R. Indumathi,
D. Mohanapriya,
R. Priyadharshini,
D. Devedharshini,
- Assistant Professor, Department of Computer Science and Engineering, Manukula Vinayagar Institute of Technology, Kalitheerthakuppam, Puducherry, India
- Assistant Professor, Department of Computer Science and Engineering, Manukula Vinayagar Institute of Technology, Kalitheerthakuppam, Puducherry, India
- Student, Department of Computer Science and Engineering, Manukula Vinayagar Institute of Technology, Kalitheerthakuppam, Puducherry, India
- Student, Department of Computer Science and Engineering, Manukula Vinayagar Institute of Technology, Kalitheerthakuppam, Puducherry, India
Abstract
SDG 14 is designated as “Life Below Water.” The United Nations established 17 global objectives in 2015. These fall under the parameters of the 2030 Agenda for Sustainable Development. This mission aims to preserve and utilize oceans, seas, and marine resources sustainably to foster peace, equality, and inclusivity. Marine life involves multiple objectives and metrics reliant on oceans for sustenance, climatic stabilization, and economic endeavours. The oceans encompass nearly 70% of the Earth’s surface area. They are a critical component for maintaining life, regulating climate, and fostering economic activities. However, they face significant threats from pollution, climate change, and overexploitation. Monitoring water quality in real-time is essential to determine pollution incidents, assess the ecological health, and lead conservation efforts. This paper shall discuss how the installation of modern sensor technologies may improve our capacity to monitor ocean water quality effectively. The research will thoroughly examine the complex dynamics of aquatic life, focusing on the diverse issues and possible solutions within this essential ecosystem. This will thoroughly examine the diverse variables affecting marine life, including pollution, climate change, overfishing, habitat degradation, and biodiversity loss.
Keywords: IoT, ocean monitoring, Real-time data collection, Early warning systems, Marine environmental monitoring, Smart sensors, Ocean data analytics
[This article belongs to Recent Trends in Sensor Research & Technology ]
R. Indumathi, D. Mohanapriya, R. Priyadharshini, D. Devedharshini. Advanced Sensor Technologies for Real Time Water Quality Monitoring and Prevention of Pollution. Recent Trends in Sensor Research & Technology. 2025; 12(01):9-14.
R. Indumathi, D. Mohanapriya, R. Priyadharshini, D. Devedharshini. Advanced Sensor Technologies for Real Time Water Quality Monitoring and Prevention of Pollution. Recent Trends in Sensor Research & Technology. 2025; 12(01):9-14. Available from: https://journals.stmjournals.com/rtsrt/article=2025/view=195029
References
- Jaiganesh S, Mittal H. Towards a Sustainable Ocean Ecosystem: Innovations in Plastic Pollution Mitigation, Policy Collaborations, and Technological Advancements. Journal of Student Research. 2023 Nov 30;12(4).
- Murawski SA. Definitions of overfishing from an ecosystem perspective. ICES Journal of Marine Science. 2000 Jun 1;57(3):649-58.
- Alloghani MA. Using AI to Monitor Marine Environmental Pollution: Systematic Review. Artificial Intelligence and Sustainability. 2023 Nov 26:87-97.
- Fine M, Cinar M, Voolstra CR, Safa A, Rinkevich B, Laffoley D, Hilmi N, Allemand D. Coral reefs of the Red Sea—Challenges and potential solutions. Regional Studies in Marine Science. 2019 Jan 1; 25:100498.
- Mostofa KM, Liu CQ, Zhai W, Minella M, Vione D, Gao K, Minakata D, Arakaki T, Yoshioka T, Hayakawa K, Konohira E. Reviews and Syntheses: Ocean acidification and its potential impacts on marine ecosystems. Biogeosciences. 2016 Mar 23;13(6):1767-86.
- Xu G, Shi Y, Sun X, Shen W. Internet of things in marine environment monitoring: A review. Sensors. 2019 Apr 10;19(7):1711.
- Sheffield J, Wood EF, Pan M., Beck H, Coccia G, Serrat‐Capdevila A, Verbist KJ. Satellite remote sensing for water resources management: Potential for supporting sustainable development in data‐poor regions. Water Resources Research. 2018 Dec;54(12):9724-58.
- Rochman CM. Strategies for reducing ocean plastic debris should be diverse and guided by science. Environmental Research Letters. 2016 Mar 23;11(4):041001.
- Yang J, Wen J, Wang Y, Jiang B, Wang H, Song H. Fog-based marine environmental information monitoring toward ocean of things. IEEE Internet of Things Journal. 2019 Oct 11;7(5):4238-47.
- Apte SD, Sandbhor S, Kulkarni R, Khanum H. Machine learning approach for automated beach waste prediction and management system: A case study of Mumbai. Frontiers in Mechanical Engineering. 2023 Feb 3; 9:1120042.
- Ghazali NH, Salahuddin JS. New innovations and technologies in coastal rehabilitation. InProceeding of the International Conference on Innovations and Technologies in Oceanography for Sustainable Development, Malaysia. Retrieved from http://test.esmology. com/water/images/pdf/innovation_CoastalRehab. pdf 2005 Nov.

Recent Trends in Sensor Research & Technology
| Volume | 12 |
| Issue | 01 |
| Received | 07/01/2025 |
| Accepted | 11/01/2025 |
| Published | 29/01/2025 |
| Publication Time | 22 Days |
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