Smart City Gnosys

Smart city article details

Title	Towards Efficient Information Retrieval In Internet Of Things Environments Via Machine Learning Approaches
ID_Doc	58119
Authors	Yuan Q.; Lai Y.
Year	2025
Published	Journal of The Institution of Engineers (India): Series B, 106, 1
DOI	http://dx.doi.org/10.1007/s40031-024-01178-w
Abstract	The Internet of Things (IoT) brings countless real-world items together, producing a great deal of data. The IoT efficiently retrieves information from diverse data sources to achieve intelligent applications. In this regard, IoT systems can benefit from Machine Learning (ML) approaches in improving information retrieval. In this paper, advanced ML methods are thoroughly examined for this specific purpose, considering the unique constraints that IoT data present, such as its variety, capacity to accommodate a considerable amount of data, and constant change. The study covers both unsupervised and supervised learning approaches, emphasizing the critical role ML has in dealing with IoT data. Deep learning architectures model practical features of the unstructured data handled by natural language processing. This review discusses reinforcement learning methods applied to IoT environments, while ensemble learning methods are explored in seeking enhanced information retrieval performance and robustness. Further, we present real case studies that indicate how ML has been useful in rich domains such as health informatics and smart cities. Finally, the review discusses future directions, contemplating a scenario where ML will keep shaping IoT information retrieval. © The Institution of Engineers (India) 2024.
Author Keywords	Data management; Deep learning; Information retrieval; Internet of things; Machine learning; Natural language processing

Similar Articles

Id	Similarity	Authors	Title	Published
36075	0.892	Bzai J.; Alam F.; Dhafer A.; Bojović M.; Altowaijri S.M.; Niazi I.K.; Mehmood R.	Machine Learning-Enabled Internet Of Things (Iot): Data, Applications, And Industry Perspective	Electronics (Switzerland), 11, 17 (2022)
56602	0.888	Mishra S.; Tyagi A.K.	The Role Of Machine Learning Techniques In Internet Of Things-Based Cloud Applications	Internet of Things (2022)
6593	0.886	Rao G.S.; Yuvaraj S.A.; Kondapi N.R.; Kumari A.R.; Palepu N.R.; Bharathi C.R.; Arulananth T.S.; Ebinezer M.J.D.	Advancements In Machine Learning For Iot: Ai-Driven Optimization And Security	Journal of Information Systems Engineering and Management, 10, 17 (2025)
35982	0.88	Alsamhi S.H.; Almalki F.A.; Al-Dois H.; Ben Othman S.; Hassan J.; Hawbani A.; Sahal R.; Lee B.; Saleh H.	Machine Learning For Smart Environments In B5G Networks: Connectivity And Qos	Computational Intelligence and Neuroscience, 2021 (2021)
28691	0.878	Goel N.; Yadav R.K.	Handbook Of Research On Machine Learning-Enabled Iot For Smart Applications Across Industries	Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries (2023)
9370	0.877	Haouam K.-D.	Analysis Of The Role Of Machine Learning In The Internet Of Things (Iot)	Colloquium in Information Science and Technology, CIST (2023)
975	0.873	Khan M.A.A.; Kaidi H.M.	A Comprehensive Survey Of Machine Learning Techniques In Next-Generation Wireless Networks And The Internet Of Things	Ingenierie des Systemes d'Information, 28, 4 (2023)
6499	0.873	Rao S.; Gongada T.N.; Khan H.; Anand R.; Sindhwani N.; Gupta A.	Advanced Deep Learning Integration For Iot Ecosystem For Content Classification	2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2024 (2024)
36064	0.87	Alfahaid A.; Alalwany E.; Almars A.M.; Alharbi F.; Atlam E.; Mahgoub I.	Machine Learning-Based Security Solutions For Iot Networks: A Comprehensive Survey	Sensors, 25, 11 (2025)
35964	0.869	Gangal R.; Johri P.; Kumar A.	Machine Learning For Internet Of Things: A Recapitulation	2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021 (2021)