Street-level Flooding Platform: Sensing and Data Sharing for Urban Accessibility and Resilience

Of the myriad climate change impacts, flooding is expected to have an outsized influence on public health and infrastructure. In New York City, for example, sea level rise and high intensity rain storms (which convey large volumes of water to drains, leading to backups and overflows) have led to a dramatic increase in flood risk, particularly in low-lying and coastal neighborhoods. The physical presence of standing water on streets and sidewalks can impede mobility and restrict access to transportation. Additionally, urban flood water contains a diverse array of contaminants, including industrial and household chemicals, fuels, and sewage. Access to real-time information on flooding can improve resiliency and efficiency by allowing residents to identify navigable transportation routes and make informed decisions to avoid exposure to floodwater contaminants. While there exist commercially available sensors that detect the presence of water inside homes, there is an unmet need for hyperlocal information on the presence and depth of street-level floodwater. Therefore the objective of the proposed work is to develop a publicly- accessible platform that provides real-time flood information. The goals are to develop a flood sensor that overcomes common sensor challenges (including durability, connectivity, and power), as well as the digital infrastructure necessary to log, process, and present the data in combination with other publicly available information, such as rainfall data, 311 flooding complaints, and social media feeds. The research team sees many potential applications of this proposal, including incorporation with the PIs’ ongoing research into potential exposure to sewage- associated pathogens following urban flood events.


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Filing Info

  • Accession Number: 01737124
  • Record Type: Research project
  • Source Agency: Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)
  • Contract Numbers: USDOT 69A3551747124
  • Files: UTC, RIP
  • Created Date: Apr 23 2020 8:22AM