Smart PV Hydroponic Greenhouse for Sustainable Agriculture in Tunisia - Marouani, Rym; Mahamat, Chabakata; Khachroumi, Sofiane; Bouadila, Salwa; Cherif, Adnen (Engineering, Technology & Applied Science Research, 2024)
This study introduces smart tools and algorithms for controlling and monitoring Sustainable Agricultural Greenhouses (SHG). Through the implementation of solar energy, Internet of Things (IoT) sensor-actuator networks, and artificial intelligence, an SHG with a low carbon footprint has been designed. The former makes minimal use of water resources, resulting in the reduction of costs while optimizing crops and harvests. After choosing the structure and architecture of the system introduced, optimized PID controllers based on Artificial Neural Networks (ANN) are proposed, for the maximum power to be derived from the Photovoltaic (PV) solar source and the efficiency of the pump to be improved. Additionally, an IoT-based remote control system has been created using an ESP32 microcontroller with a Wi-Fi interface along with sensors for monitoring solar irradiation, soil moisture, indoor temperature, humidity, lighting, ventilation, and water flow. The system collects sensor data in real-time and employs a built-in algorithm to update the information in the cloud. The experimental measurements carried out in the SHG allowed for the verification of the chosen models and simulation results. Thanks to the hybridization of renewable energies, hydroponic techniques, smart technologies, and sustainable practices, this cutting-edge greenhouse creates an ideal microclimate for year-round cultivation while preserving the ecosystem’s energy and water resources.