Skip to main content

Image Sensing Systems and trafficnow partner on traffic information

Image Sensing Systems (ISS) and Bluetooth sensors provider trafficnow have completed a distribution agreement for Image Sensing Systems to sell trafficnow’s DeepBlue sensor in most of North America and parts of the Middle East. This partnership will allow customers to leverage ISS’ RTMS radar detection technology and trafficnow’s DeepBlue Sensor. The combination of these sensors provides a complete picture of traffic information by being a big data source for up to 12 lanes of continuous traffic.
September 23, 2015 Read time: 2 mins
Image Sensing Systems (ISS) and Bluetooth sensors provider 6771 trafficnow have completed a distribution agreement for Image Sensing Systems to sell trafficnow’s DeepBlue sensor in most of North America and parts of the Middle East.  

This partnership will allow customers to leverage ISS’ RTMS radar detection technology and trafficnow’s DeepBlue Sensor.  The combination of these sensors provides a complete picture of traffic information by being a big data source for up to 12 lanes of continuous traffic.

The RTMS Sx-300 provides the point information such as volume, occupancy, speed and classification and the DeepBlue sensor provides the spatial information such as travel time and origin/destination matrix.  The data from these two sensors will provide real-time travel time information, allowing drivers to make smart travel decisions to help reduce their commute and keep traffic flowing

“ISS works hard to identify innovative technologies that complement our technology portfolio and Bluetooth is a dynamic addition,” said Dan Skites, highway general manager at Image Sensing Systems. “As traffic continues to grow and travel times increase, the motoring public is getting frustrated and demanding that travel information is available.  Traffic management professionals can now rely on the most accurate real-time data and analytics.”

“More than just a partnership between two global players in the ITS market, this is a partnership between spatial information and point information; it’s about getting the full picture of the traffic situation in up to 12 lanes from the side of the road,” said Robert Nordentoft, general manager at trafficnow.

For more information on companies in this article

Related Content

  • Data sharing for Flow Labs & Michelin Mobility Intelligence
    June 7, 2024
    'We now have the tools to anticipate crashes and take steps to prevent them'
  • Weigh in motion reduces road wear, increases toll revenue
    January 24, 2012
    IRD, Inc's Terry Bergan discusses future applications of weigh in motion technology. The application in recent years of Weigh In Motion (WIM) at tollgates has been driven by recognition of the fact that there is economic value, which can be levied, attached to Heavy Goods Vehicles (HGVs) which haul laden (and are therefore heavy) rather than empty. As wear and damage to road surfaces increases exponentially with weight, the targeting of HGVs in particular makes sense from both the economic and maintenance p
  • Smarter transport remains key to smart cities
    January 9, 2018
    Colin Sowman looks at some of the challenges and solutions that will provide enhanced transport efficiency in tomorrow’s smarter cities. However you define a ‘smart city’, one of the key ingredients will be an efficient transport system. As most governments and city authorities face financial constraints, incremental improvements in the existing systems is the most likely way forward. In London, new trains and signalling are improving the capacity of the Underground but that then reveals previously
  • Highways Agency trials new traffic monitoring technology
    September 24, 2013
    The UK Highways Agency is trialling a system to add commercially available traffic data to its existing sources to monitor traffic flow on England’s motorways and strategic roads. Similar data sources are already used by satellite navigation devices, smartphones, and applications like Google maps. The system uses data that comes mostly from vehicle tracking devices installed by fleet operators, and a proportion from mobile sat-nav type devices, including smartphone traffic applications where the user has