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Sensors Could Make Winter Road Conditions Easier To Predict, Navigate

By Michael Luciano | November 28, 2017

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The Highways UK 2017 Intelligent Infrastructure Challenge was a major symposium that took place earlier in November. The event assembled thousands of individuals and organizations that plan, design, build, operate, and future-proof the United Kingdom’s roadways. The objective entails specific infrastructure client challenges from governmental entities like Highways England, Bristol City Council, Transport for the North, England’s Economic Heartland, London Air Quality Commission, and Transport Scotland. Participants are expected to utilize innovative technical solutions to problems relating to customer service, network efficiency, safety and security, along with infrastructure performance.

The Highways UK 2017 Intelligent Infrastructure Challenge winner was Lee Chapman, a climate resilience professor hailing from the University of Birmingham (which has an extensive history of research into winter road sensing and forecasting). Professor Chapman won the national award for developing a low-cost, non-invasive, self-contained road surface temperature sensor.

The device remotely detects road surface temperature using infrared thermometry, and can be used for direct gritting lorries to priority areas. The judges felt deploying this type of sensor network could immediately impact the ability to better control gritting routines during the winter months.

Known as “wintersense” sensors, the technology is IoT-enabled, and utilizes a new generation of low power communications to provide real-time measurements of road surface temperatures. During the winter, highway maintenance companies deploy fleets of gritting lorries with hopes of preventing and minimizing the impacts on drivers and traffic on highways and main roads caused by black ice.

These services aren’t necessarily widely available, especially when winter conditions intensify, which is when the routing and gritting of lorries becomes more optimal and selective. The biggest issue with this selective optimization is possessing good spatial resolution to observe road surface conditions.

Wintersense sensors offer an IoT approach at sensing road surface temperatures, and their sensors are notably cheaper than the systems and technologies being currently used. In addition, these sensors are so light they can be mounted on lamp posts, gantry, or road signs. These conditions can help rapidly deploy an elaborate network of sensors throughout roadway networks that can give a highly accurate depiction of road surface conditions.


Filed Under: M2M (machine to machine)

 

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