Automated Detection of the Main Pests in Cocoa Crops (Theobroma cacao L.) and Potential Natural Enemies Through Computerized Monitoring in the Dominican Republic

The project successfully developed an automated system for pest detection and moni-toring in cacao crops in the Dominican Republic, using high-resolution cameras and artificial intelligence. Results showed a significant reduction in pest incidence, with 92% accuracy in pest identification and 85% in detecting natural enemies. The system enabled a 40% reduction in pesticide use, optimizing application only in affected areas and promoting the conservation of beneficial species. Validation by ex-pert entomologists confirmed its reliability. Additionally, continuous monitoring facilitated the implementation of Integrated Pest Management (IPM) strategies, improving crop health and environmental sus-tainability. The involvement of local farmers ensured its adaptability. In conclusion, the system provides an innovative solution for precision agriculture, optimizing productivity and reducing costs.