The Detroit RiverFront Conservancy (DFRC) has partnered with the University of Michigan to use data collected by remote sensors and security cameras to better understand how people are currently using the Riverfront and to inform strategies to enhance the use of under-utilized areas.
The approximate number of people that visit the Detroit riverfront each year
Of Detroit River frontage from Joe Louis Arena to Gabriel Richard Park
Of camera data collected a year
The Detroit Riverfront Conservancy (DFRC), which is coordinating development of the Riverfront area, is interested in better understanding the ways in which visitors use their recreational spaces. Parks are one of the most essential ingredients to the success of any vibrant city because they offer a recreational venue where patrons can commune with nature while enjoying a rich set of social experiences. The value of parks is well established with benefits ranging from being engines of economic growth to improving public health.
This project partners with the DRFC to explore the development of a data-driven approach to measuring usage of the park and trails. The DRFC has struggled to fully understand how the park space that they manage is used. The overarching goal of this project is to develop and deploy new approaches to collecting data to quantitatively assess how patrons use city parks and trails including mapping their trajectories within the space and identification of patron activities. This allows park managers to make more informed, data-based decision on how to improve the experience of park patrons while also informing communities on the performance of their parks.
There is currently an extensive network of security cameras in use along the Riverfront. Using human activity recognition tools on the video obtained from the security cameras and the data collected by other remote sensing devices, researchers from the University of Michigan are able to distinguish between different activities that people engage in along the Riverfront. For example, the human activity recognition software classifies human activities into one of four categories: gestures, interactions with other people of objects, actions like walking or running, and group activities.
By understanding how areas of the Riverfront are used, Lynch’s team is able to provide recommendations to the DRFC about where to add amenities like benches and lights and to provide access. When changes are implemented, they can then test in real time the effectiveness of these changes.
The goal of this project is to explore seamless and independent mobility for people with physical disabilities.
The project aims to reduce energy use of vehicular travels by incentivizing individual travelers to adjust travel choices and driving behaviors.
A grassroots train-the-trainer program on how to install, operate and maintain faucet-mounted point-of-use filters to protect for lead in drinking water.
Rethinking how transit infrastructure can expand access to food, health, learning, and mobility services by creating multimodal hubs.
Collecting travel data to help Benton Harbor improve travel options for residents, with the goal of increased employment participation and retention.
Robots are anticipated to make the global construction industry safer and more attractive to workers, easing a worker shortage in the United States.
The goal of this project is to develop a data-driven asset management framework that quantifies risk in the water distribution network for southeast Michigan.
Mapping detailed geographies of digital access and exclusion across Detroit’s neighborhoods.
A major source of bridge deterioration requiring constant maintenance is mechanical expansion joints installed between adjacent simple span bridge decks.
Application of real-time sensing and dynamic control on existing wastewater infrastructure to reduce the frequency and volume of Combined Sewer Overflows.
Structural monitoring of highway retaining walls using remote sensing techniques to assess performance and prioritize infrastructure investments.
Using wearable-based technology to help seniors stay mobile and age in place, while avoiding exposure to falls and environmental risks or hazards.
The Urban Collaboratory is working with the USEPA and the Great Lakes Water Authority to remediate and restore the Rouge River.
Recommendations were developed to promote regional planning to ensure infrastructure investments are equitable and result in high-quality drinking water.
While parks are designed and managed to generate community benefits, there remains a need for tools that can more rigorously measure how communities use parks.
The city of Benton Harbor wishes to transform Ox Creek into a residential, recreational and commercial centerpiece linking important segments of the community.
The University of Michigan is developing a structural reliability framework to quantify the probability of failure of pipe segments throughout the GLWA system.
A PFAS treatment approach for groundwater using low-temperature plasma with a concentration phase
The Great Lakes Water Authority is looking for ways to rehabilitate large diameter water mains without actually having to dig up city streets.
The Sensors in a Shoebox project focuses on empowering Detroit youth as agents of change for their city.
The first in a series of health clinic prototypes that bring technology-enabled chronic health care monitoring to remote, underserved global populations.
Improving Benton Harbor’s aging water system using risk assessment and risk analysis techniques, as well as mobile sensors.
Donald Malloure Department Chair, Department of Civil and Environmental Engineering
Professor of Civil and Environmental Engineering
Professor of Electrical Engineering and Computer Science
Jerome P. Lynch, Ph.D. has been a member of the faculty at the University of Michigan since 2003. He was formerly the Donald Malloure Department Chair of Civil and Environmental Engineering. He was formerly a Professor of Civil and Environmental Engineering and a Professor of Electrical Engineering and Computer Science. In addition to his work as the Director of the U-M Urban Collaboratory Initiative, he is also the Director of the Laboratory for Intelligent Systems Technology (LIST). Dr. Lynch is now with Duke University.
Dr. Lynch’s work focuses on the boundary between traditional civil engineering and related engineering disciplines (such as electrical engineering, computing science, and material science), converting infrastructure systems into more intelligent and reactive systems through the integration of sensing, computing, and actuation technologies. These cyber-physcial systems (CPS) greatly enhance performance while rendering them more resilient against natural and man-made hazards.
Dr. Lynch completed his graduate studies at Stanford University where he received his Ph.D. in Civil and Environmental Engineering in 2002, M.S. in Civil and Environmental Engineering in 1998, and M.S. in Electrical Engineering in 2003. Prior to attending Stanford, Dr. Lynch received his B.E. in Civil and Environmental Engineering from the Cooper Union in New York City. He has co-authored one book and over 200 articles in peer reviewed journal and conferences. Dr. Lynch has been awarded the 2005 ONR Young Investigator Award, 2009 NSF CAREER Award, 2009 Presidential Early Career Award for Scientists and Engineers (PECASE), 2012 ASCE EMI Leonardo da Vinci Award and 2014 ASCE Huber Award.