BerryNet Computer Vision Project

Here are a few use cases for this project:

1. Agricultural Analysis and Monitoring: BerryNet can be used by farmers, agricultural researchers, and agricultural technology companies to monitor cranberry growth, health, and ripeness levels, enabling informed decisions about optimal harvesting times and disease prevention.

2. Food Safety Inspection and Quality Control: Food processing plants and regulatory agencies can utilize BerryNet to ensure cranberries being sold or used for food products meet quality and safety standards, by identifying and flagging any unhealthy or contaminated berries during the inspection process.

3. Biodiversity and Ecological Surveys: Ecologists and conservationists can employ BerryNet to study and monitor cranberry habitats, helping to evaluate plant populations, track seasonal variations, and assess the impact of environmental factors or human activities on these ecosystems.

4. Commercial Harvesting and Sorting: BerryNet can be integrated into automated harvesting and sorting systems, enabling more efficient and accurate picking of ripe cranberries, as well as reducing wasted resources and supporting sustainable agricultural practices.

5. Consumer Applications: BerryNet can be used in mobile applications or as an educational tool for hobbyist gardeners, foragers, or nature enthusiasts, to assist with identifying and learning about various cranberry species and their growth stages.