Demo Abstract: SEUS-A wearable multi-channel acoustic headset platform to improve pedestrian safety

Rishikanth Chandrasekaran; Daniel De Godoy; Stephen Xia; Md Tamzeed Islam; Bashima Islam; Shahriar Nirjon; Peter Kinget; Xiaofan Jiang

doi:10.1145/2994551.2996547

Demo Abstract: SEUS-A wearable multi-channel acoustic headset platform to improve pedestrian safety

Rishikanth Chandrasekaran, Daniel De Godoy, Stephen Xia, Md Tamzeed Islam, Bashima Islam, Shahriar Nirjon, Peter Kinget, Xiaofan Jiang

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

With the prevalence of smartphones, pedestrians and joggers today often walk or run while listening to music. Since they are deprived of their auditory senses that would have pro-vided important cues to dangers, they are at a much greater risk of being hit by cars or other vehicles. In this demon-stration we present SEUS, a wearable system aimed at Sense Enhancement for Urban Safety. SEUS uses a three-stage ar-chitecture, consisting of headset mounted audio sensors, an embedded front-end for signal processing and feature extrac-tion, and machine learning based classification on a smart-phone, to provide early danger detection for pedestrians in real-Time.

Original language	English (US)
Title of host publication	Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016
Publisher	Association for Computing Machinery, Inc
Pages	330-331
Number of pages	2
ISBN (Electronic)	9781450342636
DOIs	https://doi.org/10.1145/2994551.2996547
State	Published - Nov 14 2016
Event	14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016 - Stanford, United States Duration: Nov 14 2016 → Nov 16 2016

Publication series

Name	Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016

Other

Other	14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016
Country/Territory	United States
City	Stanford
Period	11/14/16 → 11/16/16

ASJC Scopus subject areas

Hardware and Architecture
Computer Networks and Communications
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1145/2994551.2996547

Cite this

Chandrasekaran, R., De Godoy, D., Xia, S., Islam, M. T., Islam, B., Nirjon, S., Kinget, P., & Jiang, X. (2016). Demo Abstract: SEUS-A wearable multi-channel acoustic headset platform to improve pedestrian safety. In Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016 (pp. 330-331). (Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016). Association for Computing Machinery, Inc. https://doi.org/10.1145/2994551.2996547

Chandrasekaran, Rishikanth ; De Godoy, Daniel ; Xia, Stephen et al. / Demo Abstract : SEUS-A wearable multi-channel acoustic headset platform to improve pedestrian safety. Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016. Association for Computing Machinery, Inc, 2016. pp. 330-331 (Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016).

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title = "Demo Abstract: SEUS-A wearable multi-channel acoustic headset platform to improve pedestrian safety",

abstract = "With the prevalence of smartphones, pedestrians and joggers today often walk or run while listening to music. Since they are deprived of their auditory senses that would have pro-vided important cues to dangers, they are at a much greater risk of being hit by cars or other vehicles. In this demon-stration we present SEUS, a wearable system aimed at Sense Enhancement for Urban Safety. SEUS uses a three-stage ar-chitecture, consisting of headset mounted audio sensors, an embedded front-end for signal processing and feature extrac-tion, and machine learning based classification on a smart-phone, to provide early danger detection for pedestrians in real-Time.",

author = "Rishikanth Chandrasekaran and {De Godoy}, Daniel and Stephen Xia and Islam, {Md Tamzeed} and Bashima Islam and Shahriar Nirjon and Peter Kinget and Xiaofan Jiang",

note = "Publisher Copyright: {\textcopyright} 2016 Copyright held by the owner/author(s).; 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016 ; Conference date: 14-11-2016 Through 16-11-2016",

year = "2016",

month = nov,

day = "14",

doi = "10.1145/2994551.2996547",

language = "English (US)",

series = "Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016",

publisher = "Association for Computing Machinery, Inc",

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Chandrasekaran, R, De Godoy, D, Xia, S, Islam, MT, Islam, B, Nirjon, S, Kinget, P & Jiang, X 2016, Demo Abstract: SEUS-A wearable multi-channel acoustic headset platform to improve pedestrian safety. in Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016. Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016, Association for Computing Machinery, Inc, pp. 330-331, 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016, Stanford, United States, 11/14/16. https://doi.org/10.1145/2994551.2996547

Demo Abstract: SEUS-A wearable multi-channel acoustic headset platform to improve pedestrian safety. / Chandrasekaran, Rishikanth; De Godoy, Daniel; Xia, Stephen et al.
Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016. Association for Computing Machinery, Inc, 2016. p. 330-331 (Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Chandrasekaran R, De Godoy D, Xia S, Islam MT, Islam B, Nirjon S et al. Demo Abstract: SEUS-A wearable multi-channel acoustic headset platform to improve pedestrian safety. In Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016. Association for Computing Machinery, Inc. 2016. p. 330-331. (Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems, SenSys 2016). doi: 10.1145/2994551.2996547

Demo Abstract: SEUS-A wearable multi-channel acoustic headset platform to improve pedestrian safety

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