AGRICULTURE: VARIMAX CASE STUDY

Sectors: Agriculture (Spraying Technology)
Development Model: Waterfall
Languages: Python

Technologies and Tools: AWS Elastic Beanstalk, Python, R, Flask, Sentinel, GDAL, Landsat 8

Background

VariMax is a start-up based out of Palmer, Kansas.

A group of researchers from Kansas State University developed an algorithm to produce nitrogen recommendations that produce high crop yield for growers based on satellite imagery. They started out using drones to prove the algorithm but then found a way to take it to a large scale market by leveraging satellite imagery.

 

Challenges/Successes/Lessons Learned:

Geospatial Data Abstraction Library (GDAL) tool was not trivial to set up like other 3rd party libraries. We could not install it on an Elastic beanstalk instance as we did with the sentinel image downloader. The only way we could get GDAL to run in a timely manner was to create a dedicated EC2 instance and install GDAL via Conda-forge (mini-conda, anaconda).

 

Team Composition:

One developer/architect/PM.

Responsibilities:

Genova was responsible for performing the following tasks:

Develop a cloud application
Create AWS infrastructure

 

Technologies:

AWS: Elastic Beanstalk, EC2, SES, SQS
Sentinel (Satellite Imagery vendor)
GDAL
Flask/Python

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