In the client's project, there was a recurring issue of intermittent signal loss when high-chassis vehicles passed over the loops, resulting in multiple vehicle detections from a single vehicle. Upon switching to our product, we observed that the inductance variation from high-chassis vehicles was minimal, with some positions showing changes close to or below zero. Conventional detectors would inevitably experience signal loss in such scenarios. However, our algorithm effectively identifies this situation and ensures uninterrupted signal output.

At the client's project site, there was a recurring issue where the output signal would persist even after a vehicle had left, causing the detector to enter a locked state. After replacing the existing detectors with ClairLup detectors, we discovered that the inductance variation caused by certain vehicles, particularly heavy trucks, was significantly skewed.

The client's project site is near a railway with a complex surrounding power grid, making it difficult for various detector products to work reliably. By using our detectors and utilizing the waveform display function, we observed severe interference at the site. This interference causes two issues: 1) When there are no vehicles, the interference generates false vehicle presence signals; 2) After a vehicle leaves, the interference prevents the signal from ending, resulting in a continuous vehicle presence signal. By enabling the detector's interference filtering function, we can filter out the superimposed signals, reliably detecting vehicle entry and exit, perfectly meeting the client's application needs.

To avoid the interference between loops of closely installed detectors, other brand products will offer different frequency bands for selection. However, it is not a foolproof solution due to limitations in available frequencies, changing environmental conditions, added complexity, and regulatory constraints.

The ClairLup loop detector series includes Configuration Management Client software, offering parameter settings, serial output data display, and waveform visualization. The real-time waveform display interface captures inductance changes as vehicles pass through the loops. By continuously monitoring these waveforms, it significantly aids in on-site issue analysis and location tracking, making installation and environmental problems immediately evident.

In the demanding environment of highway tunnels, where space is confined, and conditions are complex, traditional millimeter-wave radars often fall short. Their limitations—such as poor penetration, signal attenuation, and susceptibility to multipath interference—can compromise safety and efficiency. Enter the tunnel-dedicated radar, a game-changer designed to meet the unique challenges of tunnel surveillance.

ClairBox-R AI Box represents the pinnacle of intelligent video recognition devices tailored for traffic applications. Powered by cutting-edge AI technology and boasting formidable video processing capabilities, AI Box excels in real-time capture and analysis of video content.

TraffiClair is proud to announce the launch of its latest product line, ClairLDR, designed to revolutionize vehicle contour and axle detection applications. Leading this product line is the ClairLDR-L1, a cutting-edge single-line hybrid solid-state LiDAR, meticulously engineered to deliver exceptional scanning speed, resolution, and reliability.

Discover unparalleled precision and efficiency with our ClairGeo-MP series wireless magnetic parking detectors. This innovative solution integrates three layers of insurance for precise detection, combining geomagnetic, radar, and photosensitive sensors. Whether you require LoRa, NB-IoT, or CAT.1 communication, our adaptable system ensures seamless integration tailored to your site’s specific needs.

In the traffic detection roadside radar market, primary frequency bands include 24 GHz and 77 GHz:

Q: ClairEye-i video detector utilizes a vast amount of real-world traffic data, and the algorithm is embedded in the AI chip for real-time traffic data processing. Is the data sourced from projects in the local region? Is it suitable for the global market's traffic situations?

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