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An optimized embedded target detection system using acoustic and seismic sensors

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Standard

An optimized embedded target detection system using acoustic and seismic sensors. / Lee, Kyunghun; Riggan, Benjamin S.; Bhattacharyya, Shuvra S.

25th European Signal Processing Conference, EUSIPCO 2017. IEEE, 2017. s. 986-990.

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Harvard

Lee, K, Riggan, BS & Bhattacharyya, SS 2017, An optimized embedded target detection system using acoustic and seismic sensors. julkaisussa 25th European Signal Processing Conference, EUSIPCO 2017. IEEE, Sivut 986-990, EUROPEAN SIGNAL PROCESSING CONFERENCE, 1/01/00. https://doi.org/10.23919/EUSIPCO.2017.8081355

APA

Lee, K., Riggan, B. S., & Bhattacharyya, S. S. (2017). An optimized embedded target detection system using acoustic and seismic sensors. teoksessa 25th European Signal Processing Conference, EUSIPCO 2017 (Sivut 986-990). IEEE. https://doi.org/10.23919/EUSIPCO.2017.8081355

Vancouver

Lee K, Riggan BS, Bhattacharyya SS. An optimized embedded target detection system using acoustic and seismic sensors. julkaisussa 25th European Signal Processing Conference, EUSIPCO 2017. IEEE. 2017. s. 986-990 https://doi.org/10.23919/EUSIPCO.2017.8081355

Author

Lee, Kyunghun ; Riggan, Benjamin S. ; Bhattacharyya, Shuvra S. / An optimized embedded target detection system using acoustic and seismic sensors. 25th European Signal Processing Conference, EUSIPCO 2017. IEEE, 2017. Sivut 986-990

Bibtex - Lataa

@inproceedings{5de65552c8844f06896a9975ba6aca62,
title = "An optimized embedded target detection system using acoustic and seismic sensors",
abstract = "Detection of targets using low power embedded devices has important applications in border security and surveillance. In this paper, we build on recent algorithmic advances in sensor fusion, and present the design and implementation of a novel, multi-mode embedded signal processing system for detection of people and vehicles using acoustic and seismic sensors. Here, by {"}multi-mode{"}, we mean that the system has available a complementary set of configurations that are optimized for different trade-offs. The multimode capability delivered by the proposed system is useful to supporting long lifetime (long term, energy-efficient {"}standby{"} operation), while also supporting optimized accuracy during critical time periods (e.g., when a potential threat is detected). In our target detection system, we apply a strategically-configured suite of single-and dual-modality signal processing techniques together with dataflow-based design optimization for energyefficient, real-time implementation. Through experiments using a Raspberry Pi platform, we demonstrate the capability of our target detection system to provide efficient operational tradeoffs among detection accuracy, energy efficiency, and processing speed.",
author = "Kyunghun Lee and Riggan, {Benjamin S.} and Bhattacharyya, {Shuvra S.}",
note = "jufoid=55867",
year = "2017",
month = "10",
day = "23",
doi = "10.23919/EUSIPCO.2017.8081355",
language = "English",
publisher = "IEEE",
pages = "986--990",
booktitle = "25th European Signal Processing Conference, EUSIPCO 2017",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - An optimized embedded target detection system using acoustic and seismic sensors

AU - Lee, Kyunghun

AU - Riggan, Benjamin S.

AU - Bhattacharyya, Shuvra S.

N1 - jufoid=55867

PY - 2017/10/23

Y1 - 2017/10/23

N2 - Detection of targets using low power embedded devices has important applications in border security and surveillance. In this paper, we build on recent algorithmic advances in sensor fusion, and present the design and implementation of a novel, multi-mode embedded signal processing system for detection of people and vehicles using acoustic and seismic sensors. Here, by "multi-mode", we mean that the system has available a complementary set of configurations that are optimized for different trade-offs. The multimode capability delivered by the proposed system is useful to supporting long lifetime (long term, energy-efficient "standby" operation), while also supporting optimized accuracy during critical time periods (e.g., when a potential threat is detected). In our target detection system, we apply a strategically-configured suite of single-and dual-modality signal processing techniques together with dataflow-based design optimization for energyefficient, real-time implementation. Through experiments using a Raspberry Pi platform, we demonstrate the capability of our target detection system to provide efficient operational tradeoffs among detection accuracy, energy efficiency, and processing speed.

AB - Detection of targets using low power embedded devices has important applications in border security and surveillance. In this paper, we build on recent algorithmic advances in sensor fusion, and present the design and implementation of a novel, multi-mode embedded signal processing system for detection of people and vehicles using acoustic and seismic sensors. Here, by "multi-mode", we mean that the system has available a complementary set of configurations that are optimized for different trade-offs. The multimode capability delivered by the proposed system is useful to supporting long lifetime (long term, energy-efficient "standby" operation), while also supporting optimized accuracy during critical time periods (e.g., when a potential threat is detected). In our target detection system, we apply a strategically-configured suite of single-and dual-modality signal processing techniques together with dataflow-based design optimization for energyefficient, real-time implementation. Through experiments using a Raspberry Pi platform, we demonstrate the capability of our target detection system to provide efficient operational tradeoffs among detection accuracy, energy efficiency, and processing speed.

U2 - 10.23919/EUSIPCO.2017.8081355

DO - 10.23919/EUSIPCO.2017.8081355

M3 - Conference contribution

SP - 986

EP - 990

BT - 25th European Signal Processing Conference, EUSIPCO 2017

PB - IEEE

ER -