Applying Artificial Intelligence (AI) and the Internet of Things (IoT) in designing smart plant care systems

The decline in the labor force and the negative impacts of climate change are posing severe challenges to the agricultural sector. This study presents the design and evaluation of a closed-loop plant care ecosystem applying the Internet of Things (IoT) and Artificial Intelligence (AI). The system utilizes a network of microclimate and capacitive soil moisture sensors to collect real-time data, synchronized via the WebSocket protocol. The focus of the research is the integration of an AI deep learning model for pest identification via an AI Camera and the application of a fertigation system to optimize nutrition. Experimental results show that the system can save up to 80% of water consumption, reduce irrigation labor costs by 90%, and achieve an accuracy of over 80% in pest and disease identification. The research provides a viable solution, ranging from low-cost automation (DIY) scale using ESP32 to industrial scale using PLC S7-1200, contributing to the promotion of a precision and sustainable agriculture model.