Using Internet of Things (IOT) waste bin sensors to analyze the effectiveness of using dynamic routing for waste collection vehicles - BC-390

Preferred Disciplines: Geographic Information Systems (GIS), Geography, Computer Science (Masters, PhD, Post-Doc)
Project length: 4-6 months (1 unit)
Approx. start date: September 2018
Location: Richmond, BC
No. of Positions: 1
Preferences: None
Company: RecycleSmart

About Company:

Founded in 2008, RecycleSmart is a leading provider of smart waste and recycling management services in Canada. Taking a 360 degree approach, RecycleSmart is the single source for companies who want to maximize cost reduction, increase waste diversion and streamline daily operations. With over 20 years of industry expertise, the company has built trusted relationships with waste haulers, and deploys cutting edge technology and analytics to reduce recycling/waste expenses for commercial customers. Customers include Fortune 500 companies in the manufacturing, hospitality, retail and property management industries.

Summary of Project:

RecycleSmart provides smart waste and recycling management services to businesses across Canada. Being smart about waste and recycling pickups means not collecting bins that are not at least 90% full. Using IOT sensors to collect real time data about container fill levels is one part of the smart waste challenge, being able to efficiently service the full containers is another challenge. The industry typically operates on a static route model based on days of the week, the unkown is if a dynamic “just in time” system could be developed for this industry.

  • Is dynamic routing more efficient (time and financial criteria) than preset scheduled routes?
  • As waste bin fill levels fill change during the day can a dynamic routing system adjust to ensure that bins don’t overflow while maintaining efficiency of the routing system?
  • The project will seek to provide the foundation for an operational pilot using test vehicles to further validate the analysis produced during this project.

Background and required skills

Research Objectives/Sub-Objectives:

  • Can IOT enabled waste bins provide data that can be used to dynamically route collection vehicles in a commercial waste collection environment?
  • If dynamic routing is proven to be more efficient what are some of the quantifiable reductions in cost, truck trips, CO2, etc.

Methodology:

    • TBD

    Expertise and Skills Needed:

    • GIS related skills
    • Multispatial data analysis skills to combine time, cost, capacity and additional operational constraints into analysis.

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