Deep Learning Techniques for Crop Monitoring

In this project, we will investigate using artificial intelligence to assist farmers and insurance companies by providing information about farms based on our daily observations. AIRM has developed monitoring stations (Crop Sentry) that are installed on multiple farms in Manitoba, allowing us to monitor the crop on a daily basis. Crop Sentry units used lidar sensors to monitor the field, and the output of these sensors is point cloud data. As a result, in this project, we will look into developing point cloud-based machine learning techniques to predict crop properties such as crop volume and yield. During this project, the interns will learn about designing and implementing AI-driven technology and will gain exposure to precision agriculture related applications. Interns will learn the steps of data preprocessing and will have the opportunity to interact with the pipeline engineers and gain a better understanding of data science process. In addition, Interns will get the opportunity to work with AWS cloud services, one of the most cutting-edge cloud computing platforms. The intern will develop important research skills and will work with a highly skilled and experienced hardware development and data science team from industry.

Faculty Supervisor:

Vahab Khoshdel

Student:

Partner:

AIRM Consulting Ltd.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program: