International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004
The gateway wirelessly connects to the nodes and connects to
the GeoSWIFT server through the Internet. The gateway is
composed of an MICA2 mote plugged into an interface board
which connects to a PC through RS232 based serial interface.
A wireless sensor network of four MICA2 motes with sensor
boards has been tested and deployed at York University.
Currently, these MICA2 are stationary sensors that performing
sensing tasked at fixed locations. Locations can be acquired by
additional devices such as a GPS receiver when the sensors are
initially deployed in the field. In the very near future when
localization techniques of sensor networks become more mature,
the sensor web will have a lot of mobile sensors as moving
agents to collect on-demand field measurements upon requests.
An open geospatial sensing service, such as GeoSWIFT service,
will become the information centre to control, manage, display
and analyse the locations and observations of these widely
distributed moving sensors.
2.2.2 External Sensor Observation Sources:
There are a lot of sensor networks geographically distributed all
over the world and continuously collecting data. We have seen
the development and evolution of World Wide Web. Since
sensor web shares a lot of similarity with WWW, we envision
that those existing sensor networks will be integrated into
sensor web and sensor web will become a worldwide storage
and exchanging center of the sensing resources.
Thus, we tested and integrated several existing sensor networks
into GeoSWIFT. We have seen that some of the sensing
information is already available online, such as Environment
Canada's Climate Online, USGS's NEIC (National Earthquake
Information Center) for earthquakes, NOAA's METAR for
worldwide weather stations. Those existing Internet accessible
sensing resources have obstacles for integrated sensing, such as
sensor web, because these networks are using different transfer
protocols and encode jn proprietary data formats. Their data
are not interoperable, not human readable, and not machine
readable.
GeoSWIFT server retrieves the data from these sensing
information services through Internet, serves as a wrapper, and
provides a unified protocol (web service), an standard based
data formats (XML, GML) for sensor web users. In the current
integration, METAR and NEIC are the two external sensor
observations sources in this testbed. Through GeoSWIFT sever,
users don’t need to deal with the different protocols and data
formats of METAR and NEIC. By following the web service
standards and interfaces, users can concentrate in application
through collaboration and harmony between sensing resources.
223 Web Cams;
Low-cost off-the-shelf sensors, such as web cams, microphones
have become widely available. Those sensors can interface to
low-cost PCs which provide strong processing power and can
casily broadcast sensing observations (which are video, still
images, sounds, etc...) over the Internet. These sensors are
rich resources for the sensor web and can be applied to a lot of
applications, such as environmental monitoring and safety
surveillance. In this testbed, we tested our concept by
integrating City of Ottawa’s traffic web cams in GeoSWIFT.
These web cams cover most of the important intersections of
downtown Ottawa and give viewers a sense of real-time traffic
conditions. The web cams in Ottawa feed near-real time still
images into GeoSWIFT and GeoSWIFT connects users to web
cams by embedding Xlink to the web cams in GML responses
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upon users' requests. We can foresee that a lot of applications
will be done by including these low-cost off-the-shelf sensors
into the interoperable infrastructure of the sensor web.
3. DISCUSSIONS AND FUTURE WORK
An open geospatial sensing service can be the centre which
stores, disseminates, exchanges, manages, displays and
analyzes the spatial sensing information for sensor web. In
GeoSWIFT, we've integrated three sensing resources into
GeoSWIFT. At later stages of GeoSWIFT, more sensing
resources, especially remote sensing data (e.g. satellite remote
sensing imageries, Lidar point clouds, etc), will be tested and
integrated into current system.
Wireless sensor networks, such as MICA2 we are using in
GeoSWIFT, bring great opportunities and challenges to current
spatial data infrastructure. These tiny motes and moving agents
will change the way how we collect data for GIS. These tiny
motes and moving objects will generate enormous amounts of
data and data types for GIS. The processing power and
embedded operation system of MICA2 provides the capability
for GeoSWIFT sensing service to send command and control to
the nodes, and nodes change the behaviour according to the
commands.
By integrating external sensor observation sources, such as
METAR and NEIC, we expand the scope of GeoSWIFT to the
level of an interoperable sensor web. The sensor web should be
able to leverage existing sensing resources and shouldn't focus
on using certain sensing instruments and proprietary
communication protocols. The spatial component of those
existing sensor observation services is weak. In both METAR
and NEIC, locations of the observations are recorded in
geographical coordinates in text format. By providing a
standard based web service interfaces (OGC web specifications)
and data format (GML), GeoSWIFT includes these external
sensor observations into sensor web and makes these two
sensing resources interoperable and more widely available. Web
cam is the remote sensing sensors currently included in
GeoSWIFT. Web cams represent another type of sensing
resources of sensor web, which is low-cost, off-the-shelf and
yet powerful.
In the future, GeoSWIFT will include more different types of
sensing resources and remote sensing data is especially of high
priority (e.g. satellite remote sensing imageries). Real-world
applications will be built upon our currently system.
ACKNOLEGEMENTS
This research is sponsored by GEOIDE, PRECARN and
CRESTech. Authors also want to thank Mr. Bjorn Prenzel's
help on this paper.
REFERENCES
Correal, N. and Patwari, N., 2001. Wireless Sensor Networks:
Challenges and Opportunities, MPRG/Virginia Tech Wireless
Symposium.
Estrin, D., Culler, D., Pister, K. and Sukhatme, G., 2002.
Connecting the Physical World with Pervasive Networks. /EEE
Pervasive Computing, 1(1).
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