Real-Time Anomaly Detection in Underwater Gliders: Abstract and Intro

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This story was originally published on HackerNoon at: https://hackernoon.com/real-time-anomaly-detection-in-underwater-gliders-abstract-and-intro.
This paper presents a real-time anomaly detection algorithm to enhance underwater glider safety, using datasets from actual deployments.
Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-analysis, #machine-learning, #underwater-gliders, #anomaly-detection, #oceanography, #glider-navigation, #ocean-data, #marine-robotics, and more.
This story was written by: @oceanography. Learn more about this writer by checking @oceanography's about page, and for more stories, please visit hackernoon.com.
Underwater gliders are widely used in oceanography for a range of applications. However, unpredictable events like shark strikes or remora attachments can lead to abnormal glider behavior or even loss of the instrument. This paper employs an anomaly detection algorithm to assess operational conditions of underwater gliders in the real-world ocean environment. Prompt alerts are provided to glider pilots upon detecting any anomaly.

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Real-Time Anomaly Detection in Underwater Gliders: Abstract and Intro

Data Science Tech Brief By HackerNoon

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Real-Time Anomaly Detection in Underwater Gliders: Abstract and Intro