Safer Streets for Less
Cities in cold and wet climates need to dedicate significant resources to ensure that their streets are safe during wet, icy and snowy conditions. For example, cities in the United States use more than 15 million tons of salt for winter road treatment every year. While road treatment is important for driver safety, salt and chemical treatments are expensive, corrosive to both vehicles and pavements and can be detrimental to freshwater ecosystems.
With the NearSky smart city platform, cities can easily monitor road surface conditions and determine precisely where and when to apply salt or chemical treatments. The platform includes NearSky 360, CIMCON Lighting’s streetlight-mounted edge data processor that allows you to easily install road surface sensors across the city. These noninvasive sensors can measure many parameters that effect driver safety such as road condition (dry, moist, wet, ice, snow, critical wet, chemically wet), road surface temperature, water film height, dew point temperature, relative humidity, ice percentage, freezing temperature, and friction.
- Easy to install – this system uses a non-invasive measurement systems and does not require road closures for installation
- Reduces labor and material costs related to winter road treatment
- Comprehensive - measure many road safety parameters with a single device: surface temperature, water film height, friction and more.
- Pre-configured reports –road surface data is collected, aggregated, and visualized in NearSky Vue, CIMCON’s easy-to-use smart city management software, so you can easily track measurements and share them with interested parties
- Early detection – measures parameters both on the ground and in the ambient air
- Reduces environmental impact associated with over treating roads
- Decision support for winter maintenance operators on roads, motorways, and highways
- Inform and protect citizens – keep the public informed about dangerous road conditions to promote safe driving
- Data collection for weather forecast model development