Researchers: Faisal Shennib,  Ursula Eicker, Ketra Schmitt, and Nizar Bouguila

Highlights:

• This research examines how advances in data mining, big data, remote sensor technology, and machine learning algorithms can be applied to improving waste management and circular economy activities at local scales.
  
• A survey of current data applications for circular economy will be followed by practical research in living laboratory settings at district and city levels at institutions like Concordia University, public spaces in the city, or municipal waste management contexts.
  
• The waste problem requires going beyond an engineering perspective to understand issues of behavioral psychology, design, policy, and how technological, infrastructural and educational initiatives can be limited or bolstered by these factors.
• This project will involve the following:
  • Developing computer vision algorithms for smart waste bins and a mobile app to feedback waste sorting instructions to users
  • Data mining to build a recommender system for users of a material reuse center
  • Optimizing waste bin placement using occupant and pedestrian sensors and waste bin fill-level sensors