Smartphone detection of collapsed buildings during earthquakes

Aku Visuri, Zeyun Zhu, Denzil Ferreira, Shin'ichi Konomi, Vassilis Kostakos

研究成果: 著書/レポートタイプへの貢献会議での発言

抄録

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.

元の言語英語
ホスト出版物のタイトルUbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
出版者Association for Computing Machinery, Inc
ページ557-562
ページ数6
ISBN(電子版)9781450351904
DOI
出版物ステータス出版済み - 9 11 2017
イベント2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017 - Maui, 米国
継続期間: 9 11 20179 15 2017

出版物シリーズ

名前UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

会議

会議2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017
米国
Maui
期間9/11/179/15/17

Fingerprint

Smartphones
Earthquakes
Sensors

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

これを引用

Visuri, A., Zhu, Z., Ferreira, D., Konomi, S., & Kostakos, V. (2017). Smartphone detection of collapsed buildings during earthquakes. : UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (pp. 557-562). (UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers). Association for Computing Machinery, Inc. https://doi.org/10.1145/3123024.3124402

Smartphone detection of collapsed buildings during earthquakes. / Visuri, Aku; Zhu, Zeyun; Ferreira, Denzil; Konomi, Shin'ichi; Kostakos, Vassilis.

UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2017. p. 557-562 (UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers).

研究成果: 著書/レポートタイプへの貢献会議での発言

Visuri, A, Zhu, Z, Ferreira, D, Konomi, S & Kostakos, V 2017, Smartphone detection of collapsed buildings during earthquakes. : UbiComp/ISWC 2017 - Adjunct 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/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, Association for Computing Machinery, Inc, pp. 557-562, 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017, Maui, 米国, 9/11/17. https://doi.org/10.1145/3123024.3124402
Visuri A, Zhu Z, Ferreira D, Konomi S, Kostakos V. Smartphone detection of collapsed buildings during earthquakes. : UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc. 2017. p. 557-562. (UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers). https://doi.org/10.1145/3123024.3124402
Visuri, Aku ; Zhu, Zeyun ; Ferreira, Denzil ; Konomi, Shin'ichi ; Kostakos, Vassilis. / Smartphone detection of collapsed buildings during earthquakes. UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2017. pp. 557-562 (UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers).
@inproceedings{92a92c59473d48e4baf5986b8efa2db5,
title = "Smartphone detection of collapsed buildings during earthquakes",
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.",
author = "Aku Visuri and Zeyun Zhu and Denzil Ferreira and Shin'ichi Konomi and Vassilis Kostakos",
year = "2017",
month = "9",
day = "11",
doi = "10.1145/3123024.3124402",
language = "English",
series = "UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers",
publisher = "Association for Computing Machinery, Inc",
pages = "557--562",
booktitle = "UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers",

}

TY - GEN

T1 - Smartphone detection of collapsed buildings during earthquakes

AU - Visuri, Aku

AU - Zhu, Zeyun

AU - Ferreira, Denzil

AU - Konomi, Shin'ichi

AU - Kostakos, Vassilis

PY - 2017/9/11

Y1 - 2017/9/11

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85030867540&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85030867540&partnerID=8YFLogxK

U2 - 10.1145/3123024.3124402

DO - 10.1145/3123024.3124402

M3 - Conference contribution

AN - SCOPUS:85030867540

T3 - UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

SP - 557

EP - 562

BT - UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

PB - Association for Computing Machinery, Inc

ER -