Author(s): David Bazzett; Hariharan Venkat; Prasanthi Maddala; Ivan Seskar; Narayan Mandayam; Michael Wu; Ruo-Qian Wang
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Keywords: Environmental sensing weather sensing flash flood High-resolution meteorological data Flood resilience
Abstract: Urban flooding poses severe risks to public health and safety, leading to injuries, hypothermia, animal bites, infection, and mental health impacts, among other threats. While there have been advances in understanding flooding at broader scales, significant gaps remain in community-level data for evaluating climate impacts, adaptation strategies, and resilience-building solutions. The primary challenge is capturing high-resolution, community-specific meteorological data during extreme weather events. The urban environment itself, with its dense landscape of buildings and infrastructure, influences precipitation patterns and flooding. Conventional weather stations are spaced far apart (1–100 km) and are often situated in rural areas to minimize disruptions from human activity. Although satellite, airborne, and radar remote sensing offers broader coverage, they lack the spatial and temporal resolution required to monitor urban precipitation with sufficient granularity. To address this gap, we conducted a series of laboratory experiments using a Rainfall Table at the Urban and Coastal Water System Laboratory at Rutgers University. This setup simulates rainfall under controlled conditions, allowing precise measurement of raindrop size, density, and precipitation rate. A 5G mmWave transceiver, developed through the NSF PAWR COSMOS project at WINLAB at Rutgers, was installed to assess rainfall and humidity impacts on 5G signal transmission. We then developed statistical models to correlate 5G signal impairments with measured parameters of artificial rainfall, such as precipitation rate and air moisture. The resulting data processing model converts 5G attenuation data into accurate precipitation and humidity metrics. These experiments demonstrate the potential of 5G technology as a novel urban precipitation sensor, offering high-resolution, real-time data essential for improved forecasting and community-level flood resilience.
Year: 2025