Skip to main content
SpringerLink
Log in

Optimization of Deer Repellent Devices Placement Based on Hill Climbing and Acoustic Ray Tracing

  • Conference paper
  • First Online:
Advances in Internet, Data & Web Technologies (EIDWT 2024)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 193))

Included in the following conference series:

  • 257 Accesses

Abstract

Deer repelling sound is affected by the attenuation of reflected sound due to terrain undulations and air absorption. Therefore, sound wave propagation analysis can be used to decide the location of devices. This paper deals with the optimization of deer repellent device placement using the mountaineering and acoustic ray tracking methods. A Digital Elevation Model (DEM) for mid-mountainous areas is used for the placement of deer repellent devices takinginto account the undulations of the terrain. We use OpenStreetMap (OSM) to get the location of deers in their living environment. Simulation results show that the proposed system is able to optimize the placement of deer repellent devices by maximizing network connectivity and deer repellent sound range.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Shimura, S., et al.: Development of an acoustic deterrent to prevent deer-train collisions. Q. Report RTRI 59(3), 207–211 (2018)

    Article  Google Scholar 

  2. Honda, T.: A sound deterrent prevented deer intrusions at the intersection of a river and fence. Mammal Study 44(4), 269–274 (2019)

    Article  Google Scholar 

  3. Matsuzaki, H.: Acoustic measurement of deer alert whistles and investigation of sika deer reaction to alert sounds played back through loudspeaker. Wildlife Hum. Soc. 9, 75–85 (2021)

    Google Scholar 

  4. Heffner, H., et al.: The behavioral audiogram of whitetail deer (Odocoileus virginianus). J. Acoust. Soc. Am. 127(3), 111–114 (2010)

    Article  Google Scholar 

  5. Jackson, L.L., et al.: Free-field audiogram of the Japanese macaque (Macaca fuscata). J. Acoust. Soc. Am. 106(5), 3017–3023 (1999)

    Article  Google Scholar 

  6. Roubaiey, A., et al.: Reliable middleware for wireless sensor-actuator networks. IEEE Access 7, 14099–14111 (2019)

    Article  Google Scholar 

  7. Akyildiz, I.F., et al.: Wireless mesh networks: a survey. Comput. Netw. 47(4), 445–487 (2005)

    Article  Google Scholar 

  8. Sabrine, K., et. al.: Precision irrigation: an IoT-enabled wireless sensor network for smart irrigation systems. In: Women in Precision Agriculture: Technological Breakthroughs, Challenges and Aspirations for a Prosperous and Sustainable Future, pp. 107-129 (2021)

    Google Scholar 

  9. Saleem, R., et. al.: Industrial wireless sensor and actuator networks in industry 4.0: exploring requirements, protocols, and challenges - A MAC survey. Int. J. Commun. Syst. 32(15), e4074 (2019)

    Google Scholar 

  10. Asada, S., et. al.: A simulated annealing based simulation system for optimization of wild deer damage prevention devices. In: International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 38-44 (2019)

    Google Scholar 

  11. Harris, C.M.: Absorption of sound in air versus humidity and temperature. J. Acoust. Soc. Am. 40(1), 148–159 (1966)

    Article  Google Scholar 

  12. Seddeq, H.S.: Factors influencing acoustic performance of sound absorptive materials. Aust. J. Basic Appl. Sci. 3(4), 4610–4617 (2009)

    Google Scholar 

  13. Nagai, Y., et. al.: A CCM, SA and FDTD based mesh router placement optimization in WMN. In: Conference on Complex, Intelligent, and Software Intensive Systems, pp. 48-58 (2023)

    Google Scholar 

  14. Nagai, Y., et. al.: A wireless sensor network testbed for monitoring a water reservoir tank: experimental results of delay and temperature prediction by LSTM. In: International Conference on Network-Based Information Systems, pp. 392-401 (2022)

    Google Scholar 

  15. Nagai, Y., et. al.: Wireless visual sensor node placement optimization considering different distributions of events. In: International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 312-322 (2023)

    Google Scholar 

  16. K. M. Li, et. al.,“An improved ray-tracing algorithm for predicting sound propagation outdoors”, The Journal of the Acoustical Society of America, Vol. 104, No. 4, pp. 2077-2083, 1998

    Google Scholar 

  17. Hou, Q., et. al.: Dynamic modeling of traffic noise in both indoor and outdoor environments by using a ray tracing method. Build. Environ. 121, 225–237 (2017)

    Google Scholar 

  18. Economou, P., et. al.: Accuracy of wave based calculation methods compared to ISO 9613-2. In: Proceedings of Noise-Con 2014 (2014)

    Google Scholar 

Download references

Acknowledgement

This work was supported by JSPS KAKENHI Grant Number JP20K19793.

Author information

Authors and Affiliations

  1. Graduate School of Science and Engineering, Okayama University of Science (OUS), Okayama, 1-1 Ridaicho, Kita-ku, Okayama, 700–0005, Japan

    Sora Asada

  2. Graduate School of Engineering, Okayama University of Science (OUS), Okayama, 1-1 Ridaicho, Kita-ku, Okayama, 700–0005, Japan

    Yuki Nagai, Kyohei Wakabayashi & Chihiro Yukawa

  3. Department of Information and Computer Engineering, Okayama University of Science (OUS), 1-1 Ridaicho, Kita-ku, Okayama, 700–0005, Japan

    Tetsuya Oda

  4. Department of Informention and Communication Engineering, Fukuoka Insitute of Technology, 3-30-1 Wajiro-Higashi-ku, Fukuoka, 811-0295, Japan

    Leonard Barolli

Authors
  1. Sora Asada
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuki Nagai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kyohei Wakabayashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chihiro Yukawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tetsuya Oda
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Leonard Barolli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tetsuya Oda .

Editor information

Editors and Affiliations

  1. Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Asada, S., Nagai, Y., Wakabayashi, K., Yukawa, C., Oda, T., Barolli, L. (2024). Optimization of Deer Repellent Devices Placement Based on Hill Climbing and Acoustic Ray Tracing. In: Barolli, L. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 193. Springer, Cham. https://doi.org/10.1007/978-3-031-53555-0_52

Download citation

Publish with us

Policies and ethics

Search

Navigation