A mobile application that uses artificial intelligence and computer vision to detect foliar diseases in potato crops, providing on-device diagnoses and digital tools that support farmers in the field.
The problem
Early identification of foliar diseases often requires specialist knowledge that is not readily available in the field. Farmers need a fast, accessible tool that remains useful when connectivity is limited.
The solution
CultivoScan uses optimized object-detection models to identify early blight, late blight, Septoria and healthy leaves.
Inference runs locally with TensorFlow Lite, delivering results directly on the device.
Camera or image diagnosis
On-device inference
My role and responsibilities
Mobile & AI
Mobile product design and development.
Training, evaluation and optimization of computer-vision models.
Firebase, storage and on-device inference integration.
