Convergence of cloud with AI for big data analytics : foundations and innovation /
edited by Danda B. Rawat, Lalit K. Awasthi, Valentina Emilia Balas, Mohit Kumar and Jitendra Kumar Samriya.
- 1 online resource.
- Advances in learning analytics for intelligent cloud-IoT systems .
Includes bibliographical references and index.
Front Matter -- Integration of Artificial Intelligence, Big Data, and Cloud Computing with Internet of Things / Jaydip Kumar -- Cloud Computing and Virtualization / Sudheer Mangalampalli, Pokkuluri Kiran Sree, Sangram K Swain, Ganesh Reddy Karri -- Time and Cost-Effective Multi-Objective Scheduling Technique for Cloud Computing Environment / Aida A Nasr, Kalka Dubey, Nirmeen El-Bahnasawy, Gamal Attiya, Ayman El-Sayed -- Cloud-Based Architecture for Effective Surveillance and Diagnosis of COVID-19 / Shweta Singh, Aditya Bhardwaj, Ishan Budhiraja, Umesh Gupta, Indrajeet Gupta -- Smart Agriculture Applications Using Cloud and IoT / Keshav Kaushik -- Applications of Federated Learning in Computing Technologies / Sambit Kumar Mishra, Kotipalli Sindhu, Mogaparthi Surya Teja, Vutukuri Akhil, Ravella Hari Krishna, Pakalapati Praveen, Tapas Kumar Mishra -- Analyzing the Application of Edge Computing in Smart Healthcare / Parul Verma, Umesh Kumar -- Fog-IoT Assistance-Based Smart Agriculture Application / Pawan Whig, Arun Velu, Rahul Reddy Nadikattu -- Internet of Things in the Global Impacts of COVID-19 / Shalini Sharma Goel, Anubhav Goel, Mohit Kumar, Sachin Sharma -- An Efficient Solar Energy Management Using IoT-Enabled Arduino-Based MPPT Techniques / Rita Banik, Ankur Biswas -- Axiomatic Analysis of Pre-Processing Methodologies Using Machine Learning in Text Mining / Tajinder Singh, Madhu Kumari, Daya Sagar Gupta, Nikolai Siniak -- APP-Based Agriculture Information System for Rural Farmers in India / Ashwini Kumar, Dilip Kumar Choubey, Manish Kumar, Santosh Kumar -- SSAMH - A Systematic Survey on AI-Enabled Cyber Physical Systems in Healthcare / Kamalpreet Kaur, Renu Dhir, Mariya Ouaissa -- ANN-Aware Methanol Detection Approach with CuO-Doped SnO 2 in Gas Sensor / Jitendra K Srivastava, Deepak Kumar Verma, Bholey Nath Prasad, Chayan Kumar Mishra -- Detecting Heart Arrhythmias Using Deep Learning Algorithms / Dilip Kumar Choubey, Chandan Kumar Jha, Niraj Kumar, Neha Kumari, Vaibhav Soni -- Artificial Intelligence Approach for Signature Detection / Amar Shukla, Rajeev Tiwari, Saurav Raghuvanshi, Shivam Sharma, Shridhar Avinash -- Comparison of Various Classification Models Using Machine Learning to Predict Mobile Phones Price Range / Chinu Singla, Chirag Jindal -- Index -- Also of Interest
This book covers the foundations and applications of cloud computing, AI, and Big Data and analyses their convergence for improved development and services. The 17 chapters of the book masterfully and comprehensively cover the intertwining concepts of artificial intelligence, cloud computing, and big data, all of which have recently emerged as the next-generation paradigms. There has been rigorous growth in their applications and the hybrid blend of AI Cloud and IoT (Ambient-intelligence technology) also relies on input from wireless devices. Despite the multitude of applications and advancements, there are still some limitations and challenges to overcome, such as security, latency, energy consumption, service allocation, healthcare services, network lifetime, etc. Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation details all these technologies and how they are related to state-of-the-art applications, and provides a comprehensive overview for readers interested in advanced technologies, identifying the challenges, proposed solutions, as well as how to enhance the framework. Audience Researchers and post-graduate students in computing as well as engineers and practitioners in software engineering, electrical engineers, data analysts, and cyber security professionals.