Adaptive threshold triggering of GPS for long-term tracking in WSN

Llewyn Salt; Branislav Kusy; Raja Jurdak

doi:10.1109/SOCPAR.2015.7492827

Adaptive threshold triggering of GPS for long-term tracking in WSN

Llewyn Salt, Branislav Kusy, Raja Jurdak

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

1 Citation (Scopus)

Abstract

Long-term tracking is an expanding field with applications in logistics, ecology and wearable computing. The main challenge for longevity of tracking applications is the high energy consumption of GPS, which has been addressed by using low power sensors to trigger GPS activation upon detecting events of interest. While triggering can reduce power consumption, static thresholds can underperform in the longterm as context changes. This paper presents an auto-covariance based triggering algorithm that adapts trigger thresholds based on the incoming data and is effective with limited prior knowledge. We test the algorithm on empirical data from flying foxes and show that it outperforms static thresholding and existing adaptive algorithms from the literature.

Original language	English
Title of host publication	Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR 2015)
Editors	Mario Köppen, Bing Xue, Hideyuki Takagi, Ajith Abraham, Azah Kamilah Muda, Kun Ma
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	308-313
Number of pages	6
ISBN (Electronic)	9781467393607
DOIs	https://doi.org/10.1109/SOCPAR.2015.7492827
Publication status	Published - 2015
Externally published	Yes
Event	7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 - Fukuoka, Japan Duration: 13 Nov 2015 → 15 Nov 2015

Other

Other	7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015
Country/Territory	Japan
City	Fukuoka
Period	13/11/15 → 15/11/15

Keywords

Adaptive Algorithms
Embedded Software
Learning systems
Wireless sensor networks

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10.1109/SOCPAR.2015.7492827

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Salt, L., Kusy, B., & Jurdak, R. (2015). Adaptive threshold triggering of GPS for long-term tracking in WSN. In M. Köppen, B. Xue, H. Takagi, A. Abraham, A. K. Muda, & K. Ma (Eds.), Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR 2015) (pp. 308-313). Article 7492827 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/SOCPAR.2015.7492827

Salt, Llewyn ; Kusy, Branislav ; Jurdak, Raja. / Adaptive threshold triggering of GPS for long-term tracking in WSN. Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR 2015). editor / Mario Köppen ; Bing Xue ; Hideyuki Takagi ; Ajith Abraham ; Azah Kamilah Muda ; Kun Ma. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2015. pp. 308-313

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title = "Adaptive threshold triggering of GPS for long-term tracking in WSN",

abstract = "Long-term tracking is an expanding field with applications in logistics, ecology and wearable computing. The main challenge for longevity of tracking applications is the high energy consumption of GPS, which has been addressed by using low power sensors to trigger GPS activation upon detecting events of interest. While triggering can reduce power consumption, static thresholds can underperform in the longterm as context changes. This paper presents an auto-covariance based triggering algorithm that adapts trigger thresholds based on the incoming data and is effective with limited prior knowledge. We test the algorithm on empirical data from flying foxes and show that it outperforms static thresholding and existing adaptive algorithms from the literature.",

keywords = "Adaptive Algorithms, Embedded Software, Learning systems, Wireless sensor networks",

author = "Llewyn Salt and Branislav Kusy and Raja Jurdak",

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booktitle = "Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR 2015)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

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note = "7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 ; Conference date: 13-11-2015 Through 15-11-2015",

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Salt, L, Kusy, B & Jurdak, R 2015, Adaptive threshold triggering of GPS for long-term tracking in WSN. in M Köppen, B Xue, H Takagi, A Abraham, AK Muda & K Ma (eds), Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR 2015)., 7492827, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 308-313, 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015, Fukuoka, Japan, 13/11/15. https://doi.org/10.1109/SOCPAR.2015.7492827

Adaptive threshold triggering of GPS for long-term tracking in WSN. / Salt, Llewyn; Kusy, Branislav; Jurdak, Raja.
Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR 2015). ed. / Mario Köppen; Bing Xue; Hideyuki Takagi; Ajith Abraham; Azah Kamilah Muda; Kun Ma. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 308-313 7492827.

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

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AU - Kusy, Branislav

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AB - Long-term tracking is an expanding field with applications in logistics, ecology and wearable computing. The main challenge for longevity of tracking applications is the high energy consumption of GPS, which has been addressed by using low power sensors to trigger GPS activation upon detecting events of interest. While triggering can reduce power consumption, static thresholds can underperform in the longterm as context changes. This paper presents an auto-covariance based triggering algorithm that adapts trigger thresholds based on the incoming data and is effective with limited prior knowledge. We test the algorithm on empirical data from flying foxes and show that it outperforms static thresholding and existing adaptive algorithms from the literature.

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Salt L, Kusy B, Jurdak R. Adaptive threshold triggering of GPS for long-term tracking in WSN. In Köppen M, Xue B, Takagi H, Abraham A, Muda AK, Ma K, editors, Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR 2015). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2015. p. 308-313. 7492827 doi: 10.1109/SOCPAR.2015.7492827

Adaptive threshold triggering of GPS for long-term tracking in WSN

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