ai4crophealth

More About AI4CROPHEALTH

AI4CROPHEALTH project developed an innovative application for crop disease detection, prediction, and management
recommendations using emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML). It focuses on four
core objectives: (1) Develop and implement AI/ML models that detect and classify plant diseases through image processing; (2)
Integrate AI/ML models with weather data to predict disease occurrence; (3) Conduct a pilot study to evaluate the system’s
effectiveness in real-world conditions; and (4) Promote capacity building and advocate for the adoption of AI-based disease
monitoring to ensure sustainability. The central hypothesis is that efficient disease detection, prediction, and timely dissemination
of actionable information to farmers and extension workers can enhance the adoption of Good Agricultural Practices (GAPs),
leading to improved crop yields, which in return contributes to food security.
The proposed innovation has potential for addressing the need of extensive field scouting, minimizing pesticide use and costs,
and improves crop protection through predictive insights driven by weather data. Read More ...

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