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Focus on Road Safety 

Power Up Road Safety Schemes with Computer Vision Data and Insights

VivaCity's AI-powered computer vision solution can offer accurate data and insights to tackle this issue.

Traditional traffic monitoring is not able to gather accurate data on the most vulnerable road users - cyclists and pedestrians - making it difficult for local authorities to plan, implement and assess road safety interventions and their impact on these road user classes. 

Learn more about how our datasets support road safety schemes:

  • Classified Counts
  • Path Data
  • Near Misses
  • Zonal Speed
  • Turning Counts

These insights offer:

  • Baseline data before, during and after
  • Long-term and real-time data and insights
  • Comprehensive quantitative data to support funding applications
  • Data backed decisions and evidenced results
See how data and insights can power up and improve the success of your road safety schemes. Download our brochure now!

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Want to learn more about VivaCity?

Discover the Power of Computer Vision for
Traffic Monitoring and Signal Control by VivaCity

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At VivaCity, our vision is to make cities smarter, safer and more sustainable. Our AI sensors provide insights to local authorities to support strategy planning decisions.

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Our solution can  gather anonymous, real-time, multimodal traffic data and that is used by controller cabinet to optimise signalling, in an adaptable and efficient way, based on real-life needs.

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VivaCity was awarded the Queen’s Enterprise Award for Innovation in 2021 in the UK. Our sensors have been deployed in over 70 towns and cities across the UK, Europe and Australia.

A selection of our clients and partners:

Transport for London
TfGM - White PNG
Transport for West Midlands
Monmouthshire
Cambridgeshire County Council
City of Port Phillip - Australia
Westminster - White PNG
Vaisala
Ricardo Research - White PNG
Hackney
Cross River Partnership
WM5G
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VIVACITY

Improving traffic insights with Artificial Intelligence. Continuous 24/7 urban classification with complete anonymity