Co-location epidemic tracking on London public transports using low power mobile magnetometer

The public transports provide an ideal means to enable contagious diseases transmission. This paper introduces a novel idea to detect co-location of people in such environment using just the ubiquitous geomagnetic field sensor on the smartphone. Essentially, given that all passengers must share the same journey between at least two consecutive stations, we have a long window to match the user trajectory. Our idea was assessed by a painstaking survey of over 150 kilometres of travelling distance, covering different parts of London, using the overground trains, the underground tubes and the buses.

[1]  Eamonn J. Keogh,et al.  Derivative Dynamic Time Warping , 2001, SDM.

[2]  George Tzanetakis,et al.  Polyphonic audio matching and alignment for music retrieval , 2003, 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684).

[3]  Pavel Senin,et al.  Dynamic Time Warping Algorithm Review , 2008 .

[4]  Mário J. Silva,et al.  Automated Social Network Epidemic Data Collector , 2009 .

[5]  Eiko Yoneki FluPhone study: virtual disease spread using haggle , 2011, CHANTS '11.

[6]  Geeta Nijhawan,et al.  ISOLATED SPEECH RECOGNITIONUSING MFCC AND DTW , 2013 .

[7]  Hui Zhao,et al.  Detecting Flu Transmission by Social Sensor in China , 2013, 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing.

[8]  Zhiyuan Luo,et al.  On the Feasibility of Using Two Mobile Phones and WLAN Signal to Detect Co-Location of Two Users for Epidemic Prediction , 2014, LBS.

[9]  Aaron Striegel,et al.  Face-to-Face Proximity EstimationUsing Bluetooth On Smartphones , 2014, IEEE Transactions on Mobile Computing.

[10]  R. Emonet,et al.  Epidemic Contact Tracing via Communication Traces , 2014, PloS one.

[11]  Iyad Rahwan,et al.  Predicting and containing epidemic risk using friendship networks , 2016, 2016 Information Theory and Applications Workshop (ITA).

[12]  Hyogon Kim,et al.  Car-level co-location detection on trains for infectious disease epidemic monitoring , 2017 .