Evaluating low-cost internet of things and artificial intelligence in agriculture

Kamal Elhattab, Said Elatar

Abstract


This article investigates the transformative impact of low-cost internet of things (IoT) solutions on the agricultural sector, with a particular emphasis on integrating artificial intelligence (AI) and machine learning (ML) technologies. The study aims to illustrate how affordable IoT technologies, when combined with advanced AI and ML capabilities, can serve as a significant asset for small and medium-sized farms. It addresses the economic and technical barriers these farms face in adopting such technologies, including high initial costs and the complexity of implementation. By conducting a comprehensive evaluation of existing IoT hardware and software, the research identifies and highlights innovative, cost-effective solutions that have the potential to drive significant advancements in agricultural practices. The findings underscore how these integrated technologies can enhance operational efficiency, increase productivity, and support sustainable agricultural development. Additionally, the paper explores the potential challenges and limitations of adopting these technologies, offering insights into how they can be mitigated. Overall, the study demonstrates that the convergence of low-cost IoT with AI and ML presents a valuable opportunity for modernizing agriculture and improving farm management.


Keywords


Agriculture; AI; Challenges; Hardware; IoT; Machine learning; Software

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DOI: http://doi.org/10.11591/ijeecs.v37.i2.pp968-975

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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