Skip to main content

Designing of an Underwater-Internet of Things (U-IoT) for Marine Life Monitoring

  • Conference paper
  • First Online:
The Fourth Industrial Revolution and Beyond

Abstract

Marine life and environmental monitoring of deep sea have become a major field of interest for quite a long time because of the immeasurable region of the area of the ocean that comes with its own dynamics and vulnerabilities. Creating the Underwater-Internet of Things (U-IoT) model within Underwater Wireless Sensor Network (UWSN) provides the scope of ensuring proper marine life monitoring which supports the aspects of 4th Industrial Revolution. The U-IoT network model is designed for an automated, efficient, smart process of data transfer for both underwater and overwater communications through acoustic waves and Radio Frequency (RF) data transfer techniques, respectively. The proposed U-IoT network model is created with an optimum number of autonomous underwater vehicles (AUVs) and surface sinks in order to address Bangladesh’s overfishing problem (e.g., hilsa overfishing problem) which guarantees efficient management of the banning period by the authority. The network model is evaluated by comparing different deployment methods of AUVs and surface sinks taking the South Patch region of Bay of Bengal as the target area. The result shows that the proposed model transfers adequate data of marine life motion from the seafloor can enhance efficient administration of the overfishing problem.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover 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

Similar content being viewed by others

References

  1. Leape, J., William, E.P.: Harnessing the Fourth Industrial Revolution for Oceans. World Economic Forum (2017)

    Google Scholar 

  2. Byun, J.I., Choi, S.W., Song, M.H., Chang, B.U., Kim, Y.J., Yun, J.Y.: A large buoy-based radioactivity monitoring system for gamma-ray emitters in surface seawater. Appl. Radiat. Isot. 162, 109172 (2020)

    Article  Google Scholar 

  3. Muller-Karger, F.E., Miloslavich, P., Bax, N.J., Simmons, S., Costello, M.J., Sousa Pinto, I., Canonico, G., Turner, W., Gill, M., Montes, E., et al.: Advancing marine biological observations and data requirements of the complementary essential ocean variables (EOVs) and essential biodiversity variables (EBVs) frameworks. Frontiers Mar. Sci. 5, 211 (2018)

    Article  Google Scholar 

  4. Meyer, V., Audoly, C.: A parametric study of the environment and the array configuration for underwater noise measurement from ships in shallow water. In: Proceedings of the 26th International Congress on Sound and Vibrations (2019)

    Google Scholar 

  5. Williams, M., Kookana, R.S., Mehta, A., Yadav, S., Tailor, B., Maheshwari, B.: Emerging contaminants in a river receiving untreated wastewater from an Indian Urban Centre. Sci. Total Environ. 647, 1256–1265 (2019)

    Article  Google Scholar 

  6. Hall-Spencer, J.M., Harvey, B.P.: Ocean acidification impacts on coastal ecosystem services due to habitat degradation. Emerg. Topics Life Sci. 3(2), 197–206 (2019)

    Article  Google Scholar 

  7. Bernard, C., Bouvet, P.J., Pottier, A., Forjonel, P.: Multiple access acoustic communication in underwater mobile networks. In: 2021 Fifth Underwater Communications and Networking Conference (UComms) (2021)

    Google Scholar 

  8. Chen, J., Dai, Z., Chen, Z.: Development of radio-frequency sensor wake-up with unmanned aerial vehicles as an aerial gateway. Sensors 19(5), 1047 (2019)

    Article  Google Scholar 

  9. Huang, J., Wang, H., He, C., Zhang, Q., Jing, L.: Underwater acoustic communication and the general performance evaluation criteria. Frontiers Inform. Technol. Electron. Eng. 19(8), 951–971 (2018)

    Google Scholar 

  10. Das, B., Ali, K., Memon, S., Shakoor, A., et al.: Monitoring of water quality of aquarium by using IoT technology. J. Appl. Eng. Technol. (JAET) 4(2), 22–34 (2020)

    Google Scholar 

  11. Kim, S., Choi, J.W.: Optimal deployment of sensor nodes based on performance surface of underwater acoustic communication. Sensors 17(10), 2389 (2017)

    Article  Google Scholar 

  12. Duan, J.L., Lin, B., Cai, L.X., Liu, Y.X., Wu, Y.: Node deployment of marine monitoring networks: a multiobjective optimization scheme. Sensors 20(16), 4480 (2020)

    Article  Google Scholar 

  13. Reddy, T., Swarna Priya, R.M., Parimala, M., Chowdhary, C.L., Hakak, S., Khan, W.Z., et al.: A deep neural networks based model for uninterrupted marine environment monitoring. Comput. Commun. 157, 64–75 (2020)

    Google Scholar 

  14. Ghoreyshi, S.M., Shahrabi, A., Boutaleb, T.: An efficient AUV-aided data collection in underwater sensor networks. In: 2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA), pp. 281–288. IEEE (2018)

    Google Scholar 

  15. Yoon, S., Azad, A.K., Oh, H., Kim, S.: AURP: An AUV-aided underwater routing protocol for underwater acoustic sensor networks. Sensors 12(2), 1827–1845 (2012)

    Article  Google Scholar 

  16. Zenia, N.Z., Aseeri, M., Ahmed, M.R., Chowdhury, Z.I., Kaiser, M.S.: Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network: a survey. J. Netw. Comput. Appl. 71, 72–85 (2016)

    Article  Google Scholar 

  17. Arul, R., Alroobaea, R., Mechti, S., Rubaiee, S., Andejany, M., Tariq, U., Iftikhar, S.: Intelligent data analytics in energy optimization for the internet of underwater things. Soft Comput. 25(18), 12507–12519 (2021)

    Article  Google Scholar 

  18. Miah, M.S.: Climatic and anthropogenic factors changing spawning pattern and production zone of Hilsa fishery in the bay of Bengal. Weather Clim. Extremes 7, 109–115 (2015)

    Article  Google Scholar 

  19. Kim, S., Choi, J.W.: Optimal deployment of vector sensor nodes in underwater acoustic sensor networks. Sensors 19(13), 2885 (2019)

    Article  Google Scholar 

  20. González-García, J., Gómez-Espinosa, A., Cuan-Urquizo, E., García-Valdovinos, L.G., Salgado-Jiménez, T., Cabello, J.A.E.: Autonomous underwater vehicles: localization, navigation, and communication for collaborative missions. Appl. Sci. 10(4), 1256 (2020)

    Article  Google Scholar 

  21. Mekki, K., Bajic, E., Chaxel, F., Meyer, F.: A comparative study of LPWAN technologies for large-scale IoT deployment. ICT Exp. 5(1), 1–7 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. Habibul Kabir .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sazzad, A., Nawer, N., Mahbub Rimi, M., Habibul Kabir, K., Foysal Haque, K. (2023). Designing of an Underwater-Internet of Things (U-IoT) for Marine Life Monitoring. In: Hossain, M.S., Majumder, S.P., Siddique, N., Hossain, M.S. (eds) The Fourth Industrial Revolution and Beyond. Lecture Notes in Electrical Engineering, vol 980. Springer, Singapore. https://doi.org/10.1007/978-981-19-8032-9_21

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-8032-9_21

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-8031-2

  • Online ISBN: 978-981-19-8032-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics