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Predicting earthquake impact with laptop motion sensors

Gary Mcgilvary

Principle goal: to make clever use of the sudden motion sensor of Apple notebooks to map the impact of earthquakes in densely populated areas.

After an earthquake, it is vital to understand the damage sustained by its impact. Especially in densely populated areas, it is important for an effective emergency response to know which areas are likely to be worst affected. Predicting the damage caused by earthquakes is very difficult as it depends on many and poorly constrained factors from wave propagation characteristics to building vulnerability. Typically, the impact of earthquakes is linked to the level of shaking itself measured by sensors that pick up the ground acceleration [1]. To get an accurate picture of this, dense and then expensive networks are required which can only be applied in high hazard areas such as Tokyo or Taiwan for example.

In this project, the aim is to measure the impact of earthquakes by making use of the [2] sudden motion sensor found in recent Apple notebooks. These sensors are not as accurate as seismic sensors, but still sufficiently accurate to provide a map of impact providing many of them are distributed over the affected area. As cities are densely populated with many casual and business users, the chance of sufficient coverage is high. Also, as cities are often the scene for large amounts of damage by earthquakes, they provide the best application area for this approach.

To allow the approach to work, and to evaluate it, you will build a system based on existing prototypes [3,4]. The main idea is to have two components. First, a tool that people can install easily and which lets an Apple laptop continuously monitor "seismic" activity. The data produced must be buffered on the laptop for a limited period. Second, a system that when prompted with an earthquake queries the laptops it knows about (or even better, which are in the affected area) for their buffered data, which can then be copied to a central location for analysis. The output of this analysis can then be shown using so called felt-maps as shown in Figure 2 of [2].

By having your tool installed on multiple or even many laptops, you will then orchestrate your own "earthquake" by having everyone "shake" their laptops while recording the event. You will then create a ShakeMap, perhaps even showing the result on Google Maps?

This work will be in conjunction with the European-Mediterranean Seismological Centre [5], which primary purpose is to provide information on earthquakes in realtime. They will assist with the seismological part of your project including the analysis and visualisation.

Project status: 
Degree level: 
Supervisors @ NeSC: 
Other supervisors: 
Rémy Bossu, European-Mediterranean Seismological Centre, France; Fabrice Cotton, Grenoble University, France
Subject areas: 
Distributed Systems
Mobile Computation
WWW Tools and Programming
Student project type: 
[1] [2] [3] [4] [5]