Conference Agenda

Digital agriculture has significantly enhanced productive efficiency through the intensive use of technologies such as the Internet of Things (IoT), Big Data, artificial intelligence, and cyber-physical systems; however, its increasing energy demand poses substantial environmental challenges. This paper examines the role of Green Computing as a technological cornerstone for the development of sustainable digital agriculture, aimed at reducing energy consumption and carbon footprint without compromising productivity. The adopted methodology consists of an analytical and systematic review of recent scientific literature, complemented by the examination of documented case studies and a comparative analysis of green technologies applied to the agricultural sector. The findings indicate that the integration of edge and fog computing architectures, Green Machine Learning algorithms, low-power IoT sensors, and renewable energy sources enables significant reductions in water use, agricultural inputs, and fossil energy consumption, achieving decreases of up to 80% in conventional energy use and productivity improvements ranging from 10% to 30%. The study concludes that the adoption of green computing principles represents a critical strategy for ensuring environmental sustainability, operational resilience, and the long-term viability of digital agriculture, while aligning with the Sustainable Development Goals and addressing the challenges posed by climate change.