Location determination is an important field in pervasive computing and has diverse applications. Existing location determination approaches, which utilize signals from Access Points (APs), often rely upon triangulation and nearest neighbor classifiers to approximate a user’s location. In this disclosure, a classification-based approach to determine the location of a Wi-Fi enabled device is presented. Also, a new perspective of exploiting the underlying topology of the test area is disclosed, which can aid in economic placement of APs.
A classification approach exploiting the rectangular topology of a floor -plan to determine the location of a mobile user inside premises using only 2 access points
Names: Sushain Pandit
This disclosure contains two related ideas. One is the concept that tries to reduce the problem complexity by exploiting the underlying problem domain and the other provides an associated implementation with a classification approach using ANN (Artificial Neural-Networks).
The known solutions to these problems make use of a minimum 3 access-points to determine the location using triangulation. These solutions exploit the fact that the Signal strengths from an access point vary radially, i.e., the signal strength along an imaginary circle of radius 'r' from the location of the access point (assumed as the focus or center) is constant, say SS(r1), and decreases as we go radially away from the focus. So, if three such access points (APs) are placed randomly, then since 3 different circles can uniquely determine a point in 2-d space, we can locate a test-user based on his relative signal strengths w.r.t those 3 APs. [Refer Fig. 1]
Figure 1. Case when APs are randomly placed (Triangulation).
We try to take advantage of the fact that majority of physical structures, like buildings,
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organizations, etc, are rectangular in shape (top-view). Now, it is a fact that there is a near complete loss of signal strength when there is an obstruction thicker than 3cm, which is minimum wall thickness in almost all concrete buildings into which such a system may be installed. In theory, the signal strengths from an access point always vary radially and are constant along the circumference of signal strength circles. So, if we place the access-point on a corner, those circles reduce to quadrants (1/4th of a circle), because the other 3/4 of the circle is cut-off by the test-area walls.
Thus, by placing two access points at two of the adjacent corners in such rectangular structures, the "signal-strength circles" can be reduced to "Signal-Strength Quadrants" as shown in the figure. And thus, we can locate the test-user at the intersection of those two quadrants because any point in the 2d-plane of the building or test-lab can be represented by the set of Signal Strengths from the two Access Points. [Refer Fig. 2]
Figure 2. Case when APs are places at the adjacent corners of a rectangular test area.
The figure above shows the access point placement at the two 'adjacent' corners. Now, this figure is meant to portray that, theoretically, in a rectangular test-area, there is a possible arrangement of 2 access points, which would yield a unique intersection of signal strengths and this can serve as a possible premise for any further implementation.
Now, this premise serves as a foundation...