Abstract: Large scale applications of cyber physical systems (CPS) such as commercial buildings with Building Automation System (BAS)-based demand response (DR) can play a key role in alleviating demand peaks and associated grid stress, increased electricity unit cost, and carbon emissions. However, benefits of BAS alone are often limited because their demand peak reduction cannot be maintained long enough without unduly affecting occupant comfort.

Abstract: Overview: The human cost of transportation in the US reaches an unnecessary 33000 fatalities and 2.2 million injuries every year. The inefficiency of road transportation also burdens our economy, with only the cost of fuel wasted in traffic reaching $88 billion a year.

Abstract: GRID 2020: The power grid in the U.S. and many regions of the world is undergoing changes because of new technologies and government mandates. It is believed that smart meters and a smarter grid will lead to more efficient use of our infrastructure. In addition, increased renewable energy integration will provide power at low cost.

Abstract: Cyber-Physical Systems (CPS) promise to change how we study and interact with physical world. CPS use sensors and actuators connected to an autonomic cyberinfrastructure. A key requirement for having dependable CPS is the correct calibration of their sensors. Unfortunately, the current state of the art is to calibrate sensors in laboratories, often manually. Moreover, commodity sensor precision degrades over time.  Consequently, sensors must be periodically recalibrated.

Abstract: The goal of this project is to develop fundamental theory, computationally efficient algorithms, and real-world experiments for the analysis and design of safety-critical cyber-physical transportation systems with human operators. To this end, we propose a modeling, theoretical, and experimental collaborative effort combining human factors, control theory, and computer science. As crashes at traffic intersections account for about 40% of overall vehicle crashes, we will focus on intersection crashes in this project.

Abstract: Many practical barriers continue to exist for a blind individual who strives to live an independent and active life, despite decades of development of assistive technologies. This project addresses the following two most prominent challenges: (1) disparity in information-sharing among people with visual impairment and its limited understanding by the research community; and (2) lack of methods and tools for effectively addressing the disparity.

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Abstract: Motivation: Energy infrastructure is a critical underpinning of modern society. To ensure its reliable operation, a nation-wide or continent-wide situational awareness system is essential to provide high-resolution understanding of the system dynamics such that proper actions can be taken in real-time in response to power system disturbances and to avoid cascading blackouts. The power grid represents a typical highly dynamic cyber-physical system (CPS).

Abstract: In order to improve the current capabilities of automotive active safety control systems (ASCS) one needs to take into account the interactions between driver/vehicle/ASCS/environment. To achieve this goal, this research will infer longterm and short-term driver behavior via the use of Bayesian networks and neuromorphic algorithms to estimate the driver’s skills and current state of attention from eye movement data, together with dynamic motion cues obtained from steering and pedal inputs.

Abstract: Data-driven intelligence is an essential foundation for physical systems in transportation safety and efficiency, area surveillance and security, as well as environmental sustainability. While sophisticated data analysis and synthesis can be well supported in large data centers, future intelligent systems require on-the-scene processing with faster responses and less dependence on the unreliable (often wireless) data communications in the field.