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 
84 
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). 
Inte 
—— 
Es! 
Ins 
Int 
OC 
an 
OC 
Int 
Te 
To 
ISi 
Ol