AgroLens – AI-Powered Intelligent Farming Assistant

AI crop monitoring dashboard with satellite imagery, sensor data, and pest alerts.

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Inspiration

Farmers make high-stakes decisions about irrigation, pesticide use, and harvest timing with scattered data and intuition. I wanted to see how far I could go using only AI tools to build a complete crop intelligence dashboard, then plug it into real-world data sources. AgroLens was born from this idea: an AI-assembled, farmer-friendly cockpit for data-driven farming.

What it does

AgroLens is a web-based crop monitoring dashboard featuring:

  • Smart field map with NDVI overlay: Color-coded health visualization (dark green = excellent, light green = good, yellow = fair, red = poor)
  • Crop health score & KPIs: Central health gauge (0-100) with soil moisture, pest risk, and 30-day NDVI trends
  • Alert center: Critical/high/medium priority alerts sortable by status (active/resolved)
  • Sensors dashboard: Real-time data from virtual soil moisture, pH, temperature, humidity, light sensors
  • AI predictions panel: Pest risk analysis, yield predictions, and priority-tagged recommendations
  • Automated reports: Daily/weekly/monthly summaries with health scores, sensor stats, and alert history
  • Profile & settings: Dark mode, high-contrast field mode, data download/delete controls

How we built it (AI-only stack)

Frontend (Lovable): Generated entire React/HTML/CSS using natural language descriptions. Lovable handled UI scaffolding, theming, and component logic.

Backend (Anti-Gravity + Cursor): Anti-Gravity proposed backend architecture and data models. Cursor generated API stubs and mock data providers.

Every component and route was AI-generated and refined through prompting—no traditional manual coding.

Tech Stack

  • Frontend: Lovable (AI React/TypeScript)
  • Backend: Anti-Gravity (architecture), Cursor (code generation)
  • Hosting: GitHub Pages
  • Demo: YouTube video available

Challenges

  • Orchestrating multiple AI tools with different strengths
  • Simplifying dense dashboards for non-technical farmers
  • Simulating realistic mock data without real sensors

Accomplishments

  • Built a complete, multi-page farming dashboard using only AI tools
  • Created clear, at-a-glance views (NDVI, health score, alerts, sensors, reports)
  • Designed architecture ready for real satellite/drone/IoT integration

What's next

Real sensor integration: Connect actual IoT devices (soil moisture, pH, temperature sensors via LoRaWAN/MQTT)

Satellite & drone imagery: Replace simulated NDVI with real satellite data and compute live vegetation indices

True AI models: Integrate computer-vision models and time-series forecasting for pest detection and yield prediction using real imagery and sensor history

Farmer notifications: Add SMS/WhatsApp/voice alerts and automated irrigation recommendations

Multi-farm scalability: Enable cooperatives and agronomists to monitor many farms from a single interface

Long term: AgroLens will be a fully functional, AI-driven farming companion—farmers bring their fields and sensors, AgroLens turns raw data into clear, actionable insights.

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