Intelligent Actuator Control in Smart Agriculture through Machine Learning and Sensor Data Integration - Azmi, Fadhillah; Gibran, M. Khalil; Fawwaz, Insidini; Anugrahwaty, Rina; Saleh, Amir (UIN Sumatera Utara, 2025)
Smart agriculture leverages Internet of Things (IoT) technology to develop intelligent greenhouses capable of monitoring and responding to environmental changes in real time. This study proposes the use of machine learning to analyze real-time sensor data—such as temperature, humidity, water level, and soil nutrient levels (N, P, K)—to determine the optimal timing for activating actuators, including fans, irrigation systems, and water pumps. In the initial stage, the study utilized the