Speaker
Description
Urban precipitation monitoring remains challenging due to strong microclimate variability and the limitations of sparse traditional observing networks. This study leverages the OpenMesh dataset, a unique opportunistic sensing (OS) network in New York City spanning Manhattan and Brooklyn, to enable continuous environmental monitoring. We focus on the deployment of co-located personal weather stations (PWS) and wireless links operating at distinct frequency bands, including the high V-band (58--70~GHz) and a lower-frequency band (5--6~GHz), to better understand urban weather dynamics.
We present an analysis of varied precipitation events across the urban landscape. By analyzing concurrent data streams, we characterize the differing responses recorded by the PWS network and the wireless-link signal fluctuations across these distinct bands.
These distinct OS signatures, derived from a dense network of diverse sensors including PWS and wireless links of varying lengths (from tens of meters to a few kilometers) at low and high frequencies, are validated against independent meteorological sources to confirm their varying responses to different precipitation types and highlight their capability for high-resolution weather mapping across urban areas.
This highlights the broader potential of opportunistic integrated sensing and communication (OISAC) to utilize new communication link deployments, including community-based ones, for continuous, high-resolution environmental mapping. By combining the attenuation observed across these distinct bands with dense PWS data, we encourage the research community to leverage the open-access OpenMesh dataset to advance high-resolution urban precipitation retrieval.