Real-World Applications of Machine Learning
Description
This book offers a comprehensive collection of 40 research contributions that explore the diverse and growing impact of machine learning across various domains. By aligning its themes with Sustainable Development Goals (SDG9: Industry, Innovation and Infrastructure), the book examines the practical applications ranging from healthcare, agriculture, cybersecurity and renewable energy systems to natural language processing, education and defense technologies. Each contribution highlights contemporary challenges, innovative methodologies and real-world implementations, offering insights into the interdisciplinary nature of machine learning research. The book serves as a valuable reference for researchers, practitioners and students interested in the evolving applications of machine learning to address complex and multidisciplinary problems.
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Persons
Millie Pant is Professor in the Department of Applied Mathematics and Scientific Computing at the Indian Institute of Technology Roorkee (IITR), Uttrakhand, India and a joint faculty Joint Faculty at the Mehta Family School of Data Science and Artificial Intelligence at IITR and is an adjunct faculty at AIT Thailand. She is the current head of the Department and is also the Dean of the Saharanpur Campus of IIT Roorkee. She did her MSc in mathematics from CCS University Meerut and her PhD from IITR. She specializes in data science and artificial intelligence, with significant contributions to optimization algorithms and their applications. She has a robust publication record and has guided numerous Ph.D. and M.Tech. students, reflecting her commitment to research and education in advanced mathematical and computational methods.
Kusum Deep is an Emeritus Professor in the Department of Mathematics and former Joint Faculty at the Mehta Family School of Data Science and Artificial Intelligence, Indian Institute of Technology Roorkee. She is also a Visiting Professor at Liverpool Hope University (UK), University of Technology Sydney (Australia), and Curtin University, Perth (Australia). A graduate of the Centre for Advanced Studies, Panjab University, Chandigarh, she is an M.Phil Gold Medalist and earned her Ph.D. from the University of Roorkee (now IIT Roorkee) in 1988. She has been a national scholarship holder and a Post-Doctoral Fellow at Loughborough University, UK, supported by an International Bursary from the Commission of European Communities. Dr. Deep has received numerous honors, including the Khosla Research Award, UGC Career Award, AIAP Excellence Award, Starred Performer of IIT Roorkee, and multiple best paper awards. She is one of the four women from IIT Roorkee featured in the Women in STEM 2021 e-book published by CII. Since 2019, she has consistently ranked among the top 2% scientists worldwide, according to Stanford University. In 2021, she received the prestigious SERB-DST POWER Grant and since 2022 has led a collaborative AI/ML consultancy project funded by Deloitte. She received the Uttarakhand State Level Excellence in Research of the Year 2022 Award and, in 2023, the Distinguished Alumni Award from Panjab University and a Lifetime Achievement Award from IARS. Her popular NPTEL course on Operations Research has run successfully since 2018. With over 160 research papers, two authored books, and supervision of 25 PhD theses, Dr. Deep is a Senior Member of ORSI, CSI, IMS, and ISIM. She serves on editorial boards of leading journals, including Engineering Applications of Artificial Intelligence. Her research focuses on evolutionary algorithms, swarm intelligence, artificial intelligence, machine learning, and optimization techniques with real-world applications.
Atulya K. Nagar is the Foundation Chair Professor in the School of Mathematics, Computer Science and Engineering, and currently serves as Pro Vice-Chancellor (Research) at Liverpool Hope University, United Kingdom. He earned his DPhil in Applied Nonlinear Mathematics from the University of York in 1996, supported by a prestigious Commonwealth Fellowship. He also holds BSc (Hons), MSc, and MPhil (with distinction) degrees in Mathematical Physics from MDS University of Ajmer, Rajasthan, India. He is a Fellow of the Institute of Mathematics and its Applications (FIMA) and a Fellow of the Higher Education Academy (FHEA). His research encompasses nonlinear mathematical analysis, natural computing, computational optimisation, and systems engineering, with a focus on addressing complex, interdisciplinary challenges. Professor Nagar has been the Foundational Head of the School of Mathematics, Computer Science and Engineering, and served as the inaugural Dean of Faculty of Science at Liverpool Hope University. His leadership has shaped academic development, research growth, and international engagement across disciplines. In recognition of his global academic contributions, he was awarded the Sir C. V. Raman Visiting Professorship by the University of Madras for 2024-2025. Funded by the endowment of the Nobel Laureate, this honour involved delivering a lecture series on complex systems, system dynamics, and mathematical modelling across institutions in Chennai. He also holds a visiting professorship at the Indian Institute of Technology (IIT) Roorkee. A prolific scholar, he has authored or edited several books and published more than 550 research papers. He serves as the founding Series Editor of Springer's Algorithms for Intelligent Systems book series, which highlights cutting-edge developments in computational intelligence and emerging technologies. His academic career includes senior appointments at Brunel University London, lecturing at the Tata Institute of Fundamental Research, BITS Pilani, and various Indian Institutes of Technology as well as South Asian University Delhi.
Content
A Comprehensive Review of Vison Language Models in the Realm of Full Self Driving Systems.- Optimal Defense Strategies for Security Agencies: A Dual Hesitant Fuzzy Matrix Game Approach.- Crop Type Classification using Satellite Images.- Fraud Detection using ML Algorithms.- Analysis of CNN Models with Transfer Learning in Mango Diseases Detection.- Evaluating Machine Learning Techniques for Student Performance Prediction in Higher Education.- Threshold-Optimized Ensemble Learning for Accurate and Secure Android Malware Detection.- Affective DDoS Attack Detection in EV Charging Station using DL Autoencoder Model.- Federated Learning for Privacy-Preserving Next- Word Prediction on Mobile Devices.- AI Based Plant Health Monitoring under Stress Conditions.- Enhanced Weather Forecasting using Random Forest, LSTM, Gradient Boosting and Ensemble Learning (RF+GB).- Spatio-Temporal Analysis and Severity Prediction of Weather Events using Machine Learning Models.- Image Deblurring using Generative Adversarial Networks (GAN).- Triple-head Spatial Attention based Deep Learning Approach for Plant Disease Identification.- Agent Based Analysis for Smart Traffic Management.- Smart Solutions in Veterinary and Animal Sciences: Applications of AI, ML and Soft Computing.- Helmet Mounted IoT based Physiological Health Monitoring System for Soldiers.- Weather-Based Fault Detection in Solar Power Generation by ML.- Advanced Price Forecasting for Food Commodities.- A Practical and Explainable Network Anomaly Detection System for Enhanced Cybersecurity.- Augmenting AI with Context: Hybrid Generative Models for Summarizing Complex Medical Texts.- Detection and Classification of Cassava Diseases using Concatenate Model.- AI based Solution for Smart Traffic Management.- Effective Visualization Approaches for Distributed Denial of Service Threat Prediction in Large-Scale Networks Using Interpretable Machine Learning.- A Novel approach to integrate AI into Judicial Systems.- Energy Efficiency in Software-Defined Wireless Network.- Enhanced Detection of Distributed Denial-of-Service (DDoS) Attacks in Cloud Computing using Transfer Learning, DBSCAN and Entropy Analysis.- Deep Transfer Learning with GUI for Rice Pests Classification and Preventive Recommendations.- A Hybrid Privacy-Preserving Framework for Cryptographic Efficiency in Vehicular Fog Computing Networks.- Explainable Image Classification of Indian Butterflies through Post-hoc Methods.- 5G Antenna Design Using Machine Learning Algorithms.- Robust Hybrid Cryptographic Method for Cloud Computing Information Security.- Advancing Water Quality Prediction: Integrating Ensemble Learning and Explainable AI for Actionable Insights.- Predicting Cryptocurrency Prices with Sentiment Analysis and Deep Learning Models.- RNN and Logistic Regression-Based Ensemble Model for Distinguishing AI-Generated Text.