Data Science and Big Data Analytics

Proceedings of IDBA 2026, Volume 2
Erscheinungsjahr 2026
ISBN: 978-3-032-42957-5
Verlag: Springer

Buch, Englisch, 576 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Learning and Analytics in Intelligent Systems

This book features high-quality research papers presented at the Sixth International Conference on Data Science and Big Data Analytics (IDBA 2026), organized by Symbiosis University of Applied Sciences, Indore, India, in association with ACM and IEEE Computer Society in hybrid mode during July 3–4, 2026. This book discusses topics such as data science, artificial intelligence, machine learning, quantum computing, big data and cloud security, computation security, big data security, information security, forecasting, data analytics, mathematics for data science, graph theory and application in data science, data visualization, computer vision, and analytics for social networks.

Zielgruppe

Research

Autoren/Hrsg.

Mishra, Durgesh Kumar

Yang, Xin-She

Unal, Aynur

Jat, Dharam Singh

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

PAAMDDS: Predictive AI-Driven Aero-Medical Drone  Delivery System for optimized Emergency Dispatch and  Deep Learning-Based Target Tracking.- Air Quality Barriers in NCR: Trend Analysis and 2030 Projections.- An Empirical Evaluation of Machine Translation Techniques for Sanskrit–English Translation.- Dual-Lane Traffic Analytics and Border Surveillance Using Fine-Tuned YOLOv8: A Real-Time Metadata-Driven Approach.- Reducing Hallucinated Legal Citations in LLM Responses for Indian Law: A Citation-Aware Knowledge Graph Verification Approach.- Explainable Drug Adoption Forecasting using Knowledge Graphs.- Explainable Vision-Based Gait Analysis for Remote  Screening of Ataxia Using Pose Guided Machine  Learning.- AI-Driven Panic Detection and Emergency Response Framework Using Physiological Signal Analytics, Hybrid Deep Learning Models, Knowledge Graph Intelligence and Geofenced Risk Mapping.- A Knowledge Graph-Driven Machine Learning Framework for Predictive Market Intelligence and Economic Decision Analytics.

Über Autor(innen)

Durgesh Mishra obtained his Ph.D. in Computer Engineering from DAVV Indore. He worked at IIT Indore as a visiting professor. Currently, he is working as a professor and director at Symbiosis University of Applied Science, Indore. He is the chairman of IEEE Computer Society, Madhya Pradesh Section. He served as a national chairman Computer Society of India for about 5 years and treasurer for about 3 years. He is the chairman of the ACM Indore chapter. He has published more than 120 peer-reviewed papers with good citations. He supervised 7 Ph.Ds. and more than 50 master’s students. He has 6 patents granted and 12 published. He was awarded with a Lifetime Achievement award, the international paper presenter award, and the best paper award. He was the chairman IEEE Computer Society chapter, Bombay section (2010). He has published 2 books DBMS and C++ programming.

Xin-She Yang obtained his D.Phil. in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and then later at National Physical Laboratory (UK) as a senior research scientist. Now he is a reader at Middlesex University, London, and a co-editor of the Springer Tracts in Nature-Inspired Computing. He is also an elected fellow of the Institute of Mathematics and its Applications (FIMA, UK) and fellow of Asian Computational Intelligence Society. He was the IEEE Computational Intelligence Society (CIS) chair for the Task Force on Business Intelligence and Knowledge Management (2015 to 2020). He has published more than 40 books and more than 350 peer-reviewed research papers with more than 95,600 citations. He has been on the prestigious list of most influential researchers or highly cited researchers (Web of Sciences) for ten consecutive years since 2016.

Dharm Singh Jat is a professor of Computer Science and the UNESCO Chairholder on Secure High-performance Computing for Higher Education and Research established at Namibia University of Science and Technology (NUST). He received his Master of Engineering and Ph.D. in Computer Science and Engineering. He has supervised 9 Ph.Ds. and 27 Master’s students, author of more than 200 peer-reviewed articles, and author or editor of more than 20 books and conference proceedings. He has received more than 19 prestigious awards as a Scientist and Engineer. He is a fellow of The Institution of Engineers and the fellow of the Computer Society of India. His professional awards include the Eminent Scientist Award, Distinguished Academic Achievement, Eminent Engineering Personality, CSI Chapter Patron and Significant Contribution, Best Faculty Researcher, Best Technical Staff, Outstanding University Service, Distinguished ACM Speaker Award, and IEEE Computer Society DVP Speaker award.

Aynur Unal is educated at Stanford University (doctoral advisers were Prof. George Herrmann of Engineering and Prof. Harold Levine of Mathematics). She built a new computational acoustics program from scratch at Stanford University and had worked on noise reduction in various systems including Mac series and Next work stations. She took part in early Silicon Valley startup companies using ultrasound for diagnostics in both machine and human health. She used the first Artificial Neural networks in diagnostics. She was the chief technical architect of www.e2open.com. She developed the secure and private e-services, e-financial systems, e-manufacturing, e-health, and e-learning as a member of the Executive Team. In 2010, she became the Dean of Engineering at Ansal University. Advisor to several universities in India, visiting professor at IITG, Guwahati, and is an executive advisor at Stanford Medical School. Her research interests are Secure, Smart, and Sustainable Digital Systems and Services.