 Cognitively-inspired intelligent decision-making framework in cognitive IoT networkVidyapati Jha and Priyanka Tripathi International Journal of Networking and Virtual Organisations, 2024, vol. 31, issue 2, 87-105 Abstract: Numerous Internet of Things (IoT) applications require brain-empowered intelligence. This necessity has caused the emergence of a new area called cognitive IoT (CIoT). Reasoning, planning, and selection are typically involved in decision-making within the network bandwidth limit. Consequently, data minimisation is needed. Therefore, this research proposes a novel technique to extract conscious data from a massive dataset. First, it groups the data using k-means clustering, and the entropy is computed for each cluster. The most prominent cluster is then determined by selecting the cluster with the highest entropy. Subsequently, it transforms each cluster element into an informative element. The most informative data is chosen from the most prominent cluster that represents the whole massive data, which is further used for intelligent decision-making. The experimental evaluation is conducted on the 21.25 years of environmental dataset, revealing that the proposed method is efficient over competing approaches. Keywords: IoT; Internet of Things; CIoT; cognitive IoT; intelligent decision; data reduction. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijnvor:v:31:y:2024:i:2:p:87-105 Access Statistics for this article More articles in International Journal of Networking and Virtual Organisations from Inderscience Enterprises Ltd |
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