AI and Machine Learning in Cloud-Based Internet of Things (IoT) Solutions: A Comprehensive Review and Analysis - Padyana, Uday Krishna; Rai, Hitesh Premshankar; Ogeti, Pavan; Fadnavis, Narendra Sharad; Patil, Gireesh Bhaulal (Integrated Journal for Research in Arts and Humanities, 2023)
This paper undertakes a detailed review of a novel topic that revolves around integrating AI and ML in cloud-based IoT systems. This paper focuses on those technologies and discusses their potential interaction and influence on IoT systems and frameworks for IoT data and devices, analytics, management, security, and decision-making methods. Mentioning the findings in the current literature, and after analysing a number of successful and failing implementations of Gamification, this paper reveals the specific problems, presents new ideas and makes suggestions for the future studies. The prospects of affinity unveil the futuristic potential of AI & ML in optimising the performance, capacity, and wisdom of cloud-based IoT systems in the fields of smart cities, industrial IoT, and healthcare, etc. The study shows the following increase in efficiency: the energy consumption decreases by 30-40%; the accuracy of prediction increases by 30-50%; the decrease in the network latency is 25-35%. However, the following challenges persist with the current implementations; the disclosure of users’ data privacy, compatibility, and continuing debate on standards.