Team: Marco Tedesco
Affiliation: Columbia University, Research Professor at the Lamont-Doherty Earth Observatory
LinkedIn: Marco Tedesco
Email: mtedesco@ldeo.columbia.edu
Climate Impact detects flooded city areas using web cameras and images as well as artificial intelligence technology, providing estimations of water levels in impacted areas. Climate Impact’s detector has both stand-alone and plug-and-play capabilities, allowing it to generate ubiquitous real-time, accurate estimates of flooding. Through the Climate Impact product, cities can better monitor flood trends and mitigate the effects of flooding on their infrastructures and communities.
Team: Mahshid Dehkordi, Jeremy Johnston
Affiliation: Columbia University, Columbia PhD Candidates in Electrical Engineering
LinkedIn: Mahshid Dehkordi, Jeremy Johnston
Email: mahshid.ghasemi@columbia.edu, jj3057@columbia.edu
KeeVeeve provides real-time traffic, crowd, and road information for the general public. Leveraging existing city edge-cloud servers and traffic and surveillance cameras, KeeVeeve anonymously visualizes current traffic information on an interactive map and provides an API smart city technologies (ie. autonomous vehicles, smart traffic lights, and smart street lights) can connect to. KeeVeeve helps general vehicles and pedestrians reduce commute times, enhancing the accessibility and safety of cities.
Team: Caspar Lant
Affiliation: Columbia University, PhD Candidate in Computer Science
LinkedIn: Capsar Lant
Email: caspar@cs.columbia.edu
In an era of increased risk from vehicular traffic, Walkwise protects the most vulnerable road users. Through their GPS-based pedestrian intent prediction tools, which leverage a transformer-based machine-learning model that inputs live, local GPS-positioning data (as recorded by a user’s phone), Walkwise provides information on pedestrian’s intersection interactions. By transmitting crossing predictions to intersection signaling gateways, Walkwise can provide dynamic, optimal solutions for any traffic circumstance.
Team: Georgios Sklivanitis, Dan Zimmerman
Affiliation: Florida Atlantic University, Faculty in Electrical Engineering and Computer Science; Florida Atlantic University, Graduate Student in Electrical Engineering and Computer Science
LinkedIn: Dan Zimmerman, Georgios Skilvanitis
Email: dzimmerman2021@fau.edu, gsklivanitis@fau.edu
FloodSense improves the accuracy of flood forecasts in areas with lacking weather infrastructure. By crowdsourcing hydrologic data, FloodSense offers an entirely new data economy that rewards people and cities who deploy and maintain FloodSense’s flood monitoring sensors. Through a dense, decentralized flood marketplace that users can purchase and sell hydrologic data on, FloodSense can improve city-wide flood awareness.
Team: Christopher Grullon
Affiliation: Columbia University, Undergraduate Student at the Fu Foundation School of Engineering and Applied Science
LinkedIn: Christopher Grullon
Email: grullonc455@gmail.com
Sustainable Safe Smart Intersections is equipping cities with technology that enables more sustainable living. Through their intersection simulation model, Sustainable Safe Smart Intersections offers an analysis of the impact of intersection redesigns. Trained on integrated, real-world data points, the product offers simulations similar in accuracy to real-life, intersection situations.
Team: Izaac Martinez
Affiliation: Florida Atlantic University, Undergraduate Student in Data Science and Analytics
LinkedIn: Izaac Martinez
Email: izaacmartine2022@fau.edu
FloodFinder product detects road flooding, alerting the public of optimal rerouting options. The FloodFinder product leverages both FloodFinder cameras’ feeds and pre-existing traffic cameras to identify flooding. Using neural networks to develop software that analyzes photos and video, the FloodFinder alarm light will warn the public about high-flood areas, keeping drivers safer and better informed.
