Real-Time Artificial Intelligence (AI)

Key Motivations, Technologies, Platforms, and Use Cases
1. Auflage 2026
ISBN: 978-1-998511-34-1
Verlag: Apple Academic Press Inc.

Buch, Englisch, 532 Seiten, Format (B × H): 152 mm x 229 mm

Demonstrating the benefits of the real-time capture of data using AI, this new volume discusses how AI services and applications are indispensable for setting up and sustaining real-time enterprises, using historical as well as runtime data to extract actionable insights in the needed time, leading to insights. Chapters showcase the applications of real-time artificial intelligence in diverse sectors, such as using deep learning for plant disease detection, using AI for IT entrepreneurship, in healthcare for breast cancer and eclampsia screening and monitoring, for fraud detection in online transactions, for traffic sign detection and classification in autonomous vehicles, and more.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Rao, B. Narendra Kumar

Raj, Pethuru

Sundaravadivazhagan, B.

Vijaykumar, Hannah

Kavitha, V.

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

1. Machine Learning and Deep Learning Algorithms for Modern Science and Technology: Applications and Challenges 2. Exploring Incremental and Deep Learning Approaches for Plant Disease Detection: A Comprehensive Review 3. Machine, Deep, and Reinforcement Learning Algorithms and Applications 4. AIOps-Powered Entrepreneurship: Harnessing AI for Operational Excellence and Rapid Growth 5. Leveraging Incremental Learning for Agile Entrepreneurship: A Practical Guide to Continuous Learning and Adaptation in Dynamic Markets 6. Development of Artificial Intelligence-Based Breast Cancer (BC) Prediction in Healthcare Systems 7. An Energy-Efficient Approach-Based Prediction in Sensor Cloud System by Using Machine Learning Methods 8. Using Online Predictions and Machine Learning for Fraud Detection in Online Transactions 9. Incremental Learning in Real-Time Artificial Intelligence 10. Exploring of AI-Powered Applications in Chatbots for Future Development 11. Ax-YOLOv8-Based Indian Traffic Sign Detection and Classification in Autonomous Vehicle 12. Empowering Womens Health: Artificial Intelligence Applications in Pre-Eclampsia Screening and Monitoring 13. Incremental Learning 14. Understanding the Role of Artificial Intelligence in the Industry 4.0 Ecosystem: A Digital Transformation: Case Studies 15. Artificial Intelligence for the Digital Era: Unleashing the Power of Intelligent Technologies 16. An Enhanced Hidden Markov Model for Predicting Two-Tier Webpage and Improving Accuracy 17. Operationalizing Machine Learning: The Path to MLOps Excellence

Über Autor(innen)

Pethuru Raj, PhD, is Chief Architect and Vice President at Reliance Jio Platforms Ltd., India. Previously, he worked as a cloud architect at the IBM Global Cloud Center of Excellence, as an enterprise architect at Wipro Consulting Services, and as a software architect at Robert Bosch Corporate Research. In total, he has gained more than 24 years of IT industry experience and eight years of research experience.

B. Sundaravadivazhagan, PhD, is a Professor of Information Technology at the University of Technology and Applied Science, Oman. With over 23 years of experience, he has published many research papers and has contributed to multiple international conferences. He has received research grants from Oman’s TRC and serves on academic committees, including at Amrita University and Saveetha School of Engineering, India.

V. Kavitha, PhD, is an Associate Professor of Computer Science with Cognitive Systems, Sri Ramakrishna College of Arts and Science, India. She has over 20 years of teaching and research experience. She has published many research papers in international as well as national journals and international conferences and book chapters and has delivered technical talks in the areas of big data analysis and cybersecurity.

B. Narendra Kumar Rao, PhD, is a Professor and Program Head of the Department of AI & ML at the School of Computing, Mohan Babu University, India, where he is also a member of the Research Advisory Committee and Doctoral Supervisor Cluster Head. He has been a conference convener and conference chair, has published articles in reputed journals and conferences, and has edited two proceedings published by Springer. He has won several awards for his work.

Hannah Vijaykumar, PhD, is an Associate Professor and Head of the Department of Computer Science at Anna Adarsh College for Women, India, where she also serves as Dean of Computational Studies. She has 26 years of teaching experience. She has published papers in Scopus-indexed journals and in international conferences. She has also published book chapters and authored several books. She has two international patents to her credit.