sREC Computer Vision Project

Here are a few use cases for this project:

1. Agricultural Disease Diagnosis: sREC can help agricultural experts and farmers diagnose leaf diseases in their crops early, enabling them to take preventive steps accordingly. This supports efficient disease management in fields, particularly for crops like tomato, where it can distinguish between healthy and diseased plantations.

2. Plant Care Mobile Applications: Integrating sREC into consumer-level plant care mobile apps can help users identify the health status of their home plants and take proper measures if one is detected as diseased, overall promoting better plant care.

3. Botanical Research: In botanical and agricultural research, sREC can be used to accurately categorize collected samples based on their health and disease state, thereby aiding scientists and researchers in their studies.

4. Greenhouse Automation Systems: sREC can become a crucial part of automated greenhouse or hydroponics systems, where it continuously monitors the health condition of the plants, identifying any leaf-level disease, and shares these insights with the automated system. This may result in automated optimization of greenhouse conditions to prevent disease spreading.

5. Input to AI-based Agricultural Drones: Agricultural drones equipped with cameras are becoming popular in monitoring large farms for nutrient deficiency, pest outbreaks, and disease alerts. Integrating sREC with such drones can make them capable of identifying leaf-diseases like GBNV, Early blight - Alternaria solani, improving the preventive and curative measures taken by the farmers.