skip to main content
10.1145/1236360.1236389acmconferencesArticle/Chapter ViewAbstractPublication PagescpsweekConference Proceedingsconference-collections
Article

The design and evaluation of a mobile sensor/actuator network for autonomous animal control

Published: 25 April 2007 Publication History

Abstract

This paper investigates a mobile, wireless sensor/actuator network application for use in the cattle breeding industry. Our goal is to prevent fighting between bulls in on-farm breeding paddocks by autonomously applying appropriate stimuli when one bull approaches another bull. This is an important application because fighting between high-value animals such as bulls during breeding seasons causes significant financial loss to producers. Furthermore, there are significant challenges in this type of application because it requires dynamic animal state estimation, real-time actuation and efficient mobile wireless transmissions. We designed and implemented an animal state estimation algorithm based on a state-machine mechanism for each animal. Autonomous actuation is performed based on the estimated states of an animal relative to other animals. A simple, yet effective, wireless communication model has been proposed and implemented to achieve high delivery rates in mobile environments. We evaluated the performance of our design by both simulations and field experiments, which demonstrated the effectiveness of our autonomous animal control system.

References

[1]
Habitat monitoring on great duck island. http://www.greatduckisland.net/index.php.
[2]
Habitat monitoring on james reserve. http://www.jamesreserve.edu/.
[3]
D. P. Agrawal and Q.-A. Zeng. Introduction to Wireless and Mobile Systems. Thomson, 2nd edition, 2006.
[4]
E. Biagioni and K. Bridges. The application of remote sensor technology to assist the recovery of rare and endangered species. International Journal of High Performance Computing Applications, 16:315--324, 2005.
[5]
Z. Butler, P. Corke, R. Peterson, and D. Rus. Virtual fences for controlling cattle. In IEEE International Conference on Robotics and Automation, pages 4429--4436, 2004.
[6]
R. Chellappa, G. Qian, and Q. Zheng. Vehicle detection and tracking using acoustic and video sensors. In Proceedings of the International Conference on Acoustics, Speech and Signal Processing, Montreal, Canada, May 2004.
[7]
P. Corke and P. Sikka. Results from the farm. In Third Workshop on Embedded Networked Sensors (EmNets 2006), 2006.
[8]
D. Estrin, L. Girod, G. Pottie, and M. Srivastava. Instrumenting the world with wireless sensor networks. In Proceedings of the International Conference on Acoustics, Speech and Signal Processing, Salt Lake City, Utah, May 2001.
[9]
D. Gay, P. Levis, R. von Behren, M. Welsh, E. Brewer, and D. Culler. The nesc langauge: A holistic approach for network sensors. In Programming Language Design and Implementation. 2003.
[10]
J. Hill, R. Szeweczyk, A. Woo, S. Hollar, D. Culler, and K. Pister. System architecture directions for network sensors. In Archirectual Support for Programming Languages and Operating Systems. 2000.
[11]
W. Hu, N. Bulusu, and S. Jha. A communication paradigm for hybrid sensor/actuator networks. In Proceedings of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2004), pages 201--205, Barcelona, Spain, Sept. 2004.
[12]
W. Hu, V. N. Tran, N. Bulusu, C. T. Chou, S. Jha, and A. Taylor. The design and evaluation of a hybrid sensor network for cane-toad monitoring. In IPSN '05: Proceedings of the 4th international symposium on Information processing in sensor networks, page 71, Piscataway, NJ, USA, 2005. IEEE Press.
[13]
A. Krause, C. Guestrin, A. Gupta, and J. Kleinberg. Near-optimal sensor placements: Maximising information while minimizing communication cost. In The Fifth International Conference on Information Processing in Sensor Networks, pages 2--10, 2006.
[14]
L. Krishnamurthy, R. Adler, P. Buonadonna, J. Chhabra, M. Flanigan, N. Kushalnagar, L. Nachman, and M. Yarvis. Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north sea. In SenSys '05: Proceedings of the 3rd international conference on Embedded networked sensor systems, pages 64--75, New York, NY, USA, 2005. ACM Press.
[15]
A. Ledeczi, P. Volgyesi, M. Maroti, G. Simon, G. Balogh, A. Nadas, B. Kusy, S. Dora, and G. Pap. Multiple simultaneous acoustic source localization in urban terrain. In IPSN '05: Proceedings of the 4th international symposium on Information processing in sensor networks, page 69, Piscataway, NJ, USA, 2005. IEEE Press.
[16]
C. Lee, M. Reed, and J. Henshall. The stress response of cattle to electrical stimuli. In preparation for submission to Applied Animal Behaviour Science.
[17]
K. Mechitov, W. Kim, G. Agha, and T. Nagayama. High-frequency distributed sensing for structure monitoring. In Proceedings of the First International Workshop on Networked Sensing Systems, Tokyo, Japan, June 2004.
[18]
A. Meliou, D. Chu, C. Guestrin, J. Hellerstein, and W. Hong. Data gathering tours in sensor networks. In The Fifth International Conference on Information Processing in Sensor Networks, pages 43--50, 2006.
[19]
R. Musaloiu, A. Terzis, K. Szlavecz, A. Szalay, J. Cogan, and J. Gray. Life under your feet: A wireless soil ecology sensor network. In Third Workshop on Embedded Networked Sensors (EmNets 2006), 2006.
[20]
L. Schwiebert, S. K. Gupta, and J. Weinmann. Research challenges in wireless networks of biomedical sensors. In Proceedings of the 7th ACM MOBICOM, pages 151--165, Rome, Italy, July 2001. ACM Press.
[21]
P. Sikka, P. Corke, and L. Overs. Wireless sensor devices for animal tracking and control. In First IEEE Workshop on Embedded Networked Sensors in 29th Conference on Local Computer Networks, pages 446--454, 2004.
[22]
M. Srivastava, R. Muntz, and M. Potkonjak. Smart kindergarten: sensor-based wireless networks for smart developmental problem-solving enviroments. In Proceedings of the 7th ACM MOBICOM, pages 132--138, Rome, Italy, July 2001. ACM Press.
[23]
A. Tiedemann, T. Quigley, and L. White. Electronic (fenceless) control of animals. Research Paper PNW-RP-510, U.S. Department of Agriculture, 1999.
[24]
G. Tolle, J. Polstre, R. Szewczyk, D. Culler, N. Turner, K. Tu, S. Burgess, T. Dawson, P. Buonadonna, D. Gay, and W. Hong. A macroscope in the redwoods. In Proceedings of the Third International Conference on Embedded Networked Sensor Systems (SenSys05), pages 51--63, 2005.
[25]
D. Vercauteren, K. Perry, and S. Adams. Training deer to avoid sites through negative reinforcement. In Proc. of the 10th Wildlife Damage Management Conference, pages 95--104, 2003.
[26]
H. Wang, D. Estrin, and L. Girod. Preprocessing in a tiered sensor network for habitat monitoring. EURASIP JASP special issue of sensor networks, pages 392--401, 2003.
[27]
T. Wark, P. Corke, P. Sikka, L. Klingbeil, Y. Guo, C. Crossman, P. Valencia, D. Swain, and G. Bishop-Hurley. Transforming agriculture through pervasive wireless sensor networks. IEEE Pervasive Computing, (to appear), 2007.
[28]
G. Werner-Allen, K. Lorincz, M. Ruiz, O. Marcillo, J. Johnson, J. Lees, and M. Welsh. Deploying a wireless sensor network on an active volcano. To appear in special Sensor Nets issue of IEEE Internet Computing, early 2006.
[29]
A. Woo, T. Tong, and D. Culler. Taming the underlying challenges of reliable multihop routing in sensor networks. In SenSys '03: Proceedings of the 1st international conference on Embedded networked sensor systems, pages 14--27. ACM Press, 2003.
[30]
P. Zhang, C. Sadler, S. Lyon, and M. Martonosi. Hardware design experiences in zebranet. In Proceedings of 2nd International Conference on Embedded Networked Sensor Systems, 2004.

Cited By

View all
  • (2020)Novel deep learning framework for broadcasting abnormal events obtained from surveillance applicationsJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01668-6Online publication date: 2-Jan-2020
  • (2019)Massive terminal positioning system with snapshot positioning techniqueGPS Solutions10.1007/s10291-018-0821-z23:2(1-14)Online publication date: 1-Apr-2019
  • (2018)A Review of Computational Intelligence Techniques in Wireless Sensor and Actuator NetworksIEEE Communications Surveys & Tutorials10.1109/COMST.2018.285022020:4(2822-2854)Online publication date: Dec-2019
  • Show More Cited By

Index Terms

  1. The design and evaluation of a mobile sensor/actuator network for autonomous animal control

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      IPSN '07: Proceedings of the 6th international conference on Information processing in sensor networks
      April 2007
      592 pages
      ISBN:9781595936387
      DOI:10.1145/1236360
      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]

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 25 April 2007

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. application
      2. autonomous animal control
      3. sensor/actuator networks

      Qualifiers

      • Article

      Conference

      IPSN07
      Sponsor:

      Acceptance Rates

      Overall Acceptance Rate 143 of 593 submissions, 24%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)19
      • Downloads (Last 6 weeks)3
      Reflects downloads up to 22 Feb 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2020)Novel deep learning framework for broadcasting abnormal events obtained from surveillance applicationsJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01668-6Online publication date: 2-Jan-2020
      • (2019)Massive terminal positioning system with snapshot positioning techniqueGPS Solutions10.1007/s10291-018-0821-z23:2(1-14)Online publication date: 1-Apr-2019
      • (2018)A Review of Computational Intelligence Techniques in Wireless Sensor and Actuator NetworksIEEE Communications Surveys & Tutorials10.1109/COMST.2018.285022020:4(2822-2854)Online publication date: Dec-2019
      • (2018)An energy efficient and QoS aware routing protocol for wireless sensor and actuator networksAEU - International Journal of Electronics and Communications10.1016/j.aeue.2017.08.04583(193-203)Online publication date: Jan-2018
      • (2017)A study on IoT solutions for preventing cattle rustling in african contextProceedings of the Second International Conference on Internet of things, Data and Cloud Computing10.1145/3018896.3036396(1-11)Online publication date: 22-Mar-2017
      • (2017)A Multi-Aware Query Driven (MAQD) routing protocol for mobile wireless sensor networks based on neuro-fuzzy inferenceJournal of Network and Computer Applications10.1016/j.jnca.2017.02.01688:C(72-98)Online publication date: 15-Jun-2017
      • (2016)Environmental Monitoring Based on the Wireless Sensor Networking TechnologyMobile Computing and Wireless Networks10.4018/978-1-4666-8751-6.ch058(1332-1374)Online publication date: 2016
      • (2015)An Efficient Agent Location Management for Wireless Sensor NetworkProceedings of the 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conf on Embedded Software and Systems10.1109/HPCC-CSS-ICESS.2015.207(1014-1019)Online publication date: 24-Aug-2015
      • (2014)Energy efficient GPS acquisition with sparse-gpsProceedings of the 13th international symposium on Information processing in sensor networks10.5555/2602339.2602357(155-166)Online publication date: 15-Apr-2014
      • (2014)Environmental Monitoring Based on the Wireless Sensor Networking TechnologyInternational Journal of Agricultural and Environmental Information Systems10.4018/ijaeis.20141001015:4(1-39)Online publication date: 1-Oct-2014
      • Show More Cited By

      View Options

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Figures

      Tables

      Media

      Share

      Share

      Share this Publication link

      Share on social media