University of Oulu

Aku Visuri, Zeyun Zhu, Denzil Ferreira, Shin'ichi Konomi, and Vassilis Kostakos. 2017. Smartphone detection of collapsed buildings during earthquakes. In Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (UbiComp '17). ACM, New York, NY, USA, 557-562. DOI: https://doi.org/10.1145/3123024.3124402

Smartphone detection of collapsed buildings during earthquakes

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Author: Visuri, Aku1; Zhu, Zeyun1; Ferreira, Denzil1;
Organizations: 1University of Oulu, Oulu, Finland
2Kyushu University, Fukuoka, Japan
3The University of Melbourne, Melbourne, Australia
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe201902195353
Language: English
Published: Association for Computing Machinery, 2017
Publish Date: 2019-02-19
Description:

Abstract

The leading cause of death during earthquakes is the collapse of urban infrastructures and the subsequent delay of emergency responders in identifying and reaching the affected sites. To overcome this challenge, we designed and evaluated a crowdsensing system that detects collapsed buildings using end-user smartphones as distributed sensors. We present our evaluation of smartphones’ accuracy in inferring a building collapse by detecting falls onto solid surfaces, and estimating the false positive rate. Further sensors can present more detailed information about each potential collapse event. We conduct simulations to identify strategies for dealing with false-positive data under scenarios of varying population density. Potential building collapses can be determined with 95% accuracy given 10 connected devices within a 125m radius, increasing to 99.99% for 50 devices. End-user devices can proactively offer valuable help to emergency responders during earthquakes, potentially saving lives.

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ISBN Print: 978-1-4503-5190-4
Pages: 557 - 562
DOI: 10.1145/3123024.3124402
OADOI: https://oadoi.org/10.1145/3123024.3124402
Host publication: UbiComp '17. Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Maui, Hawaii Sept 11-15, 2017
Conference: Acm international joint conference on pervasive and ubiquitous computing
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
Copyright information: © 2017 Copyright is held by the owner/author(s). | ACM 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in UbiComp '17. Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Maui, Hawaii Sept 11-15, 2017, https://doi.org/10.1145/3123024.3124402.