Discussion
Started 17th Jan, 2023

Are the sciences related to oceanography prepared for the fourth industrial revolution?

Artificial intelligence (AI) is a rapidly advancing tool. It is heavily reliant on programming languages, data manipulation and analysis. As colleagues in the field of oceanography, I would like to know your opinions on the use of AI in this field. Furthermore, I would appreciate any recommendations for publications that could support your viewpoints.
It is important to be transparent about the limitations in terms of programming for the diferent subfields of oceanography, such as physical, chemical, biological, ecosystemic, and geological; how the incorporation of AI may lead to new disparities in scientific research; and how careful you would be with the use of these tools.
Thanks for your times!

Popular replies (1)

18th Jan, 2023
Qamar Ul Islam
Universiti Sains Malaysia
Sebastian Enrique Cornejo Guzmán AI is becoming an increasingly significant tool in oceanography because of its ability to handle and analyze vast volumes of data rapidly and efficiently. It is crucial to highlight, however, that the application of AI in oceanography may result in research inequities, since certain subfields may have more resources and skills to deploy AI-based methodologies than others. Furthermore, it is critical to be open about the limitations of AI in each sector and to utilize the technology with caution, ensuring that the findings are accurate and dependable.
There are several papers that explore the application of AI in oceanography, some of which are as follows:
  • "Deep Learning in Oceanography: A Review" by B. Kostas et al. (2019)
  • "Artificial Intelligence in Oceanography: Challenges and Opportunities" by J. Chen et al. (2019)
  • "The Role of Artificial Intelligence in Oceanography and Marine Affairs" by S. J. Kim et al. (2018)
These papers can give more thorough information on the application of AI in oceanography, including possible advantages and problems.
3 Recommendations

All replies (3)

18th Jan, 2023
Qamar Ul Islam
Universiti Sains Malaysia
Sebastian Enrique Cornejo Guzmán AI is becoming an increasingly significant tool in oceanography because of its ability to handle and analyze vast volumes of data rapidly and efficiently. It is crucial to highlight, however, that the application of AI in oceanography may result in research inequities, since certain subfields may have more resources and skills to deploy AI-based methodologies than others. Furthermore, it is critical to be open about the limitations of AI in each sector and to utilize the technology with caution, ensuring that the findings are accurate and dependable.
There are several papers that explore the application of AI in oceanography, some of which are as follows:
  • "Deep Learning in Oceanography: A Review" by B. Kostas et al. (2019)
  • "Artificial Intelligence in Oceanography: Challenges and Opportunities" by J. Chen et al. (2019)
  • "The Role of Artificial Intelligence in Oceanography and Marine Affairs" by S. J. Kim et al. (2018)
These papers can give more thorough information on the application of AI in oceanography, including possible advantages and problems.
3 Recommendations
18th Jan, 2023
Amboka Asumwa Agustine
Institute of Energy studies &Research,Nairobi Kenya.
Qamar Ul Islam , I would concur.
19th Jan, 2023
Rudra Tiwari
It is difficult to say whether the sciences related to oceanography as a whole are prepared for the fourth industrial revolution. However, there have been recent advancements in technologies such as autonomous underwater vehicles, satellite remote sensing, and big data analytics that are being used to improve our understanding and management of the ocean. Additionally, interdisciplinary approaches, such as oceanography's integration with computer science and data science, are increasing. These advances in technology and interdisciplinary collaboration are likely to play a significant role in shaping the future of oceanography.

Similar questions and discussions

How are artificial intelligence and machine learning being applied to tackle complex problems and boost efficiency in a variety of fields?
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29 replies
  • Qamar Ul IslamQamar Ul Islam
AI and machine learning (ML) are being utilized to tackle complicated issues and increase efficiency in a variety of sectors. Here are some instances of how AI and ML are being applied in various industries:
- AI and machine learning are being utilized in healthcare to evaluate medical pictures, aid with diagnosis, and build individualized treatment regimens. They are also used to identify people who are at risk of developing certain diseases and to create novel medications.
- Finance: AI and ML are being used to detect and prevent fraud, evaluate financial markets, and generate predictions about market movements. They are also utilized to deliver customized financial advice and to automate a variety of typical financial duties.
- Retail: Artificial intelligence and machine learning are being used to optimize prices and inventory, customize suggestions, and increase supply chain efficiency. They are also utilized to assist merchants in better understanding their clients and improving the online purchasing experience.
- Manufacturing: Artificial intelligence and machine learning are being utilized to streamline manufacturing processes, increase quality control, and minimize downtime. They are also used to forecast equipment breakdown, allowing maintenance to be arranged ahead of time, and reducing downtime and expenses.
- Transportation: Artificial intelligence and machine learning are being utilized to streamline logistics, route planning, and traffic control, boosting overall efficiency and lowering costs. They are also used to monitor the fleet and forecast repair needs, resulting in less downtime and lower expenses.
- AI and machine learning are being utilized in agriculture for precision farming, crop monitoring, and weather forecasting. They also aid in the optimization of irrigation and fertilization, the reduction of pesticide usage, and the improvement of agricultural yields.
In general, AI and ML may aid in the automation of repetitive operations, the processing of vast volumes of data, and the making of predictions and choices. This can result in increased efficiency, cost savings, and fresh insights in a variety of industries.

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