Team: Sónia Semedo, Olavo Teixeira, Anaxímeno Brito
Pests and diseases have been causing significant damage to agricultural crops in Cape Verde, leading to losses for farmers and threatening food security. The use of artificial intelligence (AI) for pest detection in Cape Verde’s agriculture sector could greatly benefit the country. Precision agriculture techniques, combined with AI, can help monitor crop growth, detect potential pests, and alert farmers in a timely manner. However, the lack of a comprehensive database on crops and pests in Cape Verde poses a challenge for implementing AI-based solutions.
Project objetive
The aim of this project is to identify Spodoptera frugiperda and Nezara pests on plant leaves in crops in Cape Verde using Artificial Intelligence models. Based on the Deep Learning model, using Convolutional Neural Network(CNN) as a method to detect the pests.
Sponsor by: IDRC and Sida
Managed by:
