Yield estimation on High resolution based remote sensing

YES-TECH is web-based agricultural intelligence platform that unifies farm management,insurance claims,andAI analytics to deliver actionable insights,optimizeyields,reduce risk,and boost productivity

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YES-TECH: Transforming Agricultural Intelligence with Data-Driven Insights 🌱

Inspiration

Modern agriculture generates massive volumes of data—from satellite imagery and weather patterns to yield records and insurance reports. Yet farmers and agri-insurers often struggle to translate this complex, high-resolution information into timely, practical decisions.

We were inspired by this gap. Farmers need clarity, not complexity; insights, not raw data. Our goal with YES-TECH was to bridge the divide between advanced remote sensing technologies and on-ground agricultural decision-making by creating a single, intuitive intelligence platform.

What We Built

YES-TECH is a comprehensive, web-based agricultural intelligence platform that unifies:

  • Farm management
  • Insurance claim processing
  • AI-powered analytics and yield estimation

into one centralized command center.

At its core, YES-TECH enables users to:

  • Monitor key performance indicators (KPIs)
  • Visualize farms and stress zones on geospatial maps
  • Track insurance claims end-to-end
  • Generate professional, print-ready analytical reports
  • Leverage AI-driven insights for yield prediction and risk mitigation

By combining high-resolution remote sensing data with AI models, the platform transforms raw agricultural data into clear, actionable intelligence.

How We Built It

YES-TECH was developed as a modern, scalable web platform using industry-leading technologies:

  • Frontend & Framework: Next.js, React
  • Styling & UX: Tailwind CSS for a clean, responsive, and accessible interface
  • Geospatial Intelligence: Satellite-derived indices aligned with farm boundaries
  • AI & Predictive Analytics: Machine learning models for yield estimation, powered by Genkit
  • Data Visualization: Interactive dashboards, charts, and maps for intuitive analysis

Our yield estimation pipeline leverages high-resolution remote sensing data to estimate productivity at the farm level. Conceptually, yield prediction can be expressed as:

[ \hat{Y} = f(NDVI_t, EVI_t, W_t, S_t, C) ]

where:

  • ( NDVI_t, EVI_t ) represent vegetation indices over time
  • ( W_t ) captures weather variables
  • ( S_t ) represents soil characteristics
  • ( C ) denotes crop type

The result is a system that is both technically robust and farmer-friendly.

Challenges We Faced

Building YES-TECH was not without its challenges:

  • Handling large geospatial datasets efficiently in a web environment
  • Accurately aligning satellite data with real-world farm boundaries
  • Ensuring model reliability across different crops, regions, and seasons
  • Simplifying complex analytics into dashboards usable by non-technical users

Balancing advanced AI capabilities with a clean, intuitive user experience was one of the most demanding—and rewarding—parts of the project.

What We Learned

Through this project, we gained several key insights:

  • Data quality and spatial resolution are critical for reliable yield estimation
  • Ground truthing and feedback loops significantly improve model performance
  • User experience matters as much as model accuracy—AI is only useful if people can understand and trust it
  • Agriculture benefits most from technology when it is integrated, contextual, and actionable

Accomplishments We’re Proud Of

  • A unified dashboard combining farms, insurance claims, and analytics
  • High-resolution, farm-level yield estimation using remote sensing
  • A streamlined insurance claim workflow with clear status tracking
  • A clean, responsive, and scalable system architecture ready for real-world deployment

What’s Next 🚀

YES-TECH is just the beginning. Our roadmap for high-resolution, remote-sensing-based yield estimation includes:

  • Multi-temporal satellite data integration
  • Weather and soil intelligence fusion
  • Crop-specific deep learning models
  • Real-time crop stress detection and alerts
  • Continuous model refinement using farmer feedback and ground data

YES-TECH is more than a platform—it’s an intelligent partner for building a more efficient, productive, and resilient agricultural future.

Built With

  • api-routes-(next.js)-ai-&-analytics:-genkit
  • frontend:-react
  • geospatial-mapping-apis-database:-postgresql-(relational-data)
  • machine-learning-models-for-yield-estimation-remote-sensing-&-gis:-high-resolution-satellite-imagery
  • map-based
  • ndvi/vegetation-indices
  • next.js
  • object-storage-for-media-cloud-&-hosting:-cloud-based-infrastructure-(scalable-compute-&-storage)-authentication-&-security:-role-based-access-control
  • secure-auth-visualization:-interactive-charts
  • tailwind-css-backend:-node.js
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