KishanSaathi
KishanSaathi is an AI-powered agritech platform that empowers farmers with predictive insights and financial access by leveraging satellite imagery, historical data, and Facebook’s Prophet model.
视频
描述
KishanSaathi is a full-stack agritech platform developed to revolutionize the way Indian farmers access predictive insights and financial services. By combining satellite-based geospatial intelligence, historical agricultural data, and advanced forecasting models like Facebook’s Prophet, KishanSaathi provides farmers with tailored recommendations and financial empowerment—all through a secure digital ecosystem.
At the core of the platform lies a Climate Score—a novel alternative to the traditional CIBIL Score. Recognizing that farmers often lack formal credit histories, the Climate Score evaluates agro-climatic performance metrics to assess creditworthiness. It factors in:
Crop health indices (e.g., NDVI, EVI from Landsat & Sentinel imagery)
Rainfall consistency and anomalies over cropping seasons
Yield stability across previous years
Local climate risk factors such as drought/flood zones
Soil moisture levels, temperature deviations, and pest risk assessments
This score enables banks, NBFCs, and microfinance institutions to make data-backed lending decisions, empowering climate-resilient financial inclusion.
The Prophet model by Facebook is used to forecast key agricultural indicators, including:
Future yield estimates based on seasonal patterns and climate regressors
Weather predictions tailored to specific geolocations
Market price trends for commodities to help farmers time their sales
Water requirement forecasts based on evapotranspiration and crop cycles
The system is powered by a secure backend with JWT-based authentication, ensuring user-level data privacy while enabling scalable interactions among farmers, agronomists, and financial entities.
In addition, KishanSaathi provides a suite of embedded financial tools, including:
Access to climate-linked microloans
Crop insurance eligibility based on forecasted risks
Tracking of government subsidies and payouts
By merging remote sensing, machine learning, and fintech innovation, KishanSaathi redefines agri-credit systems for the underserved, building climate-resilient rural economies and reducing dependency on outdated credit metrics.
本次黑客松进展
Day 1: Ideation & Architecture Planning Completed problem statement: Climate intelligence based data-driven farming & credit scoring User personas defined: small/marginal farmers, financial institutions System architecture sketched out: Frontend (React) Backend (Node.js + Express, JWT-based Auth) Data Layer (PostgreSQL + Remote Sensing Datasets) ML Layer (Facebook Prophet) Day 2: Core Development Added Landsat & Sentinel API access for vegetation index and land cover data Preprocessed historical crop yield and climate dataset Implemented Prophet-based time-series forecasting for: Rainfall Yield prediction Market trends Day 3: Feature Implementation & Testing Built Climate Score engine to replace legacy CIBIL scores with: Vegetation health (NDVI) Rainfall anomalies Yield stability Secured backend with JWT-based authentication Deployed dashboard for: Forecast visualization Credit eligibility Crop advisory Day 4: Final Touches & Demo Preparation Integrated financial services module (microloans, insurance, subsidy tracking) Completed end-to-end testing of workflows (user registration → Climate Score → loan eligibility) Designed and practiced live demo & pitch
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融资状态
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