Current CenSCIR Research Projects



Sensor Andrew - In late 2006 CenSCIR researchers will begin to design and implement a campus-wide testbed for new sensing technologies and applications. The project's goal will be to make Carnegie Mellon one of the most "sensed" campuses in the world. By mid-2007, Carnegie Mellon researchers will have access to a "living testbed" of sensors and sensed data to provide a platform for future research.
sensor_andrew.html




The goal of SPIRAL is to push the limits of automation in software and hardware development and optimization for digital signal processing (DSP) algorithms and other numerical kernels beyond what is possible with current tools.
http://www.spiral.net or http://www.ece.cmu.edu/~moura/


Critters: Pervasive Sensor Networks

The Critters project is helping to build CMU as The Most Sensed Campus by pervasively deploying thousands of sensors around campus.
http://www.sensornets.org/


Time Reversal Imaging

Time reversal techniques obtain increased resolution by exploiting scattering and multipath in propagation through inhomogeneous channels. Time reversal has been used by Fink and collaborators to achieve super-resolution focusing in acoustics, [Fink, Prada, Wu, Cassereau, 1989,Fink, 1997] as demonstrated by their work with controlled ultrasonic experiments in water tanks. More recently large-scale acoustics experiments in the ocean have confirmed the resolution ability of time reversal, [Kuperman, Hodgkiss, and Song, 1998,Song, Kuperman, Hodgkiss, Akal, and Ferla, 1999]. In our work, we study matched field detection with time reversal in the electromagentic (EM) domain. In classical matched field processing (MFP), in the acoustical domain, e.g., [Baggeroer, Kuperman, Mikhalevsky, 1983], detailed modeling of the channel is used to predict the field as received by an array of sensors, after the wavefield propagates through an inhomogenous channel. MFP, in simple terms, solves an inverse problem (source detection or location) by steping through a sequence of forward problems, where in each forward problem the unknown location of the source is postulated at each one of potential positions. Practical implementation of MFP implies the solution of the wave equation for each forward problem assuming a given channel velocity propagation profile and given boundary conditions. This is computationaly demanding and requires good knowledge of the environmental conditions, both of which make MFP an expensive, sensitive solution for many practical problems. Time reversal provides a very good alternative to MFP, since it avoids the detailed modeling of the channel, while still providing the potential gain from matching to the propagated field, rather than matching to the original transmitted wavefield. In a sense, time reversal provides the actual channel Greens' function, in contrast with MFP where the channel Greens' function is computed from the model.
http://www.ices.cmu.edu/censcir/time%20reversal%20project/TRimagingWebSite.htm




Multi-Disciplinary Research to Exploit Motor Vehicle Information and Communications Technology
The goal of this project is to explore possible uses of motor vehicle sensor information for large scale social/infrastructure purposes. Technology already exists to capture and communicate a variety of information from motor vehicles. Automobiles are equipped with sensors and can reliably report their location, velocity, and condition via cellular telecommunications. Truck location tracking with global positioning systems is common. Prototype systems exist for characterizing surrounding traffic and roadway condition. Given these advancements, we expect that future motor vehicles will be capable of reporting a wide variety of information about their own condition and the local environment, including the condition of the infrastructure that they are on.
http://www.ce.cmu.edu/~transport/index.html


Product & Process Modeling for Embedded Commissioning

Automation of Building Commissioning (BC) has many benefits and advantages. There are several automated product and process models for the building industry that are under development, such as the Industry Foundation Classes (IFC) by the Industry Alliance for Interoperability (IAI). These models have yet to be interfaced with the building commissioning phase. In this project, we develop a robust understanding of the information that needs to be represented in these building product and process models; study the IFCs to determine the extent to which they address commissioning, and designed and implemented a test rig to determine the degree to which IFCs data models support building commissioning information.




This co-study between the Carnegie Mellon University and The University of Maryland intends to explore and formalize the information dependency patterns in network forms of organizations in construction project management and crisis management fields. In construction projects, information is critical for seamless and cost-effective operations. Communication of project information and coordination of information exchanges between different project participants are essential for a project's success. On the other hand, a better understanding of information dependencies between participants is of utmost importance for strategic choices on information technology (IT) applications since decisions on IT investments greatly influence the effectiveness of not only internal communications within a project team, but also the interactions of the project team with other project-related organizations.
http://www.ce.cmu.edu/~ess/




Recent advances in generating 3D environments using laser scanning technologies, and collecting quality information about built environments using embedded and other advanced sensors, create an opportunity to explore the feasibility of frequently collecting three-dimensional and quality related as-built data. The current trends in the A/E/C industry for the use of integrated project models have also shown that a semantically rich integrated project database can support various project management and facility management functions. This research project builds on, combines and extends these advances in developing an automated early defect detection system.
http://www.ce.cmu.edu/~itr/


Development of a Formalism and Framework for Sensing System Design for Inspection of Construction Sites

Sensing systems (collections of technologies configured to measure, store, compute, transmit, receive, and analyze data from the field) are increasingly practical tools for construction inspection. However, those who make decisions based on the status of the built environment (such as inspectors, contractors, maintenance technicians, and owners) currently cannot adequately compare possible technologies for inspection tasks or make site-level decisions about the infrastructure needed for inspection during a construction project.
http://www.ce.cmu.edu/~itr/info/IndividualResearches/Chris/embeddedsensor.html


Formalization of Life-Cycle Data Management of Precast Components Using Advanced Tracking Technologies

Material related information is not readily available in construction supply chains which results in inefficiencies in material flow e.g. wrong deliveries, lost materials. Unavailability of material information is even more problematic for engineered-to-order (ETO) components since ETO components (e.g. precast, pipe spools) are highly customized having numerous component-related information items, have long lead times, and usually on the critical path in construction schedules. Advanced tracking technologies, such as radio frequency identification, can enable streamlined information flow by storing some of the component-related information on a chip attached to component and by communicating this information to different parties as the component moves through a supply chain. These advanced tracking technologies enable the components become intelligent by storing information about their identities, handling, storage and installation instructions and other important information on the component itself. This information can be communicated to different databases of different companies on an as needed basis. However, to utilize these technologies, information items that need to be stored and transferred have to be identified, and exchange needs have to be determined.
http://www.ce.cmu.edu/~eergen/Research.htm




In the modern Architecture, Engineering and Construction (AEC) industry, more and more data are available because advanced technologies offer a great ability to collect and store data. However, the uses of these data or the knowledge that can be retrieved from these data are still a relatively undiscovered area. To explore and accumulate related research efforts on the domain knowledge discovery and reuse problem, we established the Construction Knowledge Discovery and Dissemination (CKDD) Group in 1998 and we have continuously worked with other research teams to focus research interests on three types of subjects: Data Mining on traditional database systems, Text Mining, and Image Reasoning as they relate to the AEC industry.
http://www.ce.cmu.edu/~lucio/research/index.html


Large-Area Biosensing Electronics

The goal of this project is the development of low-cost sensing systems capable of multiple simultaneous analyses of biological systems. These sensing systems will be applied to the electronic detection of cell motion and/ or cell division. Information obtained electronically will be used directly or in combination with microscopic techniques. Sensing is based on the use of large-area microelectronic fabrication techniques, which will ensure low cost, disposability, redundancy, accuracy, and high speed data collection. A direct interface with digital electronics will facilitate rapid analysis and throughput at least an order of magnitude higher than existing techniques (which will lead to improved productivity in pharmaceutical and biological research). We have developed an array for live cell screening (referred to as LCAST, for Live Cell Array Sensing Technology) which will make it possible to perform direct electrical sensing of cell motility and/or division.
http://www.ece.cmu.edu/%7Edwg/research/bio.html


Infrastructure Sensing for Crack Detention

This work is directed at the development of sensors for infrastructure applications. Examples include the detection of cracks using ultrasonic waves; detection of acoustic emissions from crack propagation; and measurement of chloride concentrations in concrete.
http://www.ece.cmu.edu/%7Edwg/research/weld.html



Proactively Reconfigurable, Adaptive, Reliable Middleware (MEAD) and MEAD-Lite: Fault-tolerant Middleware for Embedded Sensor Networks


The MEAD system aims to enhance distributed middleware applications with new capabilities such as (i) transparent, yet tunable, fault tolerance with configurable performance and timing guarantees, (ii) proactive dependability, (iii) resource-aware system adaptation to crash, communication and timing faults with (iv) scalable and fast fault-detection and fault-recovery. As a part of the research on MEAD, we are investigating failure prediction, zero-downtime software upgrades, automated finger pointing in distributed systems, and resource-constrained (embedded) survivability.
http://www.ece.cmu.edu/~mead/


Trinetra - Assistive Technologies for the Blind

Trinetra aims to develop cost-effective assistive technologies to provide blind people with a greater degree of independence in their daily activies. The overall objective of the project is to improve the quality of life for the blind by harnessing the collective capability of diverse networked embedded devices to support navigation, grocery shopping, transportation, etc. To date, we have researched and developed a portable barcode-based solution involving an Internet- and Bluetooth-enabled cell phone to aid grocery shopping at the CMU campus convenience store, Entropy. We have also more recently extended this to assist the blind and visually impaired with their transportation needs, specifically, for the CMU campus shuttle.
http://www.ece.cmu.edu/~trinetra/index.html





Interested?

To learn more about CenSCIR's work, please contact Matt Sanfilippo at (412) 268-8859 or by e-mail at mattsanf@andrew.cmu.edu