Vivacity Labs

Stand J012
At Vivacity, our vision is to make cities smarter, safer and more sustainable. Our AI sensors and ‘Smart Junctions’ signal control gather detailed and anonymous data 24/7 on transport modes, traffic flow and travel patterns, supporting strategic decisions to help optimise the transport network and improve urban infrastructure. Vivacity was awarded the Queen’s Enterprise Award for Innovation in 2021, and our sensors have been deployed in over 60 towns and cities across the UK - with international growth well underway. We are passionate about the protection of personal data and our sensors have been developed using privacy-by-design principles to ensure that personal data is never compromised. For more information please visit: www.vivacitylabs.com.

Categories

  • ANPR /Automated Number Plate Recognition/ Licence Plate Recognition
  • Highway Infrastructure
  • Intelligent Transport Systems (ITS)
  • Loops / Sensors / Detection
  • Signalling
  • Software
  • Speed Measuring
  • Traffic Control & Monitoring
  • Traffic Detectors
  • Traffic Signalling & Control Devices
  • Vehicle Classification
  • Video Image Processing
  • Wireless Data Communication

Documents

Videos

Near Miss Solution for Road Safety Schemes & Traffic Management - Vivacity Labs
With advanced 3D detection capabilities, Vivacity’s new ‘near miss’ feature makes it possible to identify accident hotspots and investigate their root cause. By combining speed and path datasets, and analysing the post-encroachment time of vehicles as they cross a single point, near miss data reveals the riskiest areas of a road space to inform proactive safety interventions.
Short Term Surveys Vs Long Term Monitoring - Traffic & Transport Solution
Humans continuously strive to understand how people interact with cities, towns and infrastructure. Decision makers are constantly in need of data to monitor current network usage and adapt to changing numbers of travellers, habits and trends. So far, short-term traffic surveys have been the dominant method employed to gather this insight and deliver snapshots of activity at certain times, jumping from event to event. Short-term monitoring can’t be used for any deeper understanding of how behaviours are affected as a result of an intervention, or to identify any deficiencies in a scheme, such as potential dangers or inefficiencies in its design. Our AI-powered technology and advanced computer vision and Internet of Things (IoT) innovations unlock 24/7 365 anonymous monitoring and offer a data accuracy of +97%. Not only is it non-stop, but it’s also significantly more accurate than short-term measuring technology.
Why Data Accuracy is Crucial for the Future of Smart Cities
There is an assumption that all data is created equal. This is simply not true. History is littered with technologies which provide “data”, but if you cannot trust the insights it is worthless. When it comes to city infrastructure, authorities who are making decisions on the future of our roads and cities are rightfully sceptical of data accuracy and reliability claims that are provided without evidence, including how data is verified. Vivacity Labs' traffic sensor solution provides insights that contribute to the evolution of smart cities, helping to promote clean air and active travel initiatives and make cities better connected. All data provided is reliable, detailed and accurate so that these projects have all the insights they need to succeed.
Speed Monitoring Data for Road Safety Using Vivacity AI-Powered Sensors
Vivacity AI-powered sensors offer accurate average speed monitoring data for different road user classes, including pedestrians, cyclists, cars, vans and HGVs. This analysis and insight is extremely valuable for planning and monitoring of road safety schemes. With Zonal Speed datasets, it’s possible to identify where speed limits are or are not being obeyed. This insight can help make the case for further speed lowering methods to be introduced. The data is also valuable for assessing the success of new and existing measures, and paired with multi-modal classifications, makes it possible to identify if reduced vehicle speed has increased pedestrian and cyclist counts, and overall active travel.