Optimizing crop yield using Google Maps

Agricultural drainage design automation software

Solution summary: This case-study provides an overview of a custom software which we built for an agricultural drainage contractor. This software is used by farmers, geological engineers and agronomists to help design a drain-tile map. Our Client is a regional farm-drainage contractor with large scale operations in Minnesota, Iowa, North Dakota, and throughout the Midwest. 

OBJECTIVE

  • Create a map-based software that brings together the sciences of soil, topology, weather patterns and farm ownership data
  • Implement an ROI model for installing drain tile
  • Using drain-tile, determine how to maximize crop yield for corn, potato, wheat, sugar beets and several other type of crops.
  • Implement a shopping card to purchase the RIO analysis online
  • Create a mobile device interface for the software

SOLUTION

We built a software application using Microsoft’s .Net platform and DNN portal. The software was deployed on Microsoft Azure. A highly available Azure SQL Server instance was used for storing large amount of farm data. Near real-time weather information was obtained from DTN Weather, and overlaid on the map. LIDAR information was also overlaid for highly accurate topology display of the map to show the flow of was during a flooding situation. Soil properties (clay, sand etc.) was obtained from USGS and overlaid on the map as well. using web services. All this was implemented in an easy to use website for the benefit of farmers and agronomists.

Customer Website

After securely logging in, customers can select their field and obtain an ROI calculation for their field and take steps towards designing a tile-map for their field. Customer can input the crop type, select a pump-well location and factor in any easements required.

Site adminstration

Employees have a more enhanced view of the website, for user management, design interfaces, payment processing and customer support functionality.

Keywords: United Statues Geological Survey (USGA), Historical weather data, DTN weather, drain-tile, soil type, Hooghoudt’s equation, Hydraulic conductivity, DNN, Microsoft Azure, Microsoft SQL Server, Lidar, Topology