Diogo Paulo

The InovFarmer.MED proposal focus on PRIMA's Thematic Area 3 – Sustainable Mediterranean agro-food value chain for regional and local development, addressing specifically the topic 2.3.1 "Increasing the resilience of smallscale farms to global challenges and COVID-like crisis by using adapted technologies, smart agri-food supply chain and crisis management tools".

Knowing that environmental and social changes are deeply affecting Euro Mediterranean agro-food systems, and that COVID-19 outbreak imposing restrictions on movement, has demonstrated the fragility of the Mediterranean food systems, already distressed by climate change, population growth and scarcity of resources, the InovFarmer.MED consortium has developed a empowerment strategy addressing vulnerabilities of the producers in particular, smallholder farmers, to establish lines of resilience to face these challenges.

InovFarmer.MED will address, as case-study, the value-chains of two traditional agrifood products with high potential economic relevance and social significance for small-scale farmers of Mediterranean basin: fig (Ficus carica) and prickly pear (Opuntia ficus indica).

This research project is a collaboration between University of Beira Interior and Evox Technologies, where I'm working as a research fellow under a scholarship program. The main goal is to develop an advanced AI system capable of detecting and segmenting overflowing waste from containers in urban environments.

The project involves:

• Development of deep learning models for waste object detection and segmentation
• Creation of custom datasets for training and validation
• Implementation of computer vision algorithms for real-time analysis
• Integration with existing waste management systems

This work directly contributes to my Master's thesis research on "Detection of Bin Overflow or Parasitic Waste on Streets," supervised by Professor João Neves, combining academic research with practical industry applications in smart city development.