Data-Driven Urban Freight Management

⚙️ Operational Efficiency
📍 Metropolitan Area of Barcelona, Spain

About

Status:

✅ Finalized

🗓️ Start: 2026-03-24

🗓️ End: 2026-03-25
Managing urban freight in dense areas like the Metropolitan Area of Barcelona (AMB) is complex due to fragmented data and a lack of unified monitoring tools. The EyeDecide challenge addresses this by transforming raw data from the SPRO logistics app into actionable insights via an integrated AI platform. It enables the AMB to monitor freight activities, detect illegal parking, and forecast parking availability across nine municipalities. This data-driven approach optimizes logistics operations, reduces traffic congestion, and supports more sustainable urban mobility.

Description of the Challenge

Urban freight operations are essential for city economies but contribute significantly to traffic congestion and environmental impact. Efficient logistics management is crucial for creating more liveable urban spaces and reducing the carbon footprint of transportation.

The Metropolitan Area of Barcelona (AMB) manages a complex network of municipalities. Within the framework of the RAPTOR (Rapid Applications for Transport) project, the city sought to leverage existing data from its freight management applications to improve urban mobility and operational transparency.

Specific problem

How the challenge manifests: The AMB faces difficulties in effectively utilizing the large volumes of data collected by the SPRO app (an application dedicated to urban freight transportation). There is a lack of integrated tools to visualize freight activities, monitor vehicle circulation, and identify critical issues like parking shortages or illegal parking in real-time.

Who is affected: Logistics professionals (facing delays), city councilors (lacking data for planning), and citizens (impacted by traffic congestion and poorly managed public spaces).

Current situation and gap

Current situation: The city collects data via the SPRO app, but this data is often siloed or requires manual processing to be useful.

The Gap: There is no holistic data management platform capable of collecting, processing, and analyzing this data automatically. The city lacks a user-friendly visualization tool that allows different stakeholders to see the “big picture” of freight operations or to forecast future parking needs based on historical patterns.

Expected Outcomes

The AMB needs a comprehensive tool to unify freight data (historical and real-time), detect potential malfunctions in parking spots (e.g., illegal usage), and evaluate the effectiveness of new parking facilities.

Expected outcome

  • Desired solution: A holistic three-tier system: Kentyou Data Hub (integration), Kentyou AI (analytics/forecasting), and Kentyou Eye (visualization).
  • Functional expectations: The tool must provide customizable dashboards, interactive charts, and map-based views to compare logistics statistics across different municipalities. It must also include an AI-based forecasting solution for parking space availability.
  • Expected impact:
    • Economic: Minimized delays and reduced operational costs for logistics.
    • Environmental: Contribution to reducing traffic congestion and emissions.
    • Operational: Better-informed decision-making for city planners regarding the extension of parking networks.

Space for Solutions and Experimentation

  • Available experimentation space: The Metropolitan Area of Barcelona (AMB), specifically covering 9 municipalities (e.g., Badalona).
  • Scale of experimentation: Metropolitan and municipal (parking section level).
  • Available data/tools: Anonymized SPRO application datasets (e.g., historical data from Dec 2021 to Jan 2023). Monthly updates of real-world freight data.
  • Existing experience: The pilot followed a 5-month implementation cycle (Aug–Dec 2023) using a “lean startup” and “design thinking” methodology. It successfully moved from raw data integration to a validated proof-of-concept with authenticated access for city staff.

The Pilot

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