AI Farming Advisor

An intelligent multi-agent system for real-time, data-driven agricultural decision-making

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Inspiration

i did this project because of i saw my friend father died due to lack of knowledge about marketing conditions , weather conditions , which crop yields more and what crop will bring the profit to them , In my state(province) also 917 farmers are died ,In whole india so many farmers are attempting suicides , approximately 296,438 farmers died by suicide between 1995 and 2014 because of many factors main factors among them is they dont know which crop brings more profit , i took this one is a challenge and i want to give the better information to them via AI farmer advisor . i asked so many times why i am not able to providing solutions them , but they today i am doing..

What it does

An intelligent farming agent built with Google Agent Development Kit that provides data-driven crop recommendations, market analysis, and farming insights based on location, weather, soil conditions, and market prices.

How we built it

The system uses a multi-agent architecture with specialized agents: 1.Main Agent: Orchestrates all operations using Google ADK 2.Weather Agent: Collects and analyzes weather data 3.Soil Agent: Processes soil conditions and compatibility 4.Market Agent: Handles pricing and profit analysis 5.Data Processor: Performs calculations and rankings Language : Python I developed a simple and friendly interface using streamlit so that even a non-technical user could use it from a mobile phone or PC. All agents process live or mock data and provide: 1.Top 3 crop recommendations 2.Profit estimation

  1. Planting calendar 4Risk analysis

Challenges we ran into

  1. Accessing accurate and affordable real-time APIs
  2. Tuning the scoring algorithm for crops based on multiple parameters 3.Making the solution adaptable to multiple regions and climates
  3. Designing a UI that is simple enough for non-technical users (like small-scale farmers)

Accomplishments that we're proud of

In my childhood onwards i am listening that farmer is the backbone of the country , if i am helping to the farmers means i am helping to whole country it i will be the best proud moment for my parents and to me

What we learned

  1. How to solve real world problem using Google development kit
  2. How use different python libraries and frameworks
  3. How to build a modular, intelligent system using multi-agent architecture Integrating external APIs (weather, market data) in real-time
  4. Designing data-driven recommendation models
  5. How agriculture depends on invisible patterns — like weather, soil pH, and global prices
  6. Creating an accessible, farmer-friendly interface using streamlit ## What's next for AI Farming Advisor The current version of AI Farming Advisor v1.0 lays the foundation for data-driven agriculture. But the journey doesn’t stop here. Here's what's coming next: Planned Enhancements Mobile App Version
    • An Android app for offline usage and SMS-based interaction
    • Farmer-friendly UI with multilingual support Smart Pest & Disease Detection Agent
    • Using AI image classification (CNNs) on leaf or crop images
    • Real-time suggestions for pesticide use or organic treatments Government Schemes Integration
    • Recommending subsidies or schemes based on crop and region
    • Linking with agricultural welfare portals (India-specific) WhatsApp / SMS Bot Interface
    • Daily personalized crop tips and market alerts
    • Zero app usage, just text-based interaction Region-Aware Market Analysis
    • Real-time price predictions using local mandi/market APIs
    • Auto-adaptation to local currency and demand AI Yield Prediction
    • Predict expected yield per hectare using past data + ML models Stay tuned for v2.0 — coming soon! Thank you for reading. Let's build a world where farmers have AI on their side.

Built With

  • adk
  • commodities-api.com
  • google
  • python
  • soil
  • streamlit
  • vscode
  • weatherapi.com
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