MOTIA3: Technical report WP5 activities

Image analysis using artificial intelligence (AI) to detect and classify insects in static images is an innovative tool with key applications in pest control. Its use enables more efficient early detection, reducing time and costs, minimizing pesticide use, and optimizing response to agricultural threats. This approach also improves the monitoring of programs such as the Sterile Insect Technique (SIT), traditionally carried out manually, increasing the productivity and reach of these initiatives. Under the Work Package (WP5) of the MoTIA3 project, ITI has developed collaborative solutions with several institutions. With TRAGSA, an AI model was trained to analyze mosquito egg traps and design traps with geometric patterns that facilitate their reconstruction from images. Together with COARVAL, we worked on the detection of whitefly pests in citrus and persimmon crops, automating a previously manual process. In collaboration with IVIA, we sought to automate the analysis of images captured by intelligent insect traps. These initiatives highlight the potential of AI to optimize resources, increase precision and improve sustainability in integrated pest management.