Digitalization & Sustainability Review

Peer Reviewed Article

Vol. 3 No. 1 (2023)

IoT-Enabled Smart Agriculture System Using Cognitive Computing

Published
2023-09-30

Abstract

This paper explores the application of cognitive computing to integrating IoT-enabled innovative agriculture systems and its consequences for contemporary farming methods. The main goals are to examine these technologies' advantages, difficulties, and possible uses in agriculture and determine the policy ramifications for their broad implementation. A thorough analysis of current literature, including peer-reviewed journal articles, conference proceedings, industry reports, and case studies, is a crucial part of the technique. Key findings emphasize the increased accuracy and productivity of AI-driven decision-making and real-time data collecting, enhanced yield prediction and crop health monitoring, livestock management optimization, and streamlining supply chain operations. Widespread adoption is, however, hampered by obstacles such as high starting costs, scalability problems, data protection difficulties, and the requirement for technical skills. The policy implications include encouraging research and development, supporting farmers and training, and offering incentives for investments in innovative agriculture technologies. There is a great deal of promise to solve significant issues and open up new avenues for agriculture through integrating IoT-enabled innovative agriculture systems with cognitive computing, opening the door to a more resilient, sustainable, and adequate food system.

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