is also a member of various national and international professional societies in engineering and research, including the ACM and the International Association of Engineers (IAENG).

Sunil Kumar is a distinguished academician, currently serving as Head of the Department of Computer and Communication Engineering at Manipal University Jaipur. He started his journey as an academician as a lecturer at Guru Jambheshwar University Hisar from 2002-2003. From 2003 to 2017, he worked in different academic positions as a Lecturer, Assistant Professor, and Associate Professor at Mody University of Science and Technology, Lakshmangarh. He was an Associate Professor from 2017 to 2020 and Professor since 2020 at the Department of Computer and Communication Engineering at Manipal University Jaipur. Sunil Kumar obtained an M. Tech. in Computer Science and Engineering, from Kurukshetra University, Kurukshetra in 2001. He received a Ph.D. in Engineering from Mody University of Science and Technology in 2015 in Image Forensics. He has qualified Graduate Aptitude Test in Engineering (GATE) in Computer Science and the UGC-National Eligibility Test (NET) in Computer Applications. He has supervised many undergraduate and postgraduate projects and currently supervising 05 Ph.D. thesis. He has authored more than 35 articles in national and international journals and conferences. He is a reviewer of many high-impact journals and an evaluator of Smart India Hackathons. He has been a TPC member of more than 50 international conferences and chaired many sessions. He has one patent granted and many published in patent office journal, India. He has design patents and copyrights to his credit. He is a senior member of reputed technical societies like IEEE, CSI, IUPRAI, and IEI. He has been co-chairman of various international conferences, including Innovations in Computational Intelligence and Computer Vision (ICICV) 2020/2021/2022/2024/2025. He has organized many FDPs including ATAL FDP. His main research areas include Machine Intelligence, Energy Efficient Cloud Infrastructure, and IoT.