Abstract
This work examines how to get safety and security in Internet of Things (IoT) systems where multiple devices (things), each designed in isolation from others, are brought together to form a networked system, controlled via one or more software applications ("apps"). "Things" in an IoT environment can include simple devices such as switches, lightbulbs, smart locks, thermostats, and safety alarms as well as complex systems such as appliances, smartphones, and cars.
Performance Period: 01/01/2017 - 12/31/2019
Institution: University of Michigan Ann Arbor
Sponsor: National Science Foundation
Award Number: 1646392
Abstract
This research investigates a cyber-physical framework for scalable, long-term monitoring and maintenance of civil infrastructures. With growth of the world economy and its population, there has been an ever increasing dependency on larger and more complex networks of civil infrastructure as evident in the billions of dollars spent by the federal, state and local governments to either upgrade or repair transportation systems or utilities. Despite these large expenditures, the nation continues to suffer staggering consequences from infrastructural decay.
Performance Period: 09/01/2016 - 08/31/2020
Institution: Washington University in St. Louis
Sponsor: National Science Foundation
Award Number: 1646380
CPS: Breakthrough: Secure Interactions with Internet of Things
Lead PI:
Kang Shin
Abstract
The objective of this research is to (1) gain insights into the challenges of securing interactions in Internet of Things (IoT)deployments, (2) develop a practical framework that mitigates security and privacy threats to IoT interactions, and (3) validate the proposed framework in a medium-scale IoT testbed and through user studies. The emerging IoT computing paradigm promises novel applications in almost all sectors by enabling interactions between users, sensors, and actuators.
Performance Period: 10/01/2016 - 09/30/2019
Institution: University of Michigan Ann Arbor
Sponsor: National Science Foundation
Award Number: 1646130
Abstract
Scaling the Internet of Things (IoT) to billions and possibly trillions of "things" requires transformative advances in the science, technology, and engineering of cyber-physical systems (CPS), with none more pressing or challenging than the power problem. Consider that if every device in a 1 trillion IoT network had a battery that lasted for a full five years, over 500 million batteries would need to be changed every day. Clearly, a battery-powered IoT is not feasible at this scale due to both human resource logistics and environmental concerns.
Performance Period: 09/15/2016 - 08/31/2019
Institution: Pennsylvania State University
Sponsor: National Science Foundation
Award Number: 1646399
Abstract
By 2050, 70% of the world's population is projected to live and work in cities, with buildings as major constituents. Buildings' energy consumption contributes to more than 70% of electricity use, with people spending more than 90% of their time in buildings. Future cities with innovative, optimized building designs and operations have the potential to play a pivotal role in reducing energy consumption, curbing greenhouse gas emissions, and maintaining stable electric-grid operations.
Performance Period: 09/01/2016 - 08/31/2018
Institution: University of California-Riverside
Sponsor: National Science Foundation
Award Number: 1637258
Abstract
Advances in the effective integration of networked information systems, sensing and communication devices, data sources, decision making, and physical infrastructure are transforming society, allowing cities and communities to surmount deeply interlocking physical, social, behavioral, economic, and infrastructural challenges. These novel socio-technical approaches enable increased understanding of how to intelligently and effectively design, adapt, and manage Smart and Connected Communities (S&CC).
Performance Period: 04/15/2016 - 03/31/2019
Institution: University of Washington
Sponsor: National Science Foundation
Award Number: 1624193
Project URL
Project URL
Abstract
Inadequate system understanding and inadequate situational awareness have caused large-scale power outages in the past. With the increased reliance on variable energy supply sources, system understanding and situational awareness of a complex energy system become more challenging. This project leverages the power of big data analytics to directly improve system understanding and situational awareness.
Performance Period: 08/24/2016 - 08/31/2018
Institution: New Jersey Institute of Technology
Sponsor: National Science Foundation
Award Number: 1660025
CAREER: Theoretical Foundations of the UAS in the NAS Problem (Unmanned Aerial Systems in the National Air Space)
Lead PI:
Kristin Yvonne Rozier
Abstract
Due to their increasing use by civil and federal authorities and vast commercial and amateur applications, Unmanned Aerial Systems (UAS) will be introduced into the National Air Space (NAS); the question is only how this can be done safely. Today, NASA and the FAA are designing a new, (NextGen) automated air traffic control system for all aircraft, manned or unmanned. New algorithms and tools will need to be developed to enable computation of the complex questions inherent in designing such a system while proving adherence to rigorous safety standards.
Performance Period: 02/15/2016 - 11/30/2016
Institution: University of Cincinnati
Sponsor: National Science Foundation
Award Number: 1552934
Abstract
Software-Defined Control (SDC) is a revolutionary methodology for controlling manufacturing systems that uses a global view of the entire manufacturing system, including all of the physical components (machines, robots, and parts to be processed) as well as the cyber components (logic controllers, RFID readers, and networks). As manufacturing systems become more complex and more connected, they become more susceptible to small faults that could cascade into major failures or even cyber-attacks that enter the plant, such as, through the internet.
Performance Period: 09/01/2016 - 08/31/2021
Institution: Cornell University
Sponsor: National Science Foundation
Award Number: 1544613
Abstract
Software-Defined Control (SDC) is a revolutionary methodology for controlling manufacturing systems that uses a global view of the entire manufacturing system, including all of the physical components (machines, robots, and parts to be processed) as well as the cyber components (logic controllers, RFID readers, and networks). As manufacturing systems become more complex and more connected, they become more susceptible to small faults that could cascade into major failures or even cyber-attacks that enter the plant, such as, through the internet.
Dawn Tilbury
Dawn M. Tilbury received the B.S. degree in Electrical Engineering, summa cum laude, from the University of Minnesota in 1989, and the M.S. and Ph.D. degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley, in 1992 and 1994, respectively. In 1995, she joined the faculty of the University of Michigan, Ann Arbor, where she is currently Professor of Mechanical Engineering with a joint appointment in Electrical Engineering and Computer Science. In January 2014, she became Associate Dean for Research and Graduate Education. Her research interests lie broadly in the area of control systems, including applications to robotics, manufacturing, and healthcare. She was Program Chair of ACC 2012 and will be General Chair of ACC 2014. She is a life member of SWE, and Fellow of ASME and IEEE.
Performance Period: 09/01/2016 - 08/31/2021
Institution: University of Michigan Ann Arbor
Sponsor: National Science Foundation
Award Number: 1544678