Science and Technology
Modern Techniques in the Underwater Sediment Classification: Can Machine Learning (ML) provide another path?
Bhavin Jain
MRC Intern, IIT Bombay
Key Highlights
- Remote sensing technologies are methods for acquiring information about the Earth’s surface and subsurface without direct physical contact.
- A sub-bottom profiler generates low-frequency sonar waves that penetrate the seafloor, reflecting off various subsurface sediment layers.
- Continuous refinement of these models can enhance accuracy over time, ensuring more efficient and effective analysis in the future.
- Existing methods play a very important role in solving this issue, but a future of machine learning and artificial intelligence can provide an efficient and intelligent solution.
Overview
This article will discuss the different methods currently used for sediment classification, ranging from traditional field methods to remote sensing and GIS. It will also explain why sediment classification is essential and the need for a more straightforward approach to this problem. It will detail how machine learning can provide approximate yet valuable answers to this problem and make it a much simpler problem.
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Bhavin Jain
MRC Intern, IIT Bombay
Bhavin Jain is pursuing a BTech degree in Civil Engineering from IIT Bombay. He is interested in data analytics and marine ecosystems and loves to read all forms of literature.