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Work item:
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Y.IoT-DQA-FMT
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Subject/title:
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Assessment metrics for IoT data quality in foundation model training
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Status:
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Under study
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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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2027-Q3 (Medium priority)
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Liaison:
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ITU-T SG21, ISO/IEC JTC1/SC42
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Supporting members:
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Zhejiang Dahua Technology, China Information Communication Technologies Group, Electronics and Telecommunications Research Institute, China Unicom, China Telecom
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Summary:
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IoT data is the cornerstone of intelligent decision-making and large-scale machine learning model training. It provides real-time, accurate environmental and device information, playing a crucial role in enhancing intelligence levels, optimizing prediction accuracy, and improving application effectiveness. This document aims to establish specialized IoT data quality assessment metrics in foundational model training. By ensuring that foundational models are trained and deployed using high-quality IoT data, it can help improve the accuracy, stability, and applicability of these models.
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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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| ITU-T A.5 justification(s): |
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First registration in the WP:
2025-01-30 13:10:02
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Last update:
2025-10-13 10:12:11
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