The Project
AGRO-WELL follows a highly interdisciplinary approach to enhance knowledge for technological transitions towards an environmentally, economically, and socially sustainable agricultural sector. It brings together leading scientists from a multitude
of OSH-related disciplines, various regions across Europe, key technology providers and farmer representatives.
The Problem
The agricultural sector is known for its demanding and hazardous working environments, leading to high rates of accidents and health issues among workers. Furthermore, drudgery due to physical work and repetitive tasks diminishes the attractiveness of the sector for youth.
Emerging challenges such as digitalization, technological intensification, structural change, environmental targets, and new risks due to climate change, coupled with global economic implications demand more and more from farmers and farm workers, exacerbate the need for timely information, and have new implications for occupational safety and health (OSH).
AGRO-WELL’s Mission
The AGRO-WELL project aims to develop and support the use of innovative smart farming technologies to improve working conditions, enhance safety, and increase sustainability in agriculture through stakeholder engagement, sustainable business models, and supportive policy recommendations.
Develop and demonstrate Artificial Intelligence (AI), Augmented Reality (AR) and sensor-based solutions for better working conditions in agriculture.
Evaluate the social, economic and environmental impacts of digital technologies farmers and rural communities.
Assess the needs of farmers and involve them in the development of solutions, ensuring they address real-world needs.
Develop sustainable business models, training materials, and effective policy recommendations to support the use of these technologies.
The Technologies
AGRO-WELL's Solutions
AGRO-WELL's innovative solutions will be showcased across four demonstration sites, representing key farming sectors: Open fields, Orchards, Pig farming and Greenhouses.
AI helps farmers make data-driven decisions, automate processes, and optimize farming practices for better yields, resource management, and sustainability. Some applications of AI in agriculture include Predictive Analytics and Forecasting, Precision Farming, Automated Machinery, Crop Monitoring and Disease Detection and Livestock Management.
AR is transforming the way farmers interact with data, machinery, and environments by overlaying digital information onto the physical world. Some applications of AR in agriculture include Field Visualization, Training and Education, Maintenance and Troubleshooting, Enhanced Crop Management and Remote Assistance.
