Cloud based Machine learning algorithms on archived satellite/raster Imagery datasets

The proposed research work will be a breakthrough in the emerging data engineering field, especially in satellite data management, Machine learning algorithms, quality and quantitative analytics. The machine learning platform quickly scans vast archives of satellite images and delivers usable insights to decision makers. After processing of raster images, the data will be readily available to farmers sooner than any government or commercial desktop software or email delivery system, therefore assisting in making critical decisions early on, and reducing chances of crop failure
This project will make Beriqo a leader in Canadian Agriculture tech industry. The precision agriculture is fast growing space with expected market size of 6.43 billion [15] by 2022. Also, completion of this project results more job creation, putting Canada on the top of innovative chart, help Canadian farm operators save millions in farm operating cost, and decrease emission of nitrogen oxide (a green house gas) .

Faculty Supervisor:

Mirza Beg

Student:

Gurman Thind

Partner:

Beriqo

Discipline:

Engineering - other

Sector:

Alternative energy

University:

Program: