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Work item:
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F.CVADS
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Subject/title:
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Requirements and framework for computer vision-based anomaly detection service in wind farm
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Status:
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Under study [Issued from previous study period]
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Approval process:
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AAP
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Type of work item:
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Recommendation
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Version:
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New
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Equivalent number:
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-
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Timing:
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2025 (Medium priority)
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Liaison:
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IEC/TC129, ITU-T SG20 , ISO/TC83, IEEE CS
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Supporting members:
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State Grid of China, China Telecom, Huawei Technology (China), Electronic and Telecommunication Research Institute(Korea), ZTE Communications Ltd, Zhejiang Lab, China Unicom.
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Summary:
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Traditional video surveillance system usually discovers the anomaly by manually observing videos and cannot meet the need for automatic anomaly detection in the wind farm. With the development of machine learning algorithms, computer vision can achieve automatic intelligent processing such as image enhancement, image restoration, feature extraction, object detection, object recognition, object tracking, pose estimation, motion estimation, event detection, and anomaly detection. Therefore, an intelligent system based on computer vision can be deployed on a wind farm for automatic anomaly detection.
The computer vision-based anomaly detection service can be an effective way to automatically detect general anomalies such as vessel trespass, small flames, and abnormal appearances in the wind farm. It can compensate for the way in which general anomalies are detected by manually observing video and avoiding the missed anomaly due to human negligence.
This Recommendation addresses the essential requirements and framework for computer vision-based anomaly detection service in the wind farm.
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Comment:
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-
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Reference(s):
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Historic references:
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Contact(s):
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First registration in the WP:
2023-08-23 14:28:05
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Last update:
2025-03-05 13:30:39
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