Flood Finder

Data Science
Image Recognition

The impacts of climate change drive more extreme weather events, which leads to flooding that puts many urban communities under stress. In 2017, San Jose was hit with heavy rain that resulted in creeks and reservoirs overflowing that overwhelmed the area. The flood resulted in $100 million in economic losses and 14,000 people displaced. The biggest issue during the 2017 flood was the city’s failure to notify its residents that their neighborhoods were under imminent danger of flooding. By the time San Jose put an evacuation order into place, many residents were already standing waist-deep in water. Since 1950, the city has dealt with 13 floods, and the absence of any warning has remained a consistent issue due to the lack of real-time flood data.

To resolve this lack of real time data/information issue, we are proposing the implementation of the FloodFinder project which seeks to collect accurate flood data by utilizing camera (traffic and private camera) feeds and flood sensors. FloodFinder seeks to develop Urban Water Resilience in San Jose and work toward achieving the targets set in five different Sustainable Development Goals: SDG 9 “Industry, Innovation, and Infrastructure”, SDG 11 “Sustainable cities and communities”, SDG 13 “Climate actions”, and SDG 15 “Life on land”.

1. Camera Data Feed (Traffic camera and Private camera feeds)
Machine learning algorithms will be applied to the traffic and the crowdsourced private camera feeds to detect areas that are flooded. Furthermore, the algorithm will be able to estimate the height of the water in order to determine the areas that are most affected.

2. FloodFinder Dashboard and alert system
The data collected by the cameras and flood sensors will be compiled to create a flood model dashboard that will visualize flooding. Just as you can see hotspots of traffic on Google Maps, you will be able to see hotspots of flooding on this dashboard. The FloodFinder dashboard will be placed on the city website so that it can be accessed by citizens. The citizens can enroll to get text alerts.

Our key partners will be the San Jose City officials and student citizen-scientists. The partnership with city officials will be crucial in adopting FloodFinder to their existing systems. After speaking with the mayor of San Jose, Sam Liccardo, we have learned that the city is supportive and encourages innovation to create water resilience in San Jose. Furthermore, student citizen scientists will be critical for FloodFinder, as we will partner with the engineering departments of San Jose schools to mobilize student citizen scientists to assemble the flood sensors.

FloodFinder is able to differentiate itself from competitors by utilizing existing infrastructure, offering a custom low-cost solution, and using open-source technologies that allow for innovation.

No volunteer openings available for this project.

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