research-article

Bo-ear: unsupervised car sound sensing and tracking using microphones on smartphones

Authors:

Richard HowardAuthors Info & Claims

S3: Proceedings of the Eighth Wireless of the Students, by the Students, and for the Students Workshop

Pages 9 - 11

https://doi.org/10.1145/2987354.2987362

Published: 03 October 2016 Publication History

Get Access

Abstract

As people become increasingly accustomed to using smartphones while they walk, there will be a corresponding concern about pedestrian safety as smartphone users might become distracted. In this work, we address this concern by developing a system for smartphones that warns users when it detects an oncoming car. In addition to detecting the presence of a vehicle, it can also estimate the vehicle's driving direction. We achieve these goals by processing the acoustic signal captured by microphones embedded in the user's mobile phone. In order to achieve more robust and timely detection, we also explore two novel feature, namely, Power on Certain Frequencies and Top Right frequency.

References

[1]

F. Bu and C.-Y. Chan. Pedestrian detection in transit bus application: sensing technologies and safety solutions. In Intelligent Vehicles Symposium, 2005. Proceedings. IEEE. IEEE, 2005.

Crossref

Google Scholar

[2]

K. Fitzpatrick, S. Turner, and M. A. Brewer. Improving pedestrian safety at unsignalized intersections. Institute of Transportation Engineers. ITE Journal, 77(5):34, 2007.

Google Scholar

[3]

M. Konishi. How the owl tracks its prey: experiments with trained barn owls reveal how their acute sense of hearing enables them to catch prey in the dark. American Scientist, 61(4):414--424, 1973.

Google Scholar

[4]

NHTSA. Traffic safety facts 2013. DOT HS 812 139.

Google Scholar

[5]

W. H. Organization et al. Pedestrian safety: A road safety manual for decision-makers and practitioners. World Health Organization, 2013.

Google Scholar

Cited By

View all

Ou MWang LXun H(2019)DeaPS: Deep Learning-Based User-Level Proactive Security Auditing for Clouds2019 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOBECOM38437.2019.9014172(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/GLOBECOM38437.2019.9014172
Kalra PMittal DPrince Sidhu E(2017)Autonomous solar smart cap (ASSC) for pedestrian safety2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC)10.1109/ICBDACI.2017.8070854(307-311)Online publication date: Mar-2017
https://doi.org/10.1109/ICBDACI.2017.8070854

Recommendations

Database of multichannel in-ear and behind-the-ear head-related and binaural room impulse responses
Special issue on digital signal processing for hearing instruments

An eight-channel database of head-related impulse responses (HRIRs) and binaural room impulse responses (BRIRs) is introduced. The impulse responses (IRs) were measured with three-channel behind-the-ear (BTEs) hearing aids and an in-ear microphone at ...
Inner-ear cochlea testing with earphones
MobiSys '22: Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services

In this MobiSys demo we show a low-cost earphone based system that can screen for hearing loss with a cost of $10. Our system is designed to detect otoacoustic emissions (OAE) which are sounds generated when the outer hair cells move in a healthy ...
OpenEarable 1.4: Dual Microphones Earpiece to Capture In-Ear and Outer-Ear Audio Signals
UbiComp '24: Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing

In recent years, earables have emerged as a focal point for exploring novel sensing principles on the ears. OpenEarable, an open reference platform, has been developed to integrate various sensors in and around the ears. However, it has thus far lacked ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

S3: Proceedings of the Eighth Wireless of the Students, by the Students, and for the Students Workshop

October 2016

52 pages

ISBN:9781450342551

DOI:10.1145/2987354

Program Chairs:
Shubham Jain
Rutgers University
,
Yasaman Ghasem Pour
Rice University

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 October 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article

Conference

MobiCom'16

MobiCom'16: The 22nd Annual International Conference on Mobile Computing and Networking

October 3 - 7, 2016

New York, New York City

Acceptance Rates

S3 Paper Acceptance Rate 15 of 18 submissions, 83%;

Overall Acceptance Rate 65 of 93 submissions, 70%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
79
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Ou MWang LXun H(2019)DeaPS: Deep Learning-Based User-Level Proactive Security Auditing for Clouds2019 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOBECOM38437.2019.9014172(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/GLOBECOM38437.2019.9014172
Kalra PMittal DPrince Sidhu E(2017)Autonomous solar smart cap (ASSC) for pedestrian safety2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC)10.1109/ICBDACI.2017.8070854(307-311)Online publication date: Mar-2017
https://doi.org/10.1109/ICBDACI.2017.8070854

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

EPUB

View this article in ePub.

ePub

Abstract

References

Cited By

Recommendations

Database of multichannel in-ear and behind-the-ear head-related and binaural room impulse responses

Inner-ear cochlea testing with earphones

OpenEarable 1.4: Dual Microphones Earpiece to Capture In-Ear and Outer-Ear Audio Signals

Comments

Information

Published In

Publisher

Publication History

Permissions

Check for updates

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

EPUB

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations