Challenge:
Route planner for identification of vessels and containers for waste on the island of Brač
GreenPath AI Navigator: AI-Driven Waste Collection Optimization for Brač Island
Summary
4colors Research proposes GreenPath AI Navigator, an intelligent waste collection management system designed for the specific needs of Brač Island. The solution combines real-time monitoring of container fullness, AI-driven route optimization, and stochastic predictive modeling to maximize efficiency, reduce operational costs, and significantly lower environmental impacts. By ensuring only bins that need emptying are serviced, and by predicting optimal collection times, the system will save fuel, reduce emissions, and optimize resource allocation.
Foreseen impact
GreenPath AI Navigator is designed to deliver broad and measurable improvements in operational efficiency, cost savings, and environmental impact. Its intelligent routing and data-driven planning approach will lead to the following outcomes:
* Fuel Consumption Reduction: By avoiding unnecessary trips to containers that do not require emptying, fuel use is expected to decrease substantially, improving cost-efficiency and reducing environmental strain.
* Lower Vehicle Emissions: Fewer kilometers traveled means fewer emissions. This directly supports Brač’s sustainability objectives and aligns with broader EU decarbonization targets.
* Operational Cost Savings: Optimized routes will reduce costs related to fuel, vehicle wear and tear, and staffing — especially important during the high-demand tourist season.
* Resource Optimization: Only bins that actually require collection will be serviced. This reduces wear on vehicles, limits labor waste, and avoids unnecessary service actions.
* Improved Service Performance: The system will reduce the likelihood of overflow or missed collections, contributing to a cleaner environment and higher community satisfaction.
* Predictive Efficiency: Stochastic models will help predict bin usage patterns over time, enabling smart decisions about whether to empty a bin immediately or wait for the next cycle — balancing responsiveness and efficiency.
* Easier Driver Onboarding: Intelligent route guidance and intuitive user interfaces will simplify navigation for seasonal or new drivers, significantly reducing training and ramp-up time.
In sum, GreenPath AI Navigator ensures that every route, trip, and action is purposeful — making better use of available resources while supporting environmental, economic, and service quality goals.
* Fuel Consumption Reduction: By avoiding unnecessary trips to containers that do not require emptying, fuel use is expected to decrease substantially, improving cost-efficiency and reducing environmental strain.
* Lower Vehicle Emissions: Fewer kilometers traveled means fewer emissions. This directly supports Brač’s sustainability objectives and aligns with broader EU decarbonization targets.
* Operational Cost Savings: Optimized routes will reduce costs related to fuel, vehicle wear and tear, and staffing — especially important during the high-demand tourist season.
* Resource Optimization: Only bins that actually require collection will be serviced. This reduces wear on vehicles, limits labor waste, and avoids unnecessary service actions.
* Improved Service Performance: The system will reduce the likelihood of overflow or missed collections, contributing to a cleaner environment and higher community satisfaction.
* Predictive Efficiency: Stochastic models will help predict bin usage patterns over time, enabling smart decisions about whether to empty a bin immediately or wait for the next cycle — balancing responsiveness and efficiency.
* Easier Driver Onboarding: Intelligent route guidance and intuitive user interfaces will simplify navigation for seasonal or new drivers, significantly reducing training and ramp-up time.
In sum, GreenPath AI Navigator ensures that every route, trip, and action is purposeful — making better use of available resources while supporting environmental, economic, and service quality goals.
About the solver
4colors Research is a Cambridge-based R&D consulting firm specializing in data-driven optimization solutions. With a focus on mathematical and computational techniques, the company has successfully tackled complex challenges across various industries, including logistics, manufacturing, and defense. Notably, 4colors Research was recently recognized for its innovative approach in the Airbus-BMW Logistics Optimization Challenge, highlighting its capability to deliver cutting-edge solutions.
For more information, please visit: www.4colors-research.com
For more information, please visit: www.4colors-research.com
Indicative budget/Phases
Phase 1: System Assessment and Data Collection
We begin with an in-depth analysis of the current waste collection system on Brač, focusing on bin identification infrastructure, vehicle routes, operational schedules, and collection data (where available). Key activities include field mapping of bins and routes, hardware compatibility checks (e.g., RFID readers), and collection of baseline performance metrics.
Estimated duration: 2 months
Budget: €50000
Phase 2: Algorithm and Platform Development
Using data from Phase 1, we will design and develop the GreenPath AI Navigator platform. This includes building the core route optimization engine using stochastic modeling and heuristics, integrating vehicle GPS tracking, and simulating various operational scenarios. Prototypes of the mobile app and driver interface will also be developed.
Estimated duration: 3 months
Budget: €85,000
Phase 3: Pilot Deployment and Iterative Testing
The solution will be deployed in a selected pilot area (approx. 300 collection points) across multiple municipalities. This phase includes field testing of the platform, calibration of algorithms in real-world conditions, driver onboarding, and feedback collection. Technical improvements will be applied iteratively based on operational feedback and performance analytics.
Estimated duration: 3 months
Budget: €85,000
Phase 4: Full Rollout, Support, and Continuous Optimization
Following the pilot, we expand to all 1200+ locations. This phase includes final deployment of the platform and navigation tools, vehicle tracking integration, user training across the island, and the start of full operations. Ongoing technical support, model refinements, system updates, and performance monitoring will be provided for the duration of the contract.
Estimated duration: 2 months
Budget: €50,000
Total Estimated Budget: €270,000
We begin with an in-depth analysis of the current waste collection system on Brač, focusing on bin identification infrastructure, vehicle routes, operational schedules, and collection data (where available). Key activities include field mapping of bins and routes, hardware compatibility checks (e.g., RFID readers), and collection of baseline performance metrics.
Estimated duration: 2 months
Budget: €50000
Phase 2: Algorithm and Platform Development
Using data from Phase 1, we will design and develop the GreenPath AI Navigator platform. This includes building the core route optimization engine using stochastic modeling and heuristics, integrating vehicle GPS tracking, and simulating various operational scenarios. Prototypes of the mobile app and driver interface will also be developed.
Estimated duration: 3 months
Budget: €85,000
Phase 3: Pilot Deployment and Iterative Testing
The solution will be deployed in a selected pilot area (approx. 300 collection points) across multiple municipalities. This phase includes field testing of the platform, calibration of algorithms in real-world conditions, driver onboarding, and feedback collection. Technical improvements will be applied iteratively based on operational feedback and performance analytics.
Estimated duration: 3 months
Budget: €85,000
Phase 4: Full Rollout, Support, and Continuous Optimization
Following the pilot, we expand to all 1200+ locations. This phase includes final deployment of the platform and navigation tools, vehicle tracking integration, user training across the island, and the start of full operations. Ongoing technical support, model refinements, system updates, and performance monitoring will be provided for the duration of the contract.
Estimated duration: 2 months
Budget: €50,000
Total Estimated Budget: €270,000