Skip to main content
Smart Cities Marketplace
Scalable cities

RAPTOR

RAPTOR Smart Data Collection

EIT Urban Mobility logo

Details

Duration
to
Status
Finished
Total costs
€30,000
Project type
EIT urban mobility project
Funding programme
EIT Urban Mobility
Smart City Theme

Description

Rapid Applications for Transport (RAPTOR) is a competition that swiftly creates and tests solutions to niche urban mobility challenges. Participants compete to provide the most innovative, feasible, and impactful solutions. RAPTOR is funded by EIT Urban Mobility, an initiative of the European Institute of Innovation and Technology (EIT), a body of the European Union.

The challlenge

Cunit is a coastal city 50 km southwest of Barcelona home to around 8,000 inhabitants. During the peak holiday season, however, the population can increase up to 50,000. Cunit has a network of over 1,200 kilometres of roads. Currently, the Municipality of Cunit is using an outdated geographic information system (GIS), a web map comprised of different data layers, developed by a third party. It is necessary to modernise the GIS so that it incorporates the inventory of road elements such as pedestrian crossings, traffic signs, traffic lights, etc. and is easily updatable. A solution was sought to meet the following objective: Optimization of data collection, analysis, and maintenance of road elements.

The solution

SIMOB uses lightweight, low-cost devices on-board of commercial fleet vehicles (i.e. municipal maintenance vehicles) that are programmed to automatically collect video and data from the streets with the established frequency (i.e. bi-weekly for the whole city, daily for road works areas) and send them to the cloud.

The solution builds on three key elements:

  • On-board equipment, with sensors and cameras, are installed in vehicles that circulate normally on streets and highways, to collect data and video of the places to be monitored.
  • Cloud services that automatically detect, classify and analyse traffic signs, road markings, pavement irregularities and protections, applying Artificial Vision and Data Analytics.
  • Web application that displays information with high added value for end users. Our application can be connected through an API to Smart City platforms or traffic platforms and the information can be mixed with other sources of information.

Impacts

Over the course of three months, the pilot yielded:

  • 144 km monitored.
  • 4 police patrol vehicles involved.
  • 20,502 pavement irregularities detected.
  • 3,636 signs detected and recorded.

Stakeholders involved

Map

Project demonstration sites