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AuthorQinxia, Hao
AuthorNazir, Shah
AuthorLi, Ma
AuthorUllah Khan, Habib
AuthorLianlian, Wang
AuthorAhmad, Sultan
Available date2022-12-28T07:14:17Z
Publication Date2021-01-05
Publication NameComplexity
Identifierhttp://dx.doi.org/10.1155/2021/6616279
CitationQinxia, H., Nazir, S., Li, M., Ullah Khan, H., Lianlian, W., & Ahmad, S. (2021). AI-enabled sensing and decision-making for IoT systems. Complexity, 2021.
ISSN1076-2787
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85099636867&origin=inward
URIhttp://hdl.handle.net/10576/37703
AbstractThe 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.
SponsorNational Natural Science Foundation of China (51804248).
Languageen
PublisherHindawi
SubjectArtificial intelligence
Internet of things
Decision making
TitleAI-Enabled Sensing and Decision-Making for IoT Systems
TypeArticle
Volume Number2021
ESSN1099-0526
dc.accessType Open Access


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