Innovation

MANIFESTO pioneers Cyprus’ first AI-powered early detection system for Asian Citrus Psyllid (ACP), combining three groundbreaking innovations: (1) A dedicated deep learning model trained on a first-of-its-kind ACP benchmark dataset; (2) Smart trap technology integrating all-weather cameras with wireless alert systems; and (3) Causal Machine Learning to decode environmental drivers of pest outbreaks. This ecosystem-based approach replaces conventional pesticide-heavy methods with precise, data-driven interventions, while establishing new methodologies at the intersection of entomology and AI. The project’s explainable AI framework and open-access research outputs create transferable knowledge for Mediterranean agriculture

KEY

INNOVATIONS

First Cyprus-specific ACP
dataset

AI training

Explainable AI + Causal ML to decode pest-environment relationship

Decode pest-environment relationships

Ecosystem-based approach

Replacing chemical-intensive methods

NOVELTY

ASPECTS

Integrates Remote Sensing + IoT traps

Addresses SDG 2 (Food Security) and SDG 15 (Biodiversity)

Complies with EU Taxonomy Regulation's "Do No Significant Harm" principle