Business Intelligence and Data Analytics
Description
This book is a collection of the high-quality research articles presented at the International Conference on Business Intelligence and Data Analytics (BIDA 2025), organized by RV Institute of Management (RVIM), Bengaluru, India, during April 2025. This book covers state-of-the-art research articles from the researchers and practitioners working in the field of business intelligence, data analytics, decision support systems, data warehousing and data mining, big data analytics, predictive and prescriptive analytics, and machine learning for business applications and their real-world applications.
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Persons
Dr. Abhishek Verma is an assistant professor in the Department of Management at BITS Pilani, Pilani Campus. Before joining BITS Pilani, he was with the Indian Institute of Management Rohtak for over four years, where he worked in the Management Information Systems area. He holds a Ph.D. from the Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur. His research focuses on data analytics, particularly analyzing large-scale textual and categorical data using data mining and machine learning techniques. Dr. Verma has published extensively in reputed international journals, including Safety Science, Enterprise Information Systems, Computers & Industrial Engineering, International Journal of Injury Control and Safety Promotion, and Process Safety and Environmental Protection.
Justin Zhang teaches courses of Information Systems and Business Analytics in the Department of Management at University of North Florida. He received his Ph.D. in Business Administration with a concentration on Management Science and Information Systems from Pennsylvania State University, University Park. His research interests include economics of information systems, knowledge management, electronic business, business process management, information security, and social networking. He is the editor-in-chief of the Journal of Global Information Management , an ABET program evaluator, and an IEEE senior member. His areas of Expertise are Business Analytics, Economics of Information Systems, Information Security, Knowledge Management, Social Media.
Dr. Avinash Chandra Pandey is currently serving as an assistant professor in the Discipline of Computer Science & Engineering of PDPM Indian Institute of Information Technology, Design, and Manufacturing, Jabalpur (IIITDM), India. He did his Ph.D. in the field of data analytics under the supervision of Dr. Dharmveer Singh Rajpoot. His research areas include machine learning, text mining, and nature-inspired computing. He has over 9 years of research and teaching experience at UG and PG levels. He has published more than 40 research papers in international peer-reviewed journals of repute, national, and international conferences in India and abroad, and 02 patents. He has also guided many Ph.D. (Ongoing 01), M.Tech. (Awarded 02, Ongoing 01), and B.Tech. (Project: Awarded 30) students. He is a reviewer for various government-funded projects and leading international journals of repute.
Content
Number Plate Recognition using Machine Learning Algorithms and CNN.- Comparative Analysis of Machine Learning Algorithms for Cryptocurrency Price Forecasting in Volatile Markets.- Detection of Fake Online Products using Unsupervised GAN with Grad-CAM Visualization.- Unemployment Rate Prediction Based on Recurrent Neural Networks with Attention Mechanism Tuned by Modified Chimp Optimization Algorithm.- Real-Time Traffic Monitoring for Anomaly Detection and Congestion Management.- Advanced Abnormal Activity Detection in Online Exams with YOLOv8.- Maize and Citrus Disease Classification with EfficientNet-B0 for Real Time Detection.- Application of Artificial Intelligence Techniques for Accurate Classification and Reliable Rainfall Prediction.- Integrating TF-IDF and Fuzzy Matching: A Robust Approach to Code Plagiarism Detection.- Intelligent Analytical Framework to Reduce Customer Retention Efforts in the SaaS Industry.- DUAL CREDIT SCORING - Enhancing Creditworthiness Analysis using Spending Patterns and AI.- The Proactive Role of Big Data and IoT in Smart Cities: Achieving SDG 7 through Smart Grids.- Edge-Based DDoS Mitigation in IoT Home Automation using CNN-LSTM.- Harnessing Deep Learning for Efficient Rice Disease Detection with CNN and Advanced Transfer Learning Techniques.- Predicting Carbon Emissions using Hybrid Machine Learning and Deep Learning Models.- A Meta-learning Approach for Psychological Needs Prediction.- Bone Fracture Detection in X-rays using Advanced Deep Learning Modeling.- Navigating Truth: Unravelling the Web of Fake News through RAG.- Mul-Sensis: Multilingual sentiment analysis framework for emotion detection.- A Hybrid Approach for Rice Grain Image Classification using Deep Learning and Machine Learning Algorithms.- Occasion and Color Aware Personalized Outfit Recommendation System with Natural Language Interaction.- Enhancing Stress and Anxiety Detection Accuracy through Multimodal Sensor Fusion and Advanced Machine Learning Techniques
FPGA Based Neural Face Recognition Systems - A Survey.- Towards Sustainable Food Security in India: The Strategic Role of Optimized Cold Chain Infrastructure.- A Systematic Review of Machine Learning and Deep Learning for Mental Health Diagnosis.- Enhancing Real-Time Financial Advisory using Retrieval Augmented Generation (RAG) and Intelligent Agents.- Deep Learning Models for EEG-Based Brain-Computer Interface using Motor Imagery.- Tuberculosis Detection using Deep Learning Networks and Chameleon Swarm Algorithm.- An Attention Mechanism based Deep Learning Model for Assessing Quality of the Produce.- Robust Security Framework for Improving Security in Learning Management Systems: User Verification, Access Control, and Payment Integration.- Leveraging User Entity Behavior Analytics for Advanced Ransomware Detection and Protection.- 3D Pose Estimation in Sports using Deep Learning.- Design and Timing Analysis of 32 Bit Pipelined Wallace Tree multiplier.- Sustainable Agriculture Drone Selection: A Multi-Criteria Decision-Making Approach Using VIKOR Method.- Implementation of XGBoost Algorithm using Chi-Square Feature Selection for Early Detection of Hepatitis C Disease.- Handwritten Digit Recognition using CNN.- Blood Smear Image-Based Malaria Prediction using ACO-GWO for Healthcare Diagnostics.- Sentiment Viz: Leveraging RoBERTa in Python for Advanced Sentiment Analysis and Decision-making for a Famous Indian FMCG (Ayurvedic) Brand.