Inspiration
Farmers often notice issues in crops but don’t always know what action to take immediately. That delay can lead to reduced yield and unnecessary loss. FieldSense was built to provide quick, practical guidance from something as simple as an image.
What it does
FieldSense analyzes a crop image and provides three key outputs:
A possible disease or issue A recommended action A warning about potential impact
It helps users move from uncertainty to immediate decision-making without needing expert knowledge.
How we built it
FieldSense analyzes a crop image and provides three key outputs:
A possible disease or issue A recommended action A warning about potential impact
It helps users move from uncertainty to immediate decision-making without needing expert knowledge.
Challenges we ran into
One major challenge was ensuring stable and consistent responses while handling different types of images.
We also faced issues with API setup, environment configuration, and deployment during development.
Accomplishments that we're proud of
- Built a fully working end-to-end system
- Designed a clean and intuitive UI
- Delivered structured outputs that are easy to understand and act upon
* Successfully created a working demo under hackathon constraint
What we learned
We gained hands-on experience with API integration, debugging real-world issues, and structuring a project for clarity and usability.
We also learned how important presentation and simplicity are in making a product effective.
What's next for FieldSense
- Improve accuracy with better datasets
- Support more crop types and conditions
- Add offline-friendly capabilities for rural areas
* Expand into a more complete decision-support system for farmers
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Built With
- css
- fastapi
- html5
- javascript
- python
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