Abstract
This disclosure describes a controller for AI-enabled notebook computers that reduces predicted battery aging during video collaboration sessions without relying solely on a coarse system-wide battery-saver policy. The controller detects an active collaboration session, identifies active AI meeting features, and maintains both a session-level battery aging budget and a feature-level battery aging ledger. Using battery, thermal, processor, feature, and meeting-state telemetry, the controller estimates the incremental aging contribution and current importance of each feature, then selectively maintains, reduces, defers, migrates, or disables individual features. Unlike conventional power-saving approaches, the controller dynamically reallocates an aging budget among AI meeting features to preserve minimum collaboration quality, accessibility, privacy, and enterprise-policy requirements while reducing unnecessary battery stress from lower-priority or non-real-time processing.
Creative Commons License
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Recommended Citation
INC, HP, "Battery Aging Budget Controller for AI Meeting Features During Notebook Collaboration Sessions", Technical Disclosure Commons, (September 09, 2026)
https://www.tdcommons.org/dpubs_series/11673