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Digitizing Waste

Digitizing Waste is a collaboration between Concordia's Facilities Management and Concordia researchers and students to bring waste management and circular economy into the digital transformation age through living laboratory projects on campus.

Our projects

Waste detection app

We are designing a mobile app that uses computer vision to detect waste objects and provide instructions on the most sustainable disposal option at Concordia University (and eventually beyond).

Smart waste bins

We're collaborating with a smart waste bin company to embed their system with computer vision to detect items being disposed and provide on-the-spot sorting instructions to campus visitors.

Campus waste tracking and modeling

We're embedding campus waste bins with fill-level and weight sensors to capture waste flows and develop models to predict waste production at a community scale.

Waste invaders - waste sorting game

Designed and built by a Concordia Sustainability Ambassador, this classic arcade game has been updated to teach players the basics of waste sorting at Concordia.


The waste management industry has largely resisted the digital transformation of infrastructure that has happened more rapidly in other sectors. Waste auditing is still mostly conducted manually, while waste peformance is tracked from invoices provided by waste haulers. This means information on waste performance is expensive to retrieve, and only represents a single snapshot in time, or monthly performance.

While some companies are innovating by applying artificial intelligence and robotic sorting in waste sorting facilities, and a few smart waste bin vendors have embedded sensors and feedback into their waste bins, most waste management is still conducted using non-digitized technology. Meanwhile, the data generated from new digital waste systems has remained mostly private, limiting the potential value and learning that would be possible with open data.

Globally, the circular economy represents a trillion dollar opportunity that has yet to be realized. Lack of data on waste management performance and opportunities for diversion are often cited as key reasons for slow progress in adoption. We believe that a community-driven approach, in collaboration with industry and research, is necessary to uncover the potential of digitalisation of waste management.


Our approach is collaborative, open, and grounded in both practice and scientific method. We want to create an opportunity for all who are interested to work on an exciting and important challenge that humanity faces at a concrete scale.

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