Onssi and Vaxtor partner on license plate recognition integration

Vaxtor Corporation’s (Vaxtor) advanced LPR analytics platform can now be deployed across Onssi’s Ocularis VMS platform to recognize, capture and archive data on license plates, railway vehicles, U.S. Department of Transport (USDOT) numbers and more as part of an integration partnership between both companies. The agreement, according to Onssi’s Ken LaMarcam VP of sales & marketing, allows the solution to deliver a range of security and operations data to meet the specific challenges of the transportation
February 12, 2018 Read time: 2 mins

Vaxtor Corporation’s (Vaxtor) advanced LPR analytics platform can now be deployed across 677 Onssi’s Ocularis VMS platform to recognize, capture and archive data on license plates, railway vehicles, U.S. Department of Transport (USDOT) numbers and more as part of an integration partnership between both companies. The agreement, according to Onssi’s Ken LaMarcam VP of sales & marketing, allows the solution to deliver a range of security and operations data to meet the specific challenges of the transportation and law enforcement markets.

The Vaxtor LPR solutions include the capture of OCR, MMR (year, make and model of vehicles), USDOT, Railway, Container, Red Light and Wrong Turn detection integrations. The analytics are said to recognise letters, numbers and symbols both vertically and horizontally. Ocularis is available as a professional model for organisations operating multiple locations with small to mid-sized camera counts as well as an Enterprise version for a range of mid to large IT-centric companies. In addition, the Ultimate model is aimed at large clients with extended command and control needs and recording server failover.

Michael Deutsch, executive management consultant, Vaxtor, said: “The integration of our LPR and OCR analytics provides highly functional and reliable data capture capabilities. End users can now capitalize on the valuable rich data contained in printed text and numbers, with the confidence that the information is both highly accurate and instantly accessible.”

Urban Traffic Control

For more information on companies in this article

Related Content

  • ISS and MAV Systems partner on new mobile LPR camera
    April 15, 2014
    Image Sensing Systems (ISS) has partnered with MAV systems to release a new compact licence plate recognition (LPR) camera, the Autoscope Pn-120. The Autoscope Pn-120 is a compact high performance LPR camera designed for mobile and special purpose applications. Compact and easy to install, the camera incorporates industry leading zoom technology, infrared pulsed LEDs within a rugged hermetically sealed enclosure. According to both companies, when coupled with ISS’ state-of-the-art licence plate recogn
    Read More
  • Cooperative infrastructure an aid to environmental aims
    February 3, 2012
    Speculate to accumulate Andras Kovacs looks at how the historical focus of cooperative infrastructure on safety can be oriented to aid emerging environmental aims
    Read More
  • Mexico City seeks solutions to improve air quality
    December 6, 2017
    David Crawford ponders prospects for one of the world’s most congested and polluted cities. In 1992, the United Nations named Mexico City as the world’s most polluted urban centre. In the first half of 2016, following the updating of pollution alert limits to meet international standards, Mexico recorded 115 days where ozone concentrations exceeded the acute exposure health limit.
    Read More
  • Image Sensing Systems premiers integrated radar and Bluetooth sensor
    June 13, 2016
    Image Sensing Systems (ISS) is here at ITS America 2016 San Jose to introduce the RTMS Sx-300 with integrated Bluetooth sensor to its traffic management product line. The device is a powerful tool that agencies can use to better manage traffic. ISS says the combination of the RTMS radar with the robust Bluetooth sensor is the ideal solution for incident detection and providing traffic managers with highly accurate travel time and origin/destination information.
    Read More

Highlighted Content