Lightweight Material Detection for Placement-Aware Mobile Computing

(Comment left on Randy Ransom's blog)

Authors:
Chris Harrison Carnegie Mellon University, Pittsburgh, PA, USA
Scott E. Hudson Carnegie Mellon University, Pittsburgh, PA, USA

Paper Link:
http://delivery.acm.org/10.1145/1450000/1449761/p279-harrison.pdf?key1=1449761&key2=3175428621&coll=ACM&dl=ACM&CFID=81067528&CFTOKEN=37358406

Harrison and Hudson develop a lightweight cheap sensor for detecting the placement of mobile devices such as cell phones, ipods, and laptops. This sensor allows the device to detect the context/location that it is placed in and react accordingly.

For example a cell phone placed in a pocket doesn't have to light up it's screen to let the user know that a call is incoming. It just has to ring or vibrate. By preventing the screen from lighting up, the phone can save power and extend it's battery life.

The sensor that they implemented
1) provides info on space surrounding the device
2) Requires no external infrastructure to operate
3) The resulting data is available to use by the device.



The sensor itself is made of photoresistor which measures light intensity and a TSL230 light to frequency converter.
The sensor also has light emitting diodes
1) Infrared
2) Red
3) Green
4) Blue
5) Ultraviolet
that illuminates the surrounding area so that the sensors can pick up the reflected light back toward the device and proceed to deduce what kind of environment it finds itself in.

The sensing routine takes only 25ms and results in very low power consumption of 20mA when active.

They tested 27 sample materials over 6 trials where the first 5 trials trained the naive Bayes classifer and the 6th determined teh accuracy of the sensor. They found that the overall accuracy of the device was 86.9%

Next they conducted a 16 person survey of the environments that several mobile devices found themselves and the materials in those environments.

With those materials they ran the previous tests and found that the accuracy was now 94.4%

___________

My spill:

I'm all for making devices smarter by identifying the context of the device. This makes machines more useful and require less intentional commands to get what you want out of it.

I think that they've succeeded for the most part in devising their sensor. Hopefully businesses will pick up on this sensor and implement it in their devices.
With a little bit of advertising. We could see a new generation of mobile devices that are smarter and more energy efficient.

Their work seemed pretty flawless on the sensor itself. If they had to make any improvements, I would have expanded the number of people they got to take the survey or maybe take the time to implement their sensor in a number of devices and implement a few uses to showcase their work.