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ELECTRONICS | Chips & Semiconductors / Semiconductors: Sensors
vivacitylabs.com

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Founded Year

2015

Stage

Series A | Alive

Total Raised

$12.84M

Last Raised

$7.02M | 7 mos ago

About Vivacity Labs

Vivacity Labs provides mobility tracking services, enabling detailed understanding of transport systems through intelligent cameras & video analytics. The company has developed novel machine learning software and sensor technology which is applied to solve a wide range of traffic and transport issues, most specifically for the automatic counting and classification of pedestrian and vehicle flows in a variety of environments.

Vivacity Labs Headquarter Location

International House 24 Holborn Viaduct

London, England, EC1A 2BN,

United Kingdom

Latest Vivacity Labs News

Council Uses AI to Track Actual Cycle Lane Usage

May 29, 2021

Earlier this year, Sutton and Kingston Councils announced their partnership with UK-based transport company Vivacity Labs to help improve active travel insight and the safety of high footfall areas. The councils, as part of the South London Partnership’s InnOvaTe Project , will use Vivacity’s AI and Internet of Things (IoT) technology to provide anonymous data on different transport modes and movement patterns. Sensors will be deployed to gather more information about each borough’s cycle infrastructure, including the number of cyclists currently using the existing cycle lanes and main roads within the borough, and the number of unauthorised vehicles illegally using the spaces. This will help the councils to consider the areas to be included in any future expansion of their cycle infrastructure. Councillor Manuel Abellan, Chair of the Environment & Sustainable Transport Committee at Sutton Council, said: “The Council recognises the need to reduce the amount of private car use and to promote active travel. By using this innovative technology, the Council can learn more and gain better insights into the use of its cycle lanes. This will enable us to identify opportunities to reduce carbon dioxide emissions.” Mark Nicholson, CEO of Vivacity Labs, commented: “By understanding how space is being used with detailed and accurate data, councils can make informed and strategic decisions on how best to improve city infrastructure. As restrictions are eased, making roads smarter, safer and more sustainable is vital, and we look forward to seeing the positive impact on cycling that this project will create in the Kingston and Sutton area.” Thirteen sites have been identified in Sutton to provide a good insight into the cross-borough usage of the cycle infrastructure, which includes areas in Beddington, Hackbridge, Carshalton, Cheam and Worcester Park. In Kingston, seventeen sites have been identified, including routes in Kingston Town Centre, Surbiton, Tolworth, Chessington and New Malden. The scheme will help both councils build an overview of the cycle network to enhance decision-making and the application of bids. Share this:

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Expert Collections containing Vivacity Labs

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

Vivacity Labs is included in 3 Expert Collections, including Smart Cities.

S

Smart Cities

1,344 items

C

Connected Vehicle Tech

410 items

Startups developing software and/or hardware technology that enables in-vehicle connectivity and connectivity-related applications like telematics, media, and vehicle-to-infrastructure communication.

A

Artificial Intelligence

7,364 items

This collection includes startups selling AI SaaS, using AI algorithms to develop their core products, and those developing hardware to support AI workloads.

Vivacity Labs Patents

Vivacity Labs has filed 3 patents.

The 3 most popular patent topics include:

  • Artificial neural networks
  • Machine learning
  • Artificial intelligence
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Application Date

Grant Date

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Related Topics

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2/28/2019

10/27/2020

Mathematical optimization, Artificial neural networks, Artificial intelligence, Diagrams, Machine learning

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10/27/2020

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Related Topics

Mathematical optimization, Artificial neural networks, Artificial intelligence, Diagrams, Machine learning

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