Optimization of crop yield in precision agriculture using WSNs, remote sensing, and atmospheric simulation models for real-time environmental monitoring

Due to the increasing demand for agricultural production and the depletion of natural resources, the rational and efficient use of resources in agriculture becomes essential. Thus, Agriculture 4.0 or precision agriculture (PA) was born, which leverages advanced technologies such as Geographic Information Systems (GIS), Artificial Intelligence (AI), sensors and remote sensing techniques to optimize agricultural practices. This study focuses on an innovative approach integrating data from different sources, within a GIS platform, including data from an experimental atmospheric simulator and from a wireless sensor network, to identify the most suitable areas for future crops. In addition, we also calculate the optimal path of a drone for crop monitoring and for a farm machine for agricultural operations, improving efficiency and sustainability in relation to agricultural practices and applications. Expected and obtained results of the conducted study in a specific area of Reggio Calabria (Italy) include increased accuracy in agricultural planning, reduced resource and pesticide use, as well as increased yields and more sustainable management of natural resources.