EAGER: Safer Connected Communities Through Integrated Data-driven Modeling, Learning, and Optimization
Lead PI:
Viktor Prasanna
Abstract
Crime is a major problem in many urban communities. This project focuses on developing a framework for increased security and crime prevention in crime-prone environments by identifying and integrating hitherto disaggregated heterogeneous data and analyzing the causal and spatio-temporal interconnections between constituent parts of a connected community including environmental aspects (i.e., traffic, lighting, poverty levels, business proximity such as banks/ATMs), crime history, and social events.
Performance Period: 08/15/2016 - 07/31/2018
Institution: University of Southern California
Sponsor: National Science Foundation
Award Number: 1637372
Distributed Data Analytics for Real-Time Monitoring and Detection of Flash Floods in Smart City
Lead PI:
Array Array
Abstract
Distributed Data Analytics for Real-Time Monitoring and Detection of Flash Floods in Smart City Nirmalya Roy, University of Maryland Baltimore County Storms and floods cause 70% of the world's natural disasters. These natural disasters affect on average up to 200 million people in a year, with economic losses between US$50 billion to US$100 billion annually. Monitoring these flash flood prone areas proactively in populated areas and providing just-in-time notification to the city officials can help in effectively prioritizing, controlling, and mitigating such disastrous events.
Performance Period: 09/01/2016 - 08/31/2018
Institution: University of Maryland Baltimore County
Sponsor: National Science Foundation
Award Number: 1640625
CPS: Frontier: Collaborative Research: VeHICaL: Verified Human Interfaces, Control, and Learning for Semi-Autonomous Systems
Lead PI:
Sanjit Seshia
Co-PI:
Abstract

This NSF Cyber-Physical Systems (CPS) Frontier project "Verified Human Interfaces, Control, and Learning for Semi-Autonomous Systems (VeHICaL)" is developing the foundations of verified co-design of interfaces and control for human cyber-physical systems (h-CPS) --- cyber-physical systems that operate in concert with human operators. VeHICaL aims to bring a formal approach to designing both interfaces and control for h-CPS, with provable guarantees.

Performance Period: 09/01/2016 - 08/31/2024
Institution: University of California-Berkeley
Sponsor: National Science Foundation
Award Number: 1545126
CPS: Breakthrough: Wearables With Feedback Control
John Stankovic
Lead PI:
John Stankovic
Abstract
Recently there is an increasing availability of smart wearables including smart watches, bands, buttons and pendants. Many of these devices are part of human-in-the-loop Cyber Physical Systems (CPS). With future fundamental advances in the intersection of communications, control, and computation for these energy and resource limited devices, there is a great potential to revolutionize many CPS applications.
Performance Period: 09/01/2016 - 08/31/2019
Institution: University of Virginia Main Campus
Sponsor: National Science Foundation
Award Number: 1646470
CPS: Breakthrough: From Whole-Hand Tactile Imaging to Interactive Simulation
Lead PI:
Yon Visell
Abstract
This project aims to enable cyber-physical systems that can be worn on the body in order to one day allow their users to touch, feel, and manipulate computationally simulated three-dimensional objects or digital data in physically realistic ways, using the whole hand. It will do this by precisely measuring touch and movement-induced displacements of the skin in the hand, and by reproducing these signals interactively, via new technologies to be developed in the project.
Performance Period: 09/01/2015 - 12/31/2018
Institution: University of California-Santa Barbara
Sponsor: National Science Foundation
Award Number: 1628831
Integrated Safety Incident Forecasting and Analysis
Yevgeniy Vorobeychik
Lead PI:
Yevgeniy Vorobeychik
Co-PI:
Abstract
The objective of this research is to understand and improve the resource coordination and dispatch mechanisms used by first responders in smart and connected communities. In prior art, as well as practice, incident forecasting and response are typically siloed by category and department, reducing effectiveness of prediction and precluding efficient coordination of resources.
Yevgeniy Vorobeychik

Yevgeniy Vorobeychik is an Assistant Professor of Computer Science and Computer Engineering at Vanderbilt University. Previously, he was a Principal Member of Technical Staff at Sandia National Laboratories. Between 2008 and 2010 he was a post-doctoral research associate at the University of Pennsylvania Computer and Information Science department. He received Ph.D. (2008) and M.S.E. (2004) degrees in Computer Science and Engineering from the University of Michigan, and a B.S. degree in Computer Engineering from Northwestern University. His work focuses on game theoretic modeling of security, algorithmic and behavioral game theory and incentive design, optimization, complex systems, epidemic control, network economics, and machine learning. Dr. Vorobeychik has published over 60 research articles on these topics. Dr. Vorobeychik was nominated for the 2008 ACM Doctoral Dissertation Award and received honorable mention for the 2008 IFAAMAS Distinguished Dissertation Award. In 2012 he was nominated for the Sandia Employee Recognition Award for Technical Excellence. He was also a recipient of a NSF IGERT interdisciplinary research fellowship at the University of Michigan, as well as a distinguished Computer Engineering undergraduate award at Northwestern University.

Performance Period: 09/01/2016 - 08/31/2018
Institution: Vanderbilt University
Sponsor: National Science Foundation
Award Number: 1640624
CRII: CPS: Towards Reliable Cyber-Physical Systems using Unreliable Human Sensors
Lead PI:
Dong Wang
Abstract
A growing number of Cyber-Physical Systems (CPS) domains, such as environment, transportation, energy, and disaster response, involve humans in non-trivial ways. Humans act as sensors in these scenarios when they contribute data (either directly or via sensors they own) that a CPS application can use. Using humans as sensors (commonly known as social sensing or crowdsensing) is an emerging paradigm, which provides unprecedented opportunities to sense the physical world in an inexpensive, versatile and scalable manner.
Performance Period: 05/01/2016 - 04/30/2019
Institution: University of Notre Dam
Sponsor: National Science Foundation
Award Number: 1566465
CPS: TTP Option: Breakthrough: Collaborative Sensing: An Approach for Immediately Scalable Sensing in Buildings
Lead PI:
Cameron Whitehouse
Abstract
Buildings are complex systems with profound impact on human health, productivity, comfort, and energy consumption. Smart building technology promises to improve many aspects of building operation by applying sensor data toward more informed and precise building operation. Smart buildings are one important dimension of enabling sustainable Smart Cities. One of the challenges in smart buildings is the selection, placement, and installation of multiple sensors in the building. This can be both an expensive and time consuming process.
Performance Period: 10/01/2016 - 09/30/2019
Institution: University of Virginia Main Campus
Sponsor: National Science Foundation
Award Number: 1646501
EAGER: Congestion Mitigation via Better Parking: New Fundamental Models and A Living Lab
Lead PI:
Baosen Zhang
Co-PI:
Abstract
This EAGER project on Smart and Connected Communities focuses on developing new fundamental models of urban parking in order to address issues of congestion that negatively impact mobility and health. Traffic congestions are increasingly becoming bottlenecks to sustainable urban growth as infrastructures are being stretched to their limits. A significant amount-up to 40%-of all surface level traffic in urban areas stems from drivers looking for parking.
Performance Period: 07/01/2016 - 06/30/2018
Institution: University of Washington
Sponsor: National Science Foundation
Award Number: 1634136
CAREER: Hierarchical Control for Large-Scale Cyber-Physical Systems
Lead PI:
Wei Zhang
Abstract
Many complex engineering systems involve interactions among a large number of agents with coupled dynamics and decisions due to their shared environment and resources. Such systems are often operated using a hierarchical architecture, where a coordinator determines some macroscopic control signal to steer the population to achieve a desired group objective while respecting local preferences and constraints for individual agents. Examples include electricity demand response programs, ground and air transportation systems, data center power management, robotic networks, among others.
Performance Period: 08/01/2016 - 07/31/2021
Institution: Ohio State University
Sponsor: National Science Foundation
Award Number: 1552838
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