iShake System: Earthquake Detection with Smartphones Presenter: Jize Zhang Da Huo Original Paper:Reilly, Jack, et al. "Mobile phones as seismologic sensors: Automating data extraction for the iShake system." Automation Science and Engineering, IEEE Transactions on 10.2 (2013):

Earthquake Detection with Smartphones  The Big One: A massive scale (8.0 or higher on the Richter Scale) earthquake is predicted to shake the California sometime within the next 30 years.

Earthquake Detection with Smartphones (cont.)  Hardware of smart phones make them good candidates for seismic sensors Accelerometer GPS Gyroscope

Earthquake Detection with Smartphones (cont.)  Smart phones have densely covered urban areas (higher risk areas)

Potential Benefits  Early Warning: Tens of seconds is enough time to stop trains and surgeries and for people to find cover  Rapid Shake-Map: Shake-maps could tell us what areas have sustained the most serious damage Government could decide what resources must be mobilized and in what quantities

Challenges  Tradeoff between accuracy and coverage Human Sensing USGS Stations iShake

Challenges  False alarms Noisy environment Cheap sensors inside the phones  Battery life issues Sensors could drain batteries fast  Cellular coverage Soon after an actual earthquake event, cellular coverage often becomes unreliable

How Does iShake Work?  Phone sensors enable the device to capture all 3 axes of motion  Shaking of the ground -> Shaking of the phone  EQ parameters could be captured Epicenter, Intensity, etc.

The Architecture of iShake System  Phones  Servers  USGS Earthquake feed

Three-state mode  Steady Mode Phones must stay steady and charged before recording  Trigger Mode A shaking event above a predetermined threshold is recorded  Streaming Mode Local copy of data would be placed into a queue to be sent

11 Steady Trigger

12 Steady Trigger

13 2/5 2/7 1/5 Steady Trigger

14 4/5 5/7 1/5 1/1 2/8 1/5 Steady Trigger

Evaluations  Shaking Table Tests

Evaluations  Recorded data vs. Reference

Limitations  USGS Earthquake Feed Dependency iShake depends on USGS Earthquake Feed to filter individual phone’s data noise

Limitations  Our solution: Distributed hypothesis tests instead of centralized ones using USGS