Agriculture holds a crucial role in fulfilling food demands and bolstering the national economy, particularly in Indonesia. However, farmers often encounter challenges such as limited land availability, soaring costs, and suboptimal irrigation practices. Precision farming, leveraging the Internet of Things (IoT) and artificial intelligence (AI), emerges as a viable solution for sustainable and efficient agricultural practices. With the escalating demand for food, the agricultural sector must strive for optimal efficiency and productivity. The deployment of an IoT-based monitoring system facilitates chili crop management for farmers by providing real-time insights into soil conditions, temperature, and humidity. Through the utilization of the Artificial Neural Network (ANN) method, this system enables automated watering tailored to the specific water intensity requirements of the crops. The ANN algorithm is employed through a rigorous three-stage process encompassing training, testing, and validation, aiming to maintain soil moisture levels above 80%.
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Ismail et al. (2024) studied this question.
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