FarmInsight

Inspiration

Despite having rich potential in Animal husbandry, Nepal has failed to meet them due to non-optimal farming practices rooted in conventional methods.

What it does

FarmInvest provides an intuitive and localized platform for management of animal farms, small and big. It helps farmers to optimize the yield by providing scientific calculations that follow the standards set by Food and Agriculture Organization (FAO) and United States Department of Agriculture (USDA)

How we built it

We have used NextJS for the Frontend and Backend. MongoDB is used as the Database for ease of use and efficient querying. We have used Cattle DMI Calculation algorithm by USDA and Selective Breeding Coefficient Calculation derived from Formulae provided by FAO.

Challenges we ran into

1. Unavailability of Datasets for ML Model Training
2. Inadequate researches in Nepal for reference

Accomplishments that we're proud of

1. Bridging the gap between agriculture and technology
2. Providing a platform suitable for both rural and industrial farmers.
3. Introducing Standard Practices accepted Internationally to Nepali Farmers.

What we learned

1. The ground reality of animal farms in Nepal.
2. Untapped potential of yields in Nepali farms.
3. Nepal is lacking in terms of data collection and analytics.

What's next for FarmInsight

We plan to shift to ReactJS(Web), React Native(App), Express and PostgreSQL as this project scales with additional features like Spatial Data of cattle movement and FastAPI, Scikit-Learn, Tensorflow for Machine Learning to train models for feed calculation and selective breeding. We also plan to store anonymized data for further research and machine learning models, without violating user's privacy.

Built With

• mongodb
• nextjs