Integrating Artificial Intelligence into an Automated Irrigation System - Nicoleta Cristina Gaitan; Bianca Ioana Batinas; Calin Ursu; Filaret Niculai Crainiciuc (Sensors)
Climate change in Eastern Europe requires introducing automated irrigation systems and monitoring agricultural and climatic parameters to ensure food security. The automation of irrigation, together with the generation of climate reports based on AI (artificial intelligence) using OpenAI models for Internet of Things (IoT) data processing, contributes to the optimization of resources by reducing excessive water and energy consumption, supporting plant health through proper irrigation and increasing sustainable agricultural productivity by providing suggestions and statistics to streamline the agricultural process. In this paper, the authors present a system that allows continuous data collection of parameters such as temperature, humidity, and soil moisture, providing detailed information and advanced analytics for each device and area monitored using AI to generate predictive recommendations. The data transmission is performed wirelessly via WebSocket to the central database. This system uses data from all devices connected to the application to assess current climate conditions at a national level, identifying trends and generating reports that aid in adapting to extreme events. The integration of artificial intelligence in the context of monitoring and irrigation of agricultural areas is a step forward in the development of sustainable agriculture and for the adaptation of agriculture to increasingly aggressive climate phenomena, providing a replicable framework for vulnerable regions.