# Development of a 5G-Connected Ultra-Wideband Radar Platform for Traffic Monitoring in a Campus Environment

## TL;DR

Researchers developed a 5G-connected UWB radar system for campus traffic monitoring, achieving high detection and classification accuracy.

## Contribution

A novel 5G-connected UWB radar platform with an IoT system for scalable and real-time traffic monitoring in complex environments.

## Key findings

- The system achieved a 94.81% detection rate during peak-hour traffic on a double-lane road.
- It demonstrated a 97.29% classification accuracy and 99.66% direction accuracy.
- The median latency between radar and server was 75 ms over a commercial 5G network.

## Abstract

This paper presents the design, implementation, and testing of a traffic monitoring platform based on 5G-connected Ultra-Wideband (UWB) radars deployed on a university campus. The development of both connected radars and an IoT platform is detailed. The connected radars integrate commercial components, including a Raspberry Pi (RPi), a UWB radar, a standard enclosure, and a custom communication board featuring a 5G module. The IoT platform, which receives data from the radars via MQTT, is scalable, easily deployable, and supports radar management, data visualization, and external data access via an API. The solution was deployed and tested on campus, demonstrating real-time operation over a commercial 5G network with an estimated median latency between the radar and server of 75 ms. A preliminary evaluation conducted on a single radar during peak-hour traffic on a double-lane road, representing a challenging scenario, indicated a high detection rate of 94.81%, a low false detection rate of 1.02%, a high classification accuracy of 97.29%, and a high direction accuracy of 99.66%. These results validate the system’s capability to deliver accurate traffic monitoring.