AI-Enabled Sensing and Decision-Making for IoT Systems. (5th January 2021)

• Record Type: Journal Article
• Authors: Qinxia, Hao; Nazir, Shah; Li, Ma; Ullah Khan, Habib; Lianlian, Wang; Ahmad, Sultan
• Other Names: Uddin M. Irfan Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-01-05
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/6616279
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : The influential stage of Internet of Things (IoT) has reformed all fields of life in general but specifically with the emergence of artificial intelligence (AI) has drawn the attention of researchers into a new paradigm of life standard. This revolution has been accepted around the globe for making life easier with the use of intelligent devices such as smart sensors, actuators, and many other devices. AI-enabled devices are more intelligent and capable of doing a specific task which saves a lot of resources and time. Different approaches are available in the existing literature to tackle diverse issues of real life based on AI and IoT systems. The role of decision-making has its own importance in the AI-enabled and IoT systems. In-depth knowledge of the existing literature is dire need of the research community to summarize the literature in effective way by which practitioners and researchers can benefit from the prevailing proofs and suggest new solutions for solving a particular problem of AI-enabled sensing and decision-making for the IoT system. To facilitate research community, the proposed study presents a systematic literature review of the existing literature, organizes the evidences in a systematic way, and then analyzes it for future research. The study reported the literature of the last 5 years based on the research questions, inclusion and exclusion criteria, and quality assessment of the selected study. Finally, derivations are drawn from the included paper for future research.