Attendees at the course outside the School of Agricultural Engineers (ETSIA) of the University of Seville.
On April 2, 2024, the “Crop Prediction Using Artificial Intelligence” course was held at the Escuela Técnica Superior de Ingeniería Agronómica of the University of Seville. The event brought together technicians, freelancers, and leaders of SMEs on the university campus, where they could interact with the most advanced machine learning tools available on the market in a real-world setting.
This course, organized by Smart Biosystems Laboratory (SBL) research group, represents a top-tier initiative supported by the University of Seville, Andalucía Agrotech (Digital Innovation HUB), and the European Digital Innovation HUBs Network (EDIH). To impart new skills to foster innovation and excellence in the agricultural sector, this collaboration provides a training service for the Andalusian agricultural sector to develop skills and knowledge in artificial intelligence. It is also important to highlight that the course received financial support from the European Union and the Ministry of Agriculture, Fisheries, Water, and Rural Development of the Junta de Andalucía, thus demonstrating the commitment of both institutions to promoting technological advancement and continuous improvement in the agri-food sector.
During the workshop, participants practically experienced the creation of predictive models tailored to their specific needs. From estimating harvests to anticipating disease detection, this marked a further step towards intelligent and sustainable crop protection. In the workshop, participants explored various crops, such as berries and citrus, that were familiar to their companies. Together, they conducted a practical exercise in image analysis using photos they had taken with their mobile phones at the ETSIA‘s Future Farm.
The 18 attendees were asked to evaluate various aspects of the course: the extent to which their expectations were met scored an 8.2 out of 10; the relevance and timeliness of the topic reached a 9.7; the applicability to their professional activities was rated 8.9; and the quality of the teaching staff was rated an outstanding 9.4 out of 10. We thank all participants for their active contribution and look forward to continuing to provide opportunities for learning and collaboration.
For more information about Smart Biosystems Laboratory‘s activities and projects, please visit our website and follow us on our social networks (Twitter or LinkedIn).