Leveraging Machine Learning in Scalability of Precision Agriculture and Variable Rate Technologies

This project aims to enhance smart farming by improving the scalability and accuracy of two commercial products, SWAT CAM and SWAT MAPS, owned by Croptimistic Technologies Inc. These products are used for precision mapping on over three million acres of land across four countries. The project will utilize machine learning to identify crop parameters such as plant count and row counts, which can improve future agronomic recommendations. Additionally, it will enhance the accuracy of electrical conductivity (EC) maps by detecting and correcting erroneous data, often compromised by external factors. This initiative promises to extend the knowledge base in agricultural technology and machine learning applications, aligning with the interests of both the academic community and industry partners.

Faculty Supervisor:

Aitazaz Farooque

Student:

Partner:

Croptimistic Technology Inc

Discipline:

Engineering

Sector:

Agriculture; Professional, scientific and technical services

University:

University of Prince Edward Island

Program: