Lightweight Material Detection for Placement-Aware Mobile Computing

Authors:
Chris Harrison, Scott E. Hudson (Carnegie Mellon University)

Summary:
Placement-awareness would allow mobile devices to take certain actions without being explicitly told to do so (the authors give the example of a cell phone silencing itself while its owner is at work). In this paper, both cell phones and laptops are used to demonstrate the potential of a new sensor that observes its surroundings to determine the placement of its operating device. A user could map certain materials to locations, and the multispectral sensor could then predict its location by comparison (figure 1).

Figure 1- This picture is humongous.

After giving some examples of use, the authors discuss how the sensor works and what it is made of. To combat situations where no light reaches the bottom of the device, the sensor is equipped with different LEDs that can be reflected off of the resting surface. It does its detection in seconds, and costs less than a dollar to manufacture. With the help of a naive Bayes classifier, the sensor learns which materials correspond to which locations within 86.6% accuracy (which, they say, is much better than anything else on the market).

Discussion:
This sensor has potential, but it definitely needs to have an override added to it. If for some reason the sensor thinks that you're in a location that you aren't then you're going to get pwned. But saving energy, as they discussed in the paper, is a definite plus. I see a company catching on and then charging beastly fees for this $1 sensor (that's the way the world goes round aka Microsoft).