Tianqiong Sensor IOT Technology Co., Ltd
Sales Manager:Ms. Emily Wang
Cel,Whatsapp,Wechat:+86 15898932201
Email:info@fengtutec.com
Add:No. 155 Optoelectronic Industry Accelerator, Gaoxin District, Weifang, Shandong, China

Sales Manager:Ms. Emily Wang
Cel,Whatsapp,Wechat:+86 15898932201
Email:info@fengtutec.com
Add:No. 155 Optoelectronic Industry Accelerator, Gaoxin District, Weifang, Shandong, China
time:2025-10-22 09:08:35 source:Weather Station viewed:356 time
In modern traffic management, real-time and accurate road condition monitoring is of great significance for ensuring driving safety and improving road operation efficiency. Traditional road weather stations typically require embedded installation, which not only damages the road structure but may also disrupt normal traffic flow. The measurement accuracy of contact detection equipment is easily affected by external environments, making it difficult to fully reflect changes in road surface conditions. To address these issues, the FT-LM1 Non-Contact Road Condition Sensor emerged, based on multi-spectral remote sensing technology, achieving high-precision identification and monitoring of road surface conditions, providing reliable hardware support for traffic meteorological services.
The FT-LM1 adopts a remote sensing detection mechanism that does not require embedding in the road surface or drilling construction, fundamentally avoiding damage to the road structure. The installation process is simple and flexible, allowing rapid deployment without interfering with traffic, making it particularly suitable for high-traffic areas and accident-prone road sections.
Through multi-band spectral analysis, the sensor can accurately identify water, snow, and ice conditions on road surfaces and measure their thickness, with a water detection range of 0–10 mm and ice/snow thickness detection range of 0–2 mm. Additionally, the system can determine road surface slipperiness, with a friction coefficient identification range covering 0.01 (slippery) to 0.82 (high friction), providing critical data for road safety warning.
The FT-LM1 Non-Contact Road Condition Sensor can not only report six road surface conditions: dry, wet, slippery, snowy, icy, and ice-water mixture, but also optionally equipped with weather phenomenon monitoring function to identify weather types such as rain, snow, and heavy fog that affect visibility and road safety. Data is transmitted through RS485 or RS232 interfaces, facilitating integration into various traffic monitoring systems.
Application Scenarios:
Real-time monitoring of road surface conditions on highways, bridges, tunnels, and other critical road sections
Winter road safety warning in areas prone to snow disasters, freezing rain, and other meteorological hazards
Urban traffic arteries and accident-prone areas for monitoring slipperiness and water accumulation
Integration with smart highway platforms as the basic sensing unit of road meteorological information systems

The FT-JL1 Automatic Monitoring Instrument for Runoff Sediment is a professional device used for real-time, automatic monitoring of soil erosion conditions. It can accurately measure runoff volume and sediment concentration, providing data support for environmental protection, disaster early warning...
Digital Weather Station is a highly integrated, low-power, and rapidly deployable high-precision automatic meteorological observation device. It provides real-time monitoring of nine key meteorological elements—including wind speed, wind direction, temperature, humidity, atmospheric pressure,...
Faced with numerous types of anemometers on the market, how can one select a product that meets their own needs? First, let's understand the common types of anemometers.Mechanical AnemometerAmong mechanical anemometers, the cup anemometer is relatively common. It relies on the rotation of cups u...
In fields such as agricultural production, outdoor sports, and transportation, accurately grasping weather conditions is crucial. Although traditional large-scale weather stations can provide macro meteorological data, they have shortcomings in monitoring accuracy in local areas and are difficult to...