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Darwin Phones: the Evolution of Sensing and Inference on Mobile Phones

(2010-10-25 14:54:38)
分类: MobileSensing
Emiliano Miluzzo, Cory T.Cornelius, Ashwin Ramaswamy, Tanzeem Choudhury, Zhigang Liu, Andrew T. Campbell @ Dartmouth College
MobiSys 2010

http://www.ists.dartmouth.edu/library/478.pdf

 There are three important concepts in this paper:
Classifier Evolution: The classifier on each phone evolves when the phone enters new sensing environment. The classifier needs an initial training, which is not enough to provide high classification accuracy in different environment. In the Darwin Phones, the classifier uses semi-supervised learning and can can adjust the learning models with the varying sensing environment.
Model Pooling: When a mobile phones enters a new environment, it can make use of the classification models in co-located mobile phones. Building a new model is quite time-consuming. Model pooling can be done by a server or just a mobile phones, collecting the models from co-located mobile phones. When new phones come, they can download these models.
Collaboratively Inference: Mobile phone finally need to make inference based on the data from the sensors. Different mobiles in the same place may have different sensing context. So Darwin Phones enable mobile phones to work collaboratively when they want to make inference. In this stage, each phone first makes local inference and then broadcast their results to others. Then each phone make the final decision based on all the inference result. Synchronization among these co-located phones is essential to make sure that they are working on the same event.

At last, they try to evaluate the performance of Darwin Phones in different environments using the speaker recognition application. They also analyse the time and resource it consumes in different stages of Darwin phones.

It is referred by the following 4 papers:
Social Evolution: Options and behaviors in face-to-face networks
http://web.media.mit.edu/~anmol/madan-phdthesis-2010.pdf

Extracting Social and Community Intelligence from Digital Footprints:A emerging Researching Area
http://www.ayu.ics.keio.ac.jp/members/bingo/research/Community Intelligence_UIC2010_Invited.pdf

Happy or Moody? Why so?
http://www.create-net.org/ubint/ubihealth/papers/Matic_HappyOrMoody.pdf

EyePhone: Activating Mobile with Your Eyes
http://portal.acm.org/citation.cfm?id=1851322.1851328

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