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