Overcoming Social and Technical Barriers for the Broad Adoption of Smart Stormwater Systems
Lead PI:
Branko Kerkez
Co-Pi:
Abstract

In the age of the self-driving car, what role can autonomous technologies play in improving water systems? Floods are the leading cause of severe weather fatalities across the United States. Furthermore, large quantities of metals, nutrients, and other pollutants are washed off during storm events, making their way via streams and rivers to lakes and costal zones. To contend with these concerns, most communities across the United States maintain dedicated infrastructure (pipes, ponds, basins, wetlands, etc.) to convey and treat water during storm events. Much of this stormwater infrastructure is approaching the end of its design life, which results in more flooding and degraded water quality. Instead of building new and bigger stormwater infrastructure, which is cost prohibitive for many communities, it is possible to use existing infrastructure more effectively. The goal of this proposal is to enable the next generation of smart and connected stormwater systems, which use sensors to anticipate changes in weather and the urban landscape, and adapt their operation using active flow controls (e.g., gates, valves, pumps). This will drastically improve community resilience to floods and water quality. Equipping stormwater systems with low-cost sensors and controllers will provide a cost-effective solution to transform infrastructure from static to adaptive, permitting it to be automated and instantly reconfigured to respond to changing community needs and preferences. This research will address a truly national-scale infrastructure challenge and will lay the foundation upon which to empower and educate communities to adopt smart and autonomous stormwater solutions.

The research to enable "smart" stormwater systems will be conducted by a team of engineers, social scientists, computer scientist and environmental experts in tight collaboration with decision makers and citizens across four communities in the United States. The team will close fundamental knowledge gaps to explain (1) to what extent real-time control can improve the hydraulic and water quality performance of individual stormwater sites, (2) how to identify and overcome the barriers that public perception poses to the adoption of smart stormwater systems, and (3) how system-level interoperability can be achieved to guarantee safe and effective performance at the scale of entire communities (100s to 1000s of controlled sites). This will be achieved through three closely coupled scientific objectives, which will include testing of laboratory models of control sites, field-scale water quality studies, the formation of community advisory groups, the analysis of residential surveys in each community, and the stability analysis of system-level control algorithms under various sources of uncertainty. The approach is thus fundamentally motivated around the goal of scalability, as the results will be relevant to many communities across the United States, regardless of their size. By open-sourcing the efforts on Open-Storm.org and other public forums, the project will also support research capacity-building by reducing the overhead required by others to deploy smart and connected stormwater systems.

Branko Kerkez
Branko Kerkez is the Arthur F. Thurnau Associate Professor of Civil and Environmental Engineering at the University of Michigan. His research interests include water, data, and sensors. His group is working to enable smart water systems, which autonomously adapt themselves to changing conditions using real-time data and controls. His research projects have spanned wireless sensing of large mountain basins, real-time flood forecasting, robotics, and real-time control algorithms for water systems. He is the founder of Open-Storm.org, an open-source consortium dedicated to freely sharing hardware, software, and case studies on smart water systems. He received his M.S. and Ph.D. in Civil and Environmental Engineering, and an M.S. in Electrical Engineering and Computer Science, all from UC Berkeley. He is a recipient of the National Science Foundation’s CAREER award and was recognized by National Academy of Engineering as a Gilbreth Lecturer.
Performance Period: 09/01/2017 - 08/31/2022
Institution: Regents of the University of Michigan - Ann Arbor
Sponsor: National Science Foundation
Award Number: 1737432

MSU leads new $1.7 million research project to help disadvantaged communities confronting wildfires and related cascading hazards

MSU leads new $1.7 million research project to help disadvantaged communities confronting wildfires and related cascading hazards

STARKVILLE, Miss.—An interdisciplinary team led by Mississippi State researchers is receiving a $1.7 million grant to better equip emergency planners and other stakeholders to reduce the vulnerability of disadvantaged communities to the impacts of wildfires and related cascading hazards such as mudslides, landslides and flooding.

Submitted by Amy Karns on

Virginia Tech researchers garner NSF grant to connect AI with urban planning to improve decision making and service delivery

Virginia Tech researchers garner NSF grant to connect AI with urban planning to improve decision making and service delivery

Tom Sanchez, professor of urban affairs and planning, and Chris North, professor of computer science and associate director of the Sanghani Center for Artificial Intelligence and Data Analytics, have been awarded a planning grant from the National Science Foundation’s Smart and Connected Communities program.

Submitted by Amy Karns on

Digital City Testbed Center Lands NSF Grant to Study Climate Change Mitigation, Technology and Diverse Communities

Digital City Testbed Center Lands NSF Grant to Study Climate Change Mitigation, Technology and Diverse Communities

Portland State University’s Digital City Testbed Center (DCTC) recently received a $150,000 grant from the National Science Foundation’s “Smart and Connected Communities” program to explore why diverse communities — including people with disabilities, people with low income and BIPOC communities — are often hesitant to make use of digital technologies that could better prepare them for negative impacts of climate change.

Submitted by Amy Karns on

NSF Grant Will Support Creation of Chatbots to Gauge Pandemic’s Impact in Small Towns

NSF Grant Will Support Creation of Chatbots to Gauge Pandemic’s Impact in Small Towns

An interdisciplinary research team has received a National Science Foundation (NSF) grant to design and test a new generation of AI-driven conversational agents, or chatbots, for public data collection, with the goal of understanding the impact of the COVID-19 pandemic – and ultimately other large-scale crises – on small-town communities.

Submitted by Amy Karns on

Engineer with novel approach to urban mapping is first woman awarded prestigious Schnabel Award

Engineer with novel approach to urban mapping is first woman awarded prestigious Schnabel Award

BROOKLYN, New York, Weekday, February 23, 2022 – The Geo Institute (G-I) of the American Society of Civil Engineers is awarding one of its highest honors to a researcher at the NYU Tandon School of Engineering whose innovative approach to mapping structures and urban landscapes helps city planners and policy makers.

Submitted by Amy Karns on

How 3 Iowa Towns are Getting Smaller but Smarter through Iowa State Program

How 3 Iowa Towns are Getting Smaller but Smarter through Iowa State Program

A handful of Iowa communities and a group of Iowa State University researchers are trying to demonstrate that less can be more, and small can be vibrant. If you’re smart about it.

In an outgrowth of community surveys begun a quarter century ago, ISU researchers have identified what they call “Shrink Smart” communities. Like so many others, particularly smaller free-standing rural communities, they have steadily lost population since the 1980s recession and farm crisis.

Submitted by Amy Karns on

Shrink Smart program assists Iowa’s Shrinking Towns

Shrink Smart program assists Iowa’s Shrinking Towns

A handful of Iowa communities and a group of Iowa State University researchers are trying to demonstrate that less can, in fact, be more, and small can, in fact, be vibrant. If you’re smart about it.

In an outgrowth of community surveys begun a quarter century ago, ISU researchers have identified what they call “Shrink Smart” communities. Like so many others, particularly smaller free-standing rural communities, they have steadily lost population since the 1980s recession and farm crisis.

Submitted by Amy Karns on
Autonomy-enabled Shared Vehicles for Mobility on Demand and Urban Logistics
Lead PI:
Sertac Karaman
Abstract

Three emerging technologies provide unique opportunities for denser cities throughout the developed world: vehicle sharing, electric vehicles, and autonomous systems. Bringing these technologies close together can help enable joint mobility-on-demand and urban-logistics services. This project focuses on the co-development of design and algorithms to enable new concepts that will serve this purpose. The Persuasive Electric Vehicle (PEV) is a tricycle navigating in the bike lanes. The PEV can autonomously drive itself to its next customer; it can also deliver packages to its customers who order goods online. On the algorithmic front, the project will investigate (i) provably-safe algorithms for autonomous navigation in bike lanes, and (ii) algorithms for high-performance routing and rebalancing for joint mobility on demand and urban logistics. On the design front, the project will investigate (i) the vehicle-level designs that can best embrace the relevant CPS technologies, and (ii) the system-level designs and urban planning practices that can help enable the PEV concept. The PIs will collaborate with the City of Boston and participate in the Global City Teams Challenge, where they will demonstrate the PEV concept and its potential impact on future smart cities.

Sertac Karaman
Sertac Karaman is an Associate Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology (since Fall 2012). He is the Director of the Laboratory for Information and Decision Systems (LIDS) - interdepartmental research center committed to advancing research and education in the analytical information and decision sciences. He has obtained B.S. degrees in mechanical engineering and in computer engineering from the Istanbul Technical University, Turkey, in 2007; an S.M. degree in mechanical engineering from MIT in 2009; and a Ph.D. degree in electrical engineering and computer science also from MIT in 2012. His research interests lie in the broad areas of robotics and control theory. In particular, he studies the applications of probability theory, stochastic processes, stochastic geometry, formal methods, and optimization for the design and analysis of high-performance cyber-physical systems. The application areas of his research include driverless cars, unmanned aerial vehicles, distributed aerial surveillance systems, air traffic control, certification and verification of control systems software, and many others. He delivered the the Robotics: Science and Systems Early Career Spotlight Talk in 2017. He is the recipient of an Amazon Faculty Award in 2020, IEEE Robotics and Automation Society Early Career Award in 2017, an Office of Naval Research Young Investigator Award in 2017, Army Research Office Young Investigator Award in 2015, National Science Foundation Faculty Career Development (CAREER) Award in 2014, AIAA Wright Brothers Graduate Award in 2012, and an NVIDIA Fellowship in 2011. He serves as the technical area chair for the Transactions on Aerospace Electronic Systems for the robotics area, a co-chair of the IEEE Robotics and Automation Society Technical Committee of Algorithms for the Planning and Control of Robot Motion. He serves on the Robotics: Science and Systems (RSS) Foundation Board and acts as the Secretary of the RSS Foundation. He is also co-founder of Optimus Ride, a Boston-based MIT-spinoff startup company that is developing self-driving vehicle technologies to enable accessible, equitable, safe and sustainable mobility for all.
Performance Period: 05/01/2015 - 10/31/2016
Institution: Massachusetts Institute of Technology
Sponsor: National Science Foundation
Award Number: 1523401
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