High human population growth has caused serious problems related to the availability of water for agricultural use, which could potentially threaten food production globally. Traditional irrigation methods are currently proving inefficient, resulting in significant wastage of water resources. To address these challenges, research is proposed to apply the Internet of Things in the development of multiple linear regression-based precision irrigation systems to smart irrigation valve technology. Environmental data and plant needs will be processed through machine learning algorithms, which will provide precision solutions in irrigation water management. The results showed that the technology built was able to predict water needs with an accuracy rate of 97.4% against references. The implementation of this system can make a positive contribution in optimizing water use for agriculture, with a positive impact on the overall efficiency of food production.
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Andayani et al. (2024) studied this question.
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