Empowering Farmers and Agronomists with a Cloud Native GIS Platform for Real Time Soil, Crop, and Field Intelligence

Industry: AgriTech and Soil Intelligence 

Region: United States

Engagement: Full cycle product engineering for a next generation GIS enabled agriculture intelligence platform designed to support farmers, agronomists, and enterprise farm managers with real time insights and data driven decision making.

Technology Stack Overview

Frontend: Svelte, SvelteKit, ReactJS, AngularJS, Leaflet 

Backend: Python, Java, Node.js Database: PostgreSQL, MySQL 

AI and Analytics: Machine learning models for yield insights and soil behavior predictions 

Cloud Infrastructure: AWS, Azure, GCP 

Integrations: Weather APIs, Satellite im. agery APIs, Drone feeds, HubSpot CRM, Google Sheets 

Security and Compliance: Role based access, encrypted data pipelines, secure cloud deployment

Challenge

The client wanted to transform traditional farm management through a digital first and GIS powered platform that could unify soil data, crop intelligence, and field operations.

They faced multiple challenges

• Fragmented soil and crop data scattered across tools and manual systems 

• No centralized geospatial interface to visualize farm boundaries or field conditions

• Limited forecasting capability for yield, soil health, and irrigation patterns

• Need for real time weather, satellite, and drone insights

• Multiple stakeholders including farmers, agronomists, and enterprise managers needing custom access

• Requirement for a cloud native and scalable architecture for nationwide adoption

The objective was to build an integrated agriculture intelligence system that connects the physical world of soil and crops with the digital world of analytics and predictive insights.

Solution

EC Infosolutions engineered a comprehensive GIS powered agriculture intelligence platform that connects field mapping, soil analytics, crop insights, and farm operations into a unified digital ecosystem.

Key Functional Modules

1. Multi Layer GIS Field Mapping

• Interactive field boundary creation with Leaflet and Svelte

• Real time updates through PostgreSQL geospatial storage

• Multi layer overlays for soil zones, irrigation patterns, and crop distribution

  
  

2. Soil and Crop Data Intelligence

• Consolidated collection of soil moisture, health, and composition data

• GREET environmental impact calculator for emission insights

• Weather and irrigation data integration for daily decision support

• Satellite and drone imagery feeds for remote monitoring

3. Farm Operations and Crop Management

• Activity logs for planting, fertilization, irrigation, and harvesting

• Machine learning based yield prediction models 

• Insightful reports for agronomists, managers, and field supervisors

4. Visualization and Collaboration Dashboards

• Visual dashboards built with Plotly and Chart.js

• Role based access for farmers, managers, and enterprise analysts

• Data export options including CSV, PDF, and GeoJSON

5. Workflow Automation and Integrations

• HubSpot CRM integration for automated workflows

• Google Sheets integration for GREET model calculations

• Real time alerts, notifications, and field status updates

Implementation and Delivery

Phase 1 : Discovery, GIS architecture planning, data model design, and wireframes

Phase 2 : Development of GIS mapping tools, soil intelligence module, and data pipelines

Phase 3 : Dashboard creation, analytics development, and machine learning model integration

Phase 4 : Testing, performance optimization, and cloud deployment on AWS and GCP

Phase 5 : User onboarding, documentation, and operational handover

Results

• Field mapping and data processing improved by 70 percent

• Automated geospatial intelligence increased accuracy by 50 percent

• Agronomists gained 90 percent better real time visibility for farm conditions

• Manual reporting and analysis time reduced by 60 percent

• Soil health insights improved sustainability driven decision making

• Hundreds of farms now use the platform for soil, crop, yield, and environmental management

Key Takeaways

• Centralizing soil, crop, and weather data creates a powerful decision ecosystem

• GIS combined with analytics accelerates precision farming

• Machine learning enhances forecasting accuracy and field level recommendations

• Cloud scalability ensures reliability and long term adoption

• Data driven agriculture improves sustainability and operational performance

Get Connect

Looking to modernize your agriculture operations with a unified GIS and data intelligence system.

We partner with global AgriTech innovators to build cloud native platforms that integrate soil analytics, crop forecasting, and real time field monitoring.

 Contact us to discover how we can help you scale your digital agriculture capabilities.