Civil and Environmental Engineering Assistant Professor and also member of the ECE Graduate Faculty David Hill and ECE Assistant Professor Dario Pompili collaborate on sensing and modeling extreme weather events. Such events have profound effects on the sustainability of urban centers. At the same time human activities are increasing the variability of the climate and increasing the frequency of these events; driving the need for more dynamic decision making tools.
Recent research has explored "smart" urban infrastructure to mitigate extreme weather risks; however, these methods all rely on real-time observations of the environment at appropriate time and space scales. Unfortunately, this observational resolution is not feasible with traditional sensing technologies.
The overall objective of this research is to address urban sustainability through the development of modeling methods suitable for forecasting environmental phenomena in a changing world, and through the development of technology that can enable autonomous infrastructure to adapt to rapidly evolving environmental conditions. This pilot study will support this objective by building long-term research collaborations with Rutgers faculty necessary to meet this multidisciplinary challenge and by developing a real-time system to explore ubiquitous sensing of the environment. This research will focus on rainfall estimation and measure success by the ability to provide ac-curate rainfall estimates at resolutions higher than the minimum threshold suggested by the literature.
Specifically, this research will answer the question of whether it is necessary to use data from dense net-works of dedicated rainfall sensors to achieve accurate real-time rainfall measurements at spatio-temporal resolutions sufficient to enable predictive control of smart infrastructure, or whether networks of heterogeneous ubiquitous sensors can provide sufficient information to achieve the same level of observational resolution and accuracy. This research scope focuses the research on creating a real-time system for adaptive sensing of rainfall using ubiquitous sensors, which will permit the PI to establish research collaborations and external funding to pursue the ambitious overall objective of enabling predictive control of urban infrastructure during extreme weather events.