Trash Is Cash: Applying machine learning to optimize the utilization of crop and forest residues in rural communities

Around 4 billion tonnes per year of crop and forest residues (biomass) are burned in open air, because they are often loose, wet, bulky, and too expensive to collect and centralize for subsequent conversion into useful products. This results in air pollution, and in some cases, exacerbated wildfires. In this project, we are applying machine learning and optimization techniques to coordinate a new class of small-scale, low-cost, decentralized bioconversion systems capable of rural, decentralized deployment. This opens up the possibility of a fleet of roaming biomass conversion systems supporting localized waste-to-value conversion in rural, hard-to-access (and sometimes off-grid) communities, such that these communities are self-sufficient without being reliant on vulnerable international supply chains for their key commodities/chemicals.

Faculty Supervisor:

Yankai Cao

Student:

Partner:

Takachar

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

The University of British Columbia

Program: