Potato Crop Irrigation System in Peru Based on IoT and Machine Learning

The growing water scarcity in agriculture poses a critical challenge directly impacting the production of essential crops such as potatoes. This paper proposes an automated irrigation system that utilizes IoT technologies and machine learning to optimize water consumption. This system provides real-time access to irrigation information and offers the possibility of remotely activating the water valve. This combination of functionalities not only simplifies the irrigation process but also optimizes water usage. The system was validated through a case study in two orchards, each measuring 4.85 square meters, and using two 210-liter water containers, over a period of 126 days. The results show an MSE, MAE, and R2 of 1.3E-17, 3.3E-09, and 1.0 respectively, achieving a 24.4% reduction in water consumption, equivalent to 343 liters. These findings not only provide a technological solution for water management in agriculture but also support the environmental sustain ability of the agricultural sector by mitigating water scarcity in farming.