Cubic and SenSen Networks agree on video analytics

Cubic Transportation Systems has entered into a strategic alliance and licence agreement with Australia-based video analytics specialist SenSen Networks, enabling Cubic to distribute SenSen’s products and solutions that align with Cubic’s NextCity smart cities vision. The companies plan to deliver a range of solutions to the market, including automatic gate line monitoring in train stations and transport hubs using video analytics and intelligent video to increase commuter flow, detect health and safety
September 9, 2014 Read time: 2 mins
378 Cubic Transportation Systems has entered into a strategic alliance and licence agreement with Australia-based video analytics specialist SenSen Networks, enabling Cubic to distribute SenSen’s products and solutions that align with Cubic’s NextCity smart cities vision.

The companies plan to deliver a range of solutions to the market, including automatic gate line monitoring in train stations and transport hubs using video analytics and intelligent video to increase commuter flow, detect health and safety issues, and minimise fare evasion.

Video analytics will also be applied to speed, safety and toll enforcement solutions for road authorities, parking guidance and enforcement for city councils, people and vehicle traffic counting and classification for a variety of applications and intelligent security for stations, rail infrastructure, airports and other critical infrastructure.

“The agreement with SenSen is a good strategic fit for our NextCity vision, which will enable transport operators to regulate demand and provide travellers with choices for travel – all through the delivery of actionable data that we gather from all our information points throughout our ITS systems,” said Matt Cole, executive vice president, strategy, business development and diversification for Cubic Transportation Systems.  “Advanced video analytics allows our customers to cost-effectively gain deep insights of transportation infrastructure improving decision making, safety and long-term planning.”

”SenSen operates at the cusp of big data, sensor networks and business intelligence. Our core skill is in analysing big data streams in real time, recognising all interesting events and creating accurate and structured metadata that lead to high-value applications,” said Subhash Challa, chief executive officer of SenSen Networks.

Detection, Monitoring & Machine Vision Urban Traffic Control

For more information on companies in this article

Related Content

  • Sustainable mobility? Only possible with a multifaceted approach
    May 25, 2023
    ITS European Congress 2023 was scene for 'full and frank exchange of views'
    Read More
  • Cubic Transportation Systems launches Cubic NextBus
    October 10, 2017
    Cubic has announced its business division, Cubic Transportation Systems, is releasing the Cubic NextBus (CNB) to multimodal transit agencies, authorities and operators to provide Transit Management as a Service. The CNB uses public cloud architecture and machine learning capabilities for further enhanced real-time passenger information (RTPI), proactive transit fleet operations and mobile user experience.
    Read More
  • Digital twins help city space race
    October 26, 2022
    As the world becomes more urbanised, there is a need to monitor the likely effects this will have on the way we live, says Jeroen Borst of TNO, the Dutch organisation for applied scientific research
    Read More
  • Leeds City Council expands bus lane enforcement system
    November 17, 2015
    Leeds City Council is expanding the reach of its CCTV enforcement network to a further six sites as a direct result of the improvements that the Videalert-based system has delivered over the last four years. The council will now be enforcing bus lane contraventions at thirty sites throughout the city and expects to achieve further reductions in the number of offences committed and continue to meet its strategy of faster journey times for public transport users. The Videalert system was originally in
    Read More

Highlighted Content