Optimizing Smart Trash Collection Routes

Background

Efficient waste management is critical for urban sustainability, yet traditional garbage collection approaches often waste resources through unnecessary vehicle movements and poorly timed pickups. In 2018, the City of Pittsburgh deployed approximately 1,000 smart trash bins, each equipped with sensors to report fill-levels in real-time, paving the way for data-driven waste management strategies.

Project Details

The SUDS team collaborated closely with Pittsburgh’s Department of Innovation and Performance (I&P) and the Department of Public Works (DPW) to analyze and enhance the city’s waste collection practices. By leveraging real-time data from the city’s newly deployed smart trash bins, the team aimed to:

• Identify and evaluate leading vehicle routing optimization techniques.
• Develop predictive models to forecast which trash bins would reach full capacity during daily collection cycles.
• Create optimized collection routes that integrate real-time and historical fill-level data to minimize operational costs and environmental impacts.

Deliverables

• Routing Optimization Analysis: An evaluation of existing routing algorithms and recommendations tailored specifically to Pittsburgh’s infrastructure.
• Predictive Models: Algorithms capable of accurately predicting trash bin fill levels, enabling proactive rather than reactive collection.
• GIS-based Route Mapping: Visualizations of optimized collection routes integrating real-time sensor data and historical usage patterns.
• Stakeholder Presentations: Clear communication of findings and recommendations delivered to city stakeholders for immediate implementation and future policy guidance.

Outcomes

The project significantly reduced unnecessary mileage and resource use, resulting in tangible cost savings and lower environmental impact. Moreover, the predictive capabilities facilitated smoother operations, reduced missed collections, and improved the quality of public spaces, demonstrating Pittsburgh’s leadership in smart city initiatives.