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Use Case
Industry, Innovation And Infrastructure
Sustainable Cities And Communities
Zaragoza’s escalating traffic congestion, rising CO₂ emissions, and inefficient last-mile deliveries underscored the urgent need for a transformative urban logistics solution. The project was initiated to address these challenges by harnessing AI and machine learning to develop an adaptable, citizen-centred tool to improve access to micro-hubs and parcel lockers.
The goal of the project was to determine optimal micro-hub and parcel locker locations, refining the logistics network to lower emissions, reduce congestion, revitalize local businesses, and enhance service efficiency for citizens. By integrating diverse urban data and applying Social Sciences and Humanities (SSH) models to urban planning and spatial analysis, the project aimed to not only streamline logistics but also to enhance the overall urban experience.
This approach sets the stage for a replicable, accessible, inclusive, and human-centred urban logistics system that other cities can adopt in their pursuit of sustainability, in line with the progressive principles of the NEB project.
The project was developed under the framework of Horizon 2020 Senator (GA no:861540) and the results are stored in the public deliverable D5.2. Pilot Cases Environmental Assessment and Guidelines for replication
To tackle the Challenge of determining optimal micro-hub location, we devised a structured approach that smartly combined data analysis with innovative AI solutions:
Want to learn more about the lessons learned, financial details and results?
Log inPlanning time: Less than 6 months
Implementation time: Less than 6 months
Zaragoza City of Knowledge Foundation
BABLE
City Planners, Urban Planners