| Download the video (.wmv, 5.12M) Tracking Objects and Environments in Real-time
The trans-Alaska oil pipeline is more than 800 miles (1,300 km) long and
carries approximately 15 percent of the United State's domestic oil production.
Protecting every inch of the pipeline 24 hours a day is a monumental task,
according to a spokesman for Alyeska Pipeline Service Company.
In 1999, six employees of an oil company wrote to government officials
about the potential for a major disaster on the pipeline. "It won't be a single
gasket, or valve, or wire, or procedure, or person that will cause the
catastrophe," wrote the employees. "It will be a combination of small, perhaps
seemingly inconsequential events and conditions that will lead to the accident
that we're all dreading and powerless to prevent."
In an ideal world, a pipeline monitoring system would ensure leak
detection or prevention by monitoring factors such as flow, viscosity,
temperature and the surrounding environment. Such systems would also be
automated, affordable, and low-powered, since supplying power along a pipeline
is difficult, if not impossible. Most importantly, the system must be able to
communicate critical information in real-time to allow engineers to minimize
the effect of the leak, or prevent disaster. No system to date has been able to
meet these challenging requirements. But, researchers at Accenture Technology
Labs believe they may have a solution that combines tiny sensors called Smart
Dust, and a prototype called Sensor Aggregation Models. The prototype includes
a model of a pipeline, and shows how various emerging technologies can impact
the oil and forestry industries.
Sensor Revolution
Smart Dust is an emerging
technology, being developed at the University of California at Berkeley, which
will pack a sensor, power supply, analog circuitry, radio communication
capability and a programmable microprocessor all into a package the size of a
pinpoint. In its current form, the prototype is the size of a matchbox. But,
the Berkeley researchers predict that in less than two years it will be shrunk
down to Smart Dust size and will be inexpensive enough to scatter over a
forest, field or pipeline. In its final form, Smart Dust will be able to
identify, locate, power and organize itself into a communications network with
other sensors and transmit information.
Accenture believes that Smart Dust is just one part of a revolution,
marked by the proliferation of sensors in a variety of commercial environments
where inaccessible, vast or remote assets need to be tracked and managed. In
addition to being scattered over vast areas, these sensors can also be embedded
into objects and other materials, such as oil in a pipeline, paint on a bridge,
or a turbine blade on an aircraft.
Transforming Sensor Data into
Knowledge
Accenture Technology Labs developed Sensor Aggregation
Models to help manage and aggregate the data coming from potentially millions
of sensors. This application receives data wirelessly from the sensors and then
transforms individual data points into a cohesive, integrated view of the
environment. By summarizing data on the back end, and building visual models
with the data on the front end, the user can easily detect or investigate any
changes in the object—or the environment—as soon as they occur.
For example, if throughput in an oil pipeline slows, the application
reflects that with a change in color over the affected area. Or, if the
application notes a change in temperature along an area of the pipeline, the
user could zoom into that area to check other factors, such as air quality,
which may provide early warning of a possible gas leak. Global positioning
capabilities let the user see more, or pull back, adapting the granularity as
needed.
A commercial farm with thousands of acres could use this technology to
monitor crops in real-time from a remote location—including their growth rate,
light exposure, moisture conditions, air quality, nitrogen and phosphorous
levels, and pest control. The result? Higher yield, lower cost crops and fewer
chemicals introduced into the environment since pesticides can be applied
precisely where needed.
In addition to using a graphical representation, Sensor Aggregation
Models can feed into desktop applications such as Microsoft Excel, allowing
users to easily share critical information. When integrated with Web services,
Sensor Aggregation Models can easily be shared among many users, either within
an enterprise, or with third parties. For example, Web services would allow an
insurer to monitor the conditions and market value of assets under policy in
real time, in order to proactively manage risk.
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