Title: Cognitively-inspired intelligent decision-making framework in cognitive IoT network

Authors: Vidyapati Jha; Priyanka Tripathi

Addresses: Department of Computer Applications, National Institute of Technology, Raipur, Chhattisgarh, India ' Department of Computer Applications, National Institute of Technology, Raipur, Chhattisgarh, India

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.

DOI: 10.1504/IJNVO.2024.142239

International Journal of Networking and Virtual Organisations, 2024 Vol.31 No.2, pp.87 - 105

Received: 05 Dec 2023
Accepted: 21 Jun 2024
Published online: 15 Oct 2024 *

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