An Urban Oceanography Perspective on Intelligent Fishing Gear for Sustainable Engineering

The rapid expansion of global coastal urban agglomerations is exerting dual pressures of ecosystem degradation and resource use conflicts on nearshore environments. Traditional fishing equipment and extensive management paradigms are increasingly inadequate in addressing the highly complex and dynamically changing urban marine areas. Although smart technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI) present revolutionary opportunities for upgrading fishing gear, current research predominantly focuses on technical performance itself, lacking a systemic perspective that places these technologies within the overall governance framework of urban marine ecosystems. To bridge this gap between technological development and systemic governance, this paper introduces the theoretical framework of urban oceanography. We propose an innovative Sensing Decision-Action conceptual model, elucidating how intelligent fishing equipment can transcend its traditional role, evolving into the real-time sensory nerves of the urban marine environment, the precise executive tools for management strategies, and the core data engine for scientific decision-making. This paper systematically reviews technological frontiers such as smart fishing gear, vessel energy management, and remote sensing detection. Furthermore, it outlines a future-oriented, cross-disciplinary research agenda encompassing the development of low-cost sensors, the design of data-sharing mechanisms, and policy incentives for technology adoption. The research demonstrates that deeply integrating intelligent fishing equipment into the practice of urban oceanography is a critical pathway for constructing a resilient, efficient, and sustainable urban marine resource management system.

urban oceanography; intelligent fishing equipment; sensing-decision-action framework; sustainable governance

1. Dallimer, M., Tang, Z., Bibby, P. R., Brindley, P., Gaston, K. J., & Davies, Z. G. (2011). Temporal changes in greenspace in a highly urbanized region. Biology letters, 7(5), 763-766. [Google Scholar] [Crossref]

2. Bloom, D. E. (2011). 7 billion and counting. Science, 333(6042), 562-569. [Google Scholar] [Crossref]

3. Creel, L. (2003). Ripple effects: population and coastal regions (pp. 1-7). Washington, DC: Population reference bureau. [Google Scholar] [Crossref]

4. Small, C., & Nicholls, R. J. (2003). A global analysis of human settlement in coastal zones. Journal of coastal research, 584-599. [Google Scholar] [Crossref]

5. Konishi, H. (2000). Formation of hub cities: transportation cost advantage and population agglomeration. Journal of Urban Economics, 48(1), 1-28. [Google Scholar] [Crossref]

6. Li, H. (2003). Management of coastal megacities—a new challenge in the 21st century. Marine Policy, 27(4), 333-337. [Google Scholar] [Crossref]

7. Dafforn, K. A., Glasby, T. M., Airoldi, L., Rivero, N. K., Mayer-Pinto, M., & Johnston, E. L. (2015). Marine urbanization: an ecological framework for designing multifunctional artificial structures. Frontiers in Ecology and the Environment, 13(2), 82-90. [Google Scholar] [Crossref]

8. Firth, L. B., Knights, A. M., Bridger, D., Evans, A. J., Mieszkowska, N., Moore, P. J., ... & Hawkins, S. J. (2016). Ocean sprawl: challenges and opportunities for biodiversity management in a changing world. Oceanography and Marine Biology: an annual review, 54, 189-262. [Google Scholar] [Crossref]

9. Tian, B., Wu, W., Yang, Z., & Zhou, Y. (2016). Drivers, trends, and potential impacts of longterm coastal reclamation in China from 1985 to 2010. Estuarine, Coastal and Shelf Science, 170, 83-90. [Google Scholar] [Crossref]

10. Firth, L. B., Thompson, R. C., Bohn, K., Abbiati, M., Airoldi, L., Bouma, T. J., ... & Hawkins, S. J. (2014). Between a rock and a hard place: Environmental and engineering considerations when designing coastal defence structures. Coastal Engineering, 87, 122-135. [Google Scholar] [Crossref]

11. Huang, H., Cai, H., Qureshi, J. U., Mehdi, S. R., Song, H., Liu, C., ... & Sun, Z. (2023). Proceeding the categorization of microplastics through deep learning-based image segmentation. Science of the Total Environment, 896, 165308. [Google Scholar] [Crossref]

12. Mehdi, S. R., Raza, K., Huang, H., Naqvi, R. A., Ali, A., & Song, H. (2022). Combining deep learning with single-spectrum UV imaging for rapid detection of HNSs spills. Remote Sensing, 14(3), 576. [Google Scholar] [Crossref]

13. Dyson, K., & Yocom, K. (2015). Ecological design for urban waterfronts. Urban ecosystems, 18(1), 189-208. [Google Scholar] [Crossref]

14. Madia, M., Bottaro, M., Cillari, T., Li Vorsi, A., Castriota, L., Amico, M. R., ... & Sinopoli, M. (2024). Reducing Artisanal Fishery Impact on Marine Community: New Data from Comparison of Innovative and Traditional Gear. Fishes, 9(5), 171. [Google Scholar] [Crossref]

15. Abeysinghe, K. C., Weerarathne, A. G. P. T., Colonne, D. K. C., & Bellanthudawa, B. K. A. (2025). Sustainable development goals (SDGs), climate change, and the development of aquaculture and fisheries industries. Environmental Reviews, (ja). [Google Scholar] [Crossref]

16. Cooke, S. J., Docker, M. F., Mandrak, N. E., Young, N., Heath, D. D., Jeffries, K. M., ... & Muir, A. M. (2022). Technoscience and the modernization of freshwater fisheries assessment and management. Environmental Technology & Innovation, 28, 102865. [Google Scholar] [Crossref]

17. Wu, Y., Duan, Y., Wei, Y., An, D., & Liu, J. (2022). Application of intelligent and unmanned equipment in aquaculture: A review. Computers and Electronics in Agriculture, 199, 107201. [Google Scholar] [Crossref]

18. Blumberg, A. F., & Bruno, M. S. (2018). The urban ocean: the interaction of cities with water. Cambridge University Press. [Google Scholar] [Crossref]

19. Todd, P. A., Heery, E. C., Loke, L. H., Thurstan, R. H., Kotze, D. J., & Swan, C. (2019). Towards an urban marine ecology: characterizing the drivers, patterns and processes of marine ecosystems in coastal cities. Oikos, 128(9), 1215-1242. [Google Scholar] [Crossref]

20. Wells, F. E., Tan, K. S., Todd, P. A., Jaafar, Z., & Yeo, D. C. (2019). A low number of introduced marine species in the tropics: a case study from Singapore. Management of Biological Invasions, 10(1), 23-45. [Google Scholar] [Crossref]

21. Lotze, H. K., Lenihan, H. S., Bourque, B. J., Bradbury, R. H., Cooke, R. G., Kay, M. C., ... & Jackson, J. B. (2006). Depletion, degradation, and recovery potential of estuaries and coastal seas. Science, 312(5781), 1806-1809. [Google Scholar] [Crossref]

22. Ling, S. D., Davey, A., Reeves, S. E., Gaylard, S., Davies, P. L., Stuart-Smith, R. D., & Edgar, G. J. (2018). Pollution signature for temperate reef biodiversity is short and simple. Marine Pollution Bulletin, 130, 159-169. [Google Scholar] [Crossref]

23. Yasir, M., Zhan, L., Liu, S., Wan, J., Hossain, M. S., Isiacik Colak, A. T., ... & Yang, Q. (2023). Instance segmentation ship detection based on improved Yolov7 using complex background SAR images. Frontiers in Marine Science, 10, 1113669. [Google Scholar] [Crossref]

24. Song, H., Mehdi, S. R., Zhang, Y., Shentu, Y., Wan, Q., Wang, W., ... & Huang, H. (2021). Development of coral investigation system based on semantic segmentation of singlechannel images. Sensors, 21(5), 1848. [Google Scholar] [Crossref]

25. Chee, S. Y., Othman, A. G., Sim, Y. K., Adam, A. N. M., & Firth, L. B. (2017). Land reclamation and artificial islands: Walking the tightrope between development and conservation. Global ecology and conservation, 12, 80-95. [Google Scholar] [Crossref]

26. Song, H., Mehdi, S. R., Huang, H., Shahani, K., Zhang, Y., Raza, K., & Khan, M. A. (2020). Classification of freshwater zooplankton by pre-trained convolutional neural network in underwater microscopy. International Journal of Advanced Computer Science and Applications, 11(7). [Google Scholar] [Crossref]

27. Strain, E. M., Olabarria, C., Mayer‐Pinto, M., [Google Scholar] [Crossref]

28. Cumbo, V., Morris, R. L., Bugnot, A. B., ... & Bishop, M. J. (2018). Eco‐engineering urban infrastructure for marine and coastal biodiversity: Which interventions have the greatest ecological benefit? Journal of Applied Ecology, 55(1), 426-441. [Google Scholar] [Crossref]

29. Canton, H. (2021). Food and agriculture organization of the United Nations—FAO. In The Europa directory of international organizations 2021 (pp. 297-305). Routledge. [Google Scholar] [Crossref]

30. Guan, S., Qu, F., & Qiao, F. (2023). United Nations Decade of Ocean Science for Sustainable Development (2021-2030): From innovation of ocean science to science-based ocean governance. Frontiers in Marine Science, 9, 1091598. [Google Scholar] [Crossref]

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