With this initiative, we aim to help local schools, colleges and communities to increase creativity intelligence through a series of workshops, courses and activities. We will host distinguished guest lectures for the public. The advisory board members include world-renowned artists, writers, inventors and scientists such as Alba D'Urbano, Angelo Ciotti, Kevin Warwick and Michael Leyton. [more]
Our lab is integrating live data onto an interactive map of Pittsburgh. Over 200 live camera feeds placed throughout the Pittsburgh area will monitor weather conditions, emergency areas, water levels, bus locations, power consumption, pollution levels and traffic conditions. The result will be a dynamic, unified, user-friendly map that can be displayed on computers and mobile devices. [more]
VIS promotes green technology information in Pittsburgh. In this initiative, we will explore green alternatives to driving a car to work everyday. Points of interest include the cost benefit of telecommuting and rush hour alleviation. Our work includes bandwidth design, telecommuting desk design, video quality studies, corporate policy and tax-break incentives. [more]
VIS will develop affordable and wearable sensors that monitor human health and reduce medical costs. Our early work includes digital tongue diagnostics based on traditional Chinese medicine, motion sensors for the elderly to detect falls and alert relatives. The next generation sensors will integrate more sensing capacity and will interface with cellphones and remote diagnostic centers. [more]
VIS is developing improved methodology for detecting counterfeit money at local banks and supermarkets in collaboration with the US Secret Service and FBI. [more]
Three years ago, VIS successfully restored headstone names for St. Luke Church--a historic 200 year-old site--located in Carnegie, PA. Since then, our lab has received many inquiries for help. We will implement cutting-edge 3D imaging, scanning and reconstruction technology for other endangered landmarks. [more]
Advanced video surveillance systems create large overheads by presenting too much information. This overload creates problems in a situation where there is insufficient bandwidth and attention given to the set being processed. Over 99% of data fed into the control room is wasted. This project seeks to minimize the wireless video network throughput while maximizing the video quality with multiple resolutions on demand. [more]
Recent innovations have created a 3-D millimeter wavelength imaging system to be used in full-body scanners. This technology has raised privacy concerns since the scanner produces an almost naked image of the subject. This project aims at creating algorithms that blur private parts but reveal weapons. [more]
The team of VIS developed new software to scan 200-year-old gravestones at Old St. Luke's Church in nearby Carnegie, PA to help an Episcopal pastor identify all the names on the cemetery's tombstones. [more]
This project aims at developing a semantic object detection system for real-time video processing as the event happens, as well as afterwards. This will greatly reduce network data traffic and evidence retrieving time. Since data is presented on-demand, our solutions will preserve privacy by minimizing data emissions. [more]
This project uses Bayesian modeling and a computer vision based object tracking algorithm to monitor the harmful algae across regions. Based on databases of historical data and current physical and biochemical conditions, we seek to base our predictions of a set of events at a particular time and location. Our goal is to incorporate this model for algae blooms with operational monitoring and prediction systems in the field. [more]
This project aims at using sound classification in developing affordable sensing technology for monitoring physical intrusions. The goal is to classify sound patterns from natural environments, such as cars, trucks, airplanes, etc. This project has far reaching consequences for medical diagnostics and safety alert systems. [more]
Growing sensor webs create problems for indoor wireless self-positioning. Real-time wireless device self-position is essential for locating and tracking wireless users. This project aims to enable an affordable 802.11 RSSI-based positioning technology and demonstrate its capability with existing facilities in the Carnegie Mellon Andrew wireless network. [more]
This project aims at creating solutions for affordable wireless video streaming over long distances while ensuring a smooth video signal handover along the 802.11g access. This would enable technologies for distributed video network protocols and streaming. [more]
Inverse Physics is the process of retrieving physical properties from observations. The objective of this study is to build an embedded data mining processor for onboard physical property retrieving, which would significantly reduce the cost of physical inversion for combined observations. [more]
