Our Research on Network Environmental Sensing
Our Research on Network Environmental Sensing
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Network Environmental Sensing
Network Environmental Sensing
In this research, we are developing key technologies for extracting environmental related information, such as rainfall, water level variation, air pollution and even bushfire, using received communication signals in mobile networks. Through partnering with NSW State Emergency Service (SES) and TPG (The third largest mobile operators in Australia), we have conducted successful field trials and validated the feasibility of our 5G flood sensing technology with high performance. For example, the water sensing can be as accurate as 1mm.
Our overview paper:
Kai Wu, Zhongqin Wang, Shu-Lin Chen, J. Andrew Zhang, Y. Jay Guo, "ISAC: From Human to Environmental Sensing", submitted to IEEE JSTEAP, https://arxiv.org/abs/2507.13766
Water Level Sensing
Water Level Sensing
Sensing the water level variation via detecting the variation of the propagation path, which is reflected via the phase variation of the received signals.
Publications delayed by patent application. More to come.
Z. Wang, J. A. Zhang, K. Wu, and Y. J. Guo, “Water level sensing via communication signals in a bi-static system,” arXiv preprint arXiv:2505.19539, 2025
Z. Ni; J. A. Zhang, and R. P. Liu, “Deep Learning Based Water Level Sensing with Interference Suppression for ISAC Systems”, IEEE Communications Letters, accepted for publication, July 2025
Live water level sensing using downlink mobile signals.
In-Field base-station side water sensing using statistical information of uplink communication signals.
Rainfall Sensing
Rainfall Sensing
Radio signals are affected by rainfall in both magnitude and phase. Extracting such information enables rainfall sensing even over a short distance of several meters. Hence it is feasible to do rainfall sensing in mobile networks with connections ranging from tens of meters to a few kilometers.
The right animation shows some of our obtained results. Subfigures from top to bottom: Rain intensity shown on Google map, Rain intensity from rain gauges (Ground truth), Estimated rain intensity from mobile signals, Extracted feature signals from mobile signals.
Publications delayed by patent application. More to come.
[1] Y. Xu, K. Wu, J. A. Zhang, Z. Wang, B. A. Jayawickrama, and Y. J. Guo, “Smartphone-based experimental analysis of rainfall effects on LTE signal indicators,” Sensors, vol. 25, no. 2, p. 375, 2025
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