Stress Detection for Plants Grown in a Controlled Environment

Precision agriculture is the technique to replace traditional farming methods to sustainably improve crop productivity and ensure food security without adversely impacting the environment. Pure Roots Holdings Canada Inc. is managing an ecosystem that encapsulates 0.4 acres of the effective farming area into a modular grow room called AeroPod. AeroPod provides an automated, modular, mobile, and controlled indoor growing ecosystem which can be easily shipped anywhere across the globe. AeroPod makes growing virtually independent of multiple constraints like the growing season, harsh weather, large space requirements, etc. AeroPod provides systems to control environmental factors like temperature, humidity, air quality, sunlight, and water/nutrients supply. The objective of this project is to utilize computer vision and machine learning for plant stress detection. The project will add data-driven smart capabilities to AeroPod and make it more reliable, autonomous, and user friendly.

Faculty Supervisor:

Abdul Bais

Student:

Hafiz Sami Ullah

Partner:

Pure Roots Holdings Canada Inc.

Discipline:

Engineering - computer / electrical

Sector:

Agriculture

University:

University of Regina