Geoscience Reference
In-Depth Information
Nowadays, when I think about GIS in general and GC in particular, I cannot separate either of
them from the emerging metaverse. Viewed from a metaverse perspective, our discussions of GC
within the geospatial community have focused almost exclusively on the components of mirror
worlds. In this ubicomp age, GC should be re-conceptualised to deal with everyware in the emerg-
ing metaverse.
One of the defining characteristics of ubicomp is its context awareness, which generally refers to
the capabilities of either mobile or embedded systems to sense their physical environment and adapt
their behaviour accordingly. In ubicomp, context includes three essential elements: (1) where you
are (location), (2) who you are with (identity) and (3) what resources are nearby (potential). Context
is a broad term that includes nearby people, devices, lighting, noise level, network availability and
even the social situation, for example, whether you are with your family or a friend from school or
a colleague from work. Location is only part of the contextual information, but location alone does
not necessarily capture things of interest that are mobile or changing. As far as GC is concerned,
location is the starting point from which further spatial analysis and modelling can be conducted.
In the age of ubicomp, location has assumed more important roles in shaping everything we do in
the metaverse (Gordon and de Souza e Silva, 2011). This section first reviews the current existing
location sensing technologies, followed by a discussion on how to design ubicomp for GC.
16.3.1 l
location
/P
oSition
S
enSing
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echnologieS
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BicoMP
High-quality locational information is the foundation upon which GC is built. During the past two
decades, multiple technological advances have been made in alternative location sensing technology,
including techniques for indoor navigation, near field communication (NFC), MEMS, audio bea-
cons, Wi-Fi, radio-frequency identification (RFID) and Bluetooth (Choi et al., 2008; ABI Research,
2012). Indeed, these alternative location sensing technologies have become embedded in more and
more devices and consumer products, making computing not only more ubiquitous but also more
location and context aware. As a result, we have witnessed the growth of ubiquitous geographic
information in recent years (Kim and Jang, 2012), which is increasingly available and searchable on
the web (Gordon and de Souza e Silva, 2011).
Regardless of the specific techniques deployed to determine the locational information, three
major methods/principles are used when attempting to determine a given location in ubicomp
(Hightower and Borriello, 2001):
•
Triangulation
can be done via lateration, which uses multiple distance measurements
between known points, or via angulation, which measures angle or bearing relative to
points with known separation. Satellite-based global positioning systems (GPSs) are based
upon the principle of triangulation to determine location. GPS works well outdoors but
usually does not work inside buildings.
•
Proximity
measures nearness to a known set of points. RFID, Wi-Fi and audio beacons
all rely on proximity measures. Most indoor location sensing techniques are based on the
proximity method.
•
Scene analysis
examines a view from a particular vantage point. Widely regarded
as the most cost-effective means of tracking full-body motions in the world today,
MotionStar is a location sensing technology based on the principle of scene analysis
(http://www.vrealities.com/motionstar.html).
These different location sensing techniques vary in accuracy, cost and area coverage, ranging from
workspace and site-wide systems to regional, global and even interplanetary systems. In reality,
hybrid positioning systems (e.g. Navizon, Xtify, PlaceEngine, Skyhook, Devicescape, openBmap) -
using a combination of more than one location sensing method - are often used to locate and track
people and objects. As geotagging becomes more common for information available online and IP
