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Published:
Mar 10, 2024Keywords:
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Tanzania Journal of Engineering and Technology (Tanz. J. Engrg. Technol.) publications are written as a basis for academic discussions. Whereas effort is made by the Editorial Board to screen out inaccurate or misleading statements, data or opinions, Tanz. J. Engrg. Technol. wishes to make it clear that the contents of the articles are the sole responsibility of the authors. Accordingly, the Editorial Board and editors, publisher, College of Engineering and Technology and the University of Dar es Salaam accept no responsibility or liability whatsoever for the opinions, inaccurate or misleading data or statement and views expressed by the authors.
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Main Article Content
Comprehensive Survey on Applications of Internet of Things, Machine Learning and Artificial Intelligence in Precision Agriculture
Abstract
A comprehensive, multidisciplinary analysis of the latest developments in digital agriculture is conducted with the use of artificial intelligence (AI), machine learning (ML), and the Internet of Things. By automation and the use of modern, scalable technology solutions that reduce risks, support sustainability, and give farmers predictive advice, traditional agricultural processes are being updated and improved to maximize production. In this paper, the applications of AI, IoT, and ML in agricultural production systems are discussed in detail. The applications that have been explored can be broadly categorized into three areas: soil management, livestock management, and crop management. Weed detection, disease identification, and yield forecasting are some of the applications for crop management. Two applications of livestock management are animal welfare and production. The use of AI, IoT, and ML will make it possible to collect data from agricultural activities for analysis and the extraction of insightful knowledge, facilitating prompt and accurate decision-making to increase agricultural productivity. This will result in farming that is more exact and efficient while requiring less labour and producing high-quality produce.
