Energy-Efficient WSN Architecture for Illegal Deforestation Detection

Lucian Petrica; Gheorghe Stefan

doi:doi:10.11648/j.ijssn.20150303.12

| Peer-Reviewed

Energy-Efficient WSN Architecture for Illegal Deforestation Detection

Lucian Petrica, Gheorghe Stefan

Published in International Journal of Sensors and Sensor Networks (Volume 3, Issue 3)

Received: 25 October 2015 Accepted: 3 November 2015 Published: 24 November 2015

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

We present an energy-efficient wireless sensor network (WSN) architecture tailored for illegal deforestation detection. Illegal deforestation is a world-wide problem which may be prevented through improved monitoring of forested areas utilizing sensor networks equipped with chain-saw detection. Additional to detection, we identify sound source localization and sensor node localization as essential features of a deforestation monitoring WSN, and analyze two possible architectures which perform sound source localization with the distributed time difference-of-arrival (TDOA) algorithm and microphone-array based localization respectively. We develop an energy model and evaluate the two architectures. Our results indicate that the microphone array based WSN requires more hardware and is more complex, but is an order of magnitude more energy efficient than the distributed TDOA WSN as it minimizes radio traffic. This improvement in efficiency enables the microphone array equipped WSN to potentially operate for over a year, enabling practical deforestation monitoring with WSNs.

Published in	International Journal of Sensors and Sensor Networks (Volume 3, Issue 3)
DOI	10.11648/j.ijssn.20150303.12
Page(s)	24-30
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Deforestation, Acoustic Localization, Chain-Saw Detection, Energy, FPGA

References

[1]	D. Brack, “Briefing Paper: Illegal Logging”, Chatham House, 2006.
[2]	V. Harvanová, et al. "Detection of Wood Logging Based on Sound Recognition Using Zigbee Sensor Network." Proceedings of International Conference on Design and Architectures for Signal and Image Processing. 2011.
[3]	J. Papán, M. Jurecka, and J. Púchyová. "WSN for Forest Monitoring to Prevent Illegal Logging." FedCSIS. 2012.
[4]	L. Czúni, and P. Z. Varga. "Lightweight Acoustic Detection of Logging in Wireless Sensor Networks." The International Conference on Digital Information, Networking, and Wireless Communications (DINWC2014). The Society of Digital Information and Wireless Communication, 2014.
[5]	M. A. Razzaque, and S. Dobson. "Energy-efficient sensing in wireless sensor networks using compressed sensing." Sensors vol 14 no 2, pp. 2822-2859, 2014.
[6]	Yoo, In-Chul, and Dongsuk Yook. "Automatic sound recognition for the hearing impaired.", IEEE Trans. on Consumer Electronics vol 54 no 4, pp. 2029-2036, 2008.
[7]	J. Tiete, et al. "SoundCompass: a distributed MEMS microphone array-based sensor for sound source localization." Sensors vol. 14 no. 2, pp. 1918-1949, 2014.
[8]	R. Boaz. "Phase-mode versus delay-and-sum spherical microphone array processing." IEEE Signal Processing Letters, vol. 12 no.10, pp. 713-716, 2005.
[9]	J. H. DiBiase, H. F. Silverman, and M. S. Brandstein. "Robust localization in reverberant rooms." Microphone Arrays. Springer Berlin Heidelberg, 2001. pp. 157-180.
[10]	J. Bachrach, and C. Taylor. "Localization in sensor networks." Handbook of sensor networks: Algorithms and Architectures, 2005.
[11]	K. Whitehouse, C. Karlof, and D. Culler. "A practical evaluation of radio signal strength for ranging-based localization." ACM SIGMOBILE Mobile Computing and Communications Review vol. 11 no.1, pp. 41-52, 2007.
[12]	M. Kushwaha, et al. "Sensor node localization using mobile acoustic beacons." IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005.
[13]	“Wireless Measurement System, MICA2”, Crossbow Technology, Inc.41 Daggett Dr,.San Jose, CA 95134.
[14]	Atmel. "ATmega128L datasheet, 8-bit microcontroller with 128K bytes in-system programmable flash.", Available Online: www.atmel.com/images/doc2467.pdf
[15]	Texas Instruments. "CC1000: Single-Chip Very Low Power RF Transceiver", Available Online: www.ti.com/lit/ds/symlink/cc1000.pdf
[16]	P. Levis, et al. "Tinyos: An operating system for sensor networks." Ambient intelligence. Springer Berlin Heidelberg, 2005, pp. 115-148.
[17]	ST Microelectronics, "MP34DT01 MEMS audio sensor omnidirectional digital microphone", Available Online: http://www.st.com/web/en/resource/technical/document/datasheet/DM00039779.pdf

Cite This Article

Plain Text BibTeX RIS

APA Style

Lucian Petrica, Gheorghe Stefan. (2015). Energy-Efficient WSN Architecture for Illegal Deforestation Detection. International Journal of Sensors and Sensor Networks, 3(3), 24-30. https://doi.org/10.11648/j.ijssn.20150303.12

Copy | Download

ACS Style

Lucian Petrica; Gheorghe Stefan. Energy-Efficient WSN Architecture for Illegal Deforestation Detection. Int. J. Sens. Sens. Netw. 2015, 3(3), 24-30. doi: 10.11648/j.ijssn.20150303.12

Copy | Download

AMA Style

Lucian Petrica, Gheorghe Stefan. Energy-Efficient WSN Architecture for Illegal Deforestation Detection. Int J Sens Sens Netw. 2015;3(3):24-30. doi: 10.11648/j.ijssn.20150303.12

Copy | Download

@article{10.11648/j.ijssn.20150303.12,
  author = {Lucian Petrica and Gheorghe Stefan},
  title = {Energy-Efficient WSN Architecture for Illegal Deforestation Detection},
  journal = {International Journal of Sensors and Sensor Networks},
  volume = {3},
  number = {3},
  pages = {24-30},
  doi = {10.11648/j.ijssn.20150303.12},
  url = {https://doi.org/10.11648/j.ijssn.20150303.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20150303.12},
  abstract = {We present an energy-efficient wireless sensor network (WSN) architecture tailored for illegal deforestation detection. Illegal deforestation is a world-wide problem which may be prevented through improved monitoring of forested areas utilizing sensor networks equipped with chain-saw detection. Additional to detection, we identify sound source localization and sensor node localization as essential features of a deforestation monitoring WSN, and analyze two possible architectures which perform sound source localization with the distributed time difference-of-arrival (TDOA) algorithm and microphone-array based localization respectively. We develop an energy model and evaluate the two architectures. Our results indicate that the microphone array based WSN requires more hardware and is more complex, but is an order of magnitude more energy efficient than the distributed TDOA WSN as it minimizes radio traffic. This improvement in efficiency enables the microphone array equipped WSN to potentially operate for over a year, enabling practical deforestation monitoring with WSNs.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Energy-Efficient WSN Architecture for Illegal Deforestation Detection
AU  - Lucian Petrica
AU  - Gheorghe Stefan
Y1  - 2015/11/24
PY  - 2015
N1  - https://doi.org/10.11648/j.ijssn.20150303.12
DO  - 10.11648/j.ijssn.20150303.12
T2  - International Journal of Sensors and Sensor Networks
JF  - International Journal of Sensors and Sensor Networks
JO  - International Journal of Sensors and Sensor Networks
SP  - 24
EP  - 30
PB  - Science Publishing Group
SN  - 2329-1788
UR  - https://doi.org/10.11648/j.ijssn.20150303.12
AB  - We present an energy-efficient wireless sensor network (WSN) architecture tailored for illegal deforestation detection. Illegal deforestation is a world-wide problem which may be prevented through improved monitoring of forested areas utilizing sensor networks equipped with chain-saw detection. Additional to detection, we identify sound source localization and sensor node localization as essential features of a deforestation monitoring WSN, and analyze two possible architectures which perform sound source localization with the distributed time difference-of-arrival (TDOA) algorithm and microphone-array based localization respectively. We develop an energy model and evaluate the two architectures. Our results indicate that the microphone array based WSN requires more hardware and is more complex, but is an order of magnitude more energy efficient than the distributed TDOA WSN as it minimizes radio traffic. This improvement in efficiency enables the microphone array equipped WSN to potentially operate for over a year, enabling practical deforestation monitoring with WSNs.
VL  - 3
IS  - 3
ER  -

Copy | Download

Author Information

Lucian Petrica

FPGA Processing Department, Silicon Acuity SRL, Bucharest, Romania
Gheorghe Stefan

Faculty of Electronics and Telecommunication, University Politehnica of Bucharest, Bucharest, Romania

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Lucian Petrica, Gheorghe Stefan. (2015). Energy-Efficient WSN Architecture for Illegal Deforestation Detection. International Journal of Sensors and Sensor Networks, 3(3), 24-30. https://doi.org/10.11648/j.ijssn.20150303.12

Copy | Download

ACS Style

Lucian Petrica; Gheorghe Stefan. Energy-Efficient WSN Architecture for Illegal Deforestation Detection. Int. J. Sens. Sens. Netw. 2015, 3(3), 24-30. doi: 10.11648/j.ijssn.20150303.12

Copy | Download

AMA Style

Lucian Petrica, Gheorghe Stefan. Energy-Efficient WSN Architecture for Illegal Deforestation Detection. Int J Sens Sens Netw. 2015;3(3):24-30. doi: 10.11648/j.ijssn.20150303.12

Copy | Download

@article{10.11648/j.ijssn.20150303.12,
  author = {Lucian Petrica and Gheorghe Stefan},
  title = {Energy-Efficient WSN Architecture for Illegal Deforestation Detection},
  journal = {International Journal of Sensors and Sensor Networks},
  volume = {3},
  number = {3},
  pages = {24-30},
  doi = {10.11648/j.ijssn.20150303.12},
  url = {https://doi.org/10.11648/j.ijssn.20150303.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20150303.12},
  abstract = {We present an energy-efficient wireless sensor network (WSN) architecture tailored for illegal deforestation detection. Illegal deforestation is a world-wide problem which may be prevented through improved monitoring of forested areas utilizing sensor networks equipped with chain-saw detection. Additional to detection, we identify sound source localization and sensor node localization as essential features of a deforestation monitoring WSN, and analyze two possible architectures which perform sound source localization with the distributed time difference-of-arrival (TDOA) algorithm and microphone-array based localization respectively. We develop an energy model and evaluate the two architectures. Our results indicate that the microphone array based WSN requires more hardware and is more complex, but is an order of magnitude more energy efficient than the distributed TDOA WSN as it minimizes radio traffic. This improvement in efficiency enables the microphone array equipped WSN to potentially operate for over a year, enabling practical deforestation monitoring with WSNs.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Energy-Efficient WSN Architecture for Illegal Deforestation Detection
AU  - Lucian Petrica
AU  - Gheorghe Stefan
Y1  - 2015/11/24
PY  - 2015
N1  - https://doi.org/10.11648/j.ijssn.20150303.12
DO  - 10.11648/j.ijssn.20150303.12
T2  - International Journal of Sensors and Sensor Networks
JF  - International Journal of Sensors and Sensor Networks
JO  - International Journal of Sensors and Sensor Networks
SP  - 24
EP  - 30
PB  - Science Publishing Group
SN  - 2329-1788
UR  - https://doi.org/10.11648/j.ijssn.20150303.12
AB  - We present an energy-efficient wireless sensor network (WSN) architecture tailored for illegal deforestation detection. Illegal deforestation is a world-wide problem which may be prevented through improved monitoring of forested areas utilizing sensor networks equipped with chain-saw detection. Additional to detection, we identify sound source localization and sensor node localization as essential features of a deforestation monitoring WSN, and analyze two possible architectures which perform sound source localization with the distributed time difference-of-arrival (TDOA) algorithm and microphone-array based localization respectively. We develop an energy model and evaluate the two architectures. Our results indicate that the microphone array based WSN requires more hardware and is more complex, but is an order of magnitude more energy efficient than the distributed TDOA WSN as it minimizes radio traffic. This improvement in efficiency enables the microphone array equipped WSN to potentially operate for over a year, enabling practical deforestation monitoring with WSNs.
VL  - 3
IS  - 3
ER  -

Copy | Download