In the heart of Spain’s agricultural innovation, a groundbreaking study published in *Sensors* is set to revolutionize how farmers manage water resources, particularly in the face of climate change. The research, led by Carlos Cambra Baseca of the Grupo de Inteligencia Computacional Aplicada (GICAP) at the Universidad de Burgos, introduces an IoT-enabled edge computing model for smart irrigation systems. This model is designed to enhance sustainability in agriculture by automating irrigation processes and optimizing water usage in almond fields.
The study focuses on precision agriculture, combining IoT sensors, hybrid machine learning algorithms, and edge computing to predict soil moisture and manage Controlled Deficit Irrigation (CDI) strategies. By gathering and analyzing meteorological, soil humidity, and crop data, the researchers have developed a soft machine learning model that enhances irrigation practices and identifies crop anomalies in real-time—without relying on cloud computing.
“This methodology has the potential to transform agricultural practices by enabling precise and efficient water management, even in remote locations with limited internet access,” Cambra Baseca explains. The model applies reductions of 35% ETc (crop evapotranspiration), a significant step toward sustainable water management in agriculture.
The implications for the agriculture sector are profound. With water scarcity becoming an increasingly pressing issue, particularly in Mediterranean regions, the ability to automate and optimize irrigation processes can lead to substantial water savings and improved crop yields. This technology is not only relevant for almond farming but also has the potential to be adapted for other crops and regions facing similar challenges.
The study represents an initial step toward implementing machine learning algorithms for irrigation CDI strategies. As the technology evolves, it could pave the way for more sophisticated and widely applicable solutions in precision agriculture. The research, published in *Sensors* and led by Carlos Cambra Baseca of the Grupo de Inteligencia Computacional Aplicada (GICAP) at the Universidad de Burgos, underscores the importance of integrating advanced technologies into agricultural practices to address the pressing challenges of climate change and water scarcity.
As the agriculture sector continues to grapple with these issues, the adoption of such innovative technologies could be a game-changer, ensuring sustainable and efficient water management for future generations.