Abstract
A smart environment controller receives multi-modal occupancy signals including combinations of Wi-Fi sensing, Bluetooth proximity, acoustic analysis, and entry/lock events. Sensor fusion produces occupant hypotheses indicating identities, classes, and/or counts of occupants. A social context classifier determines a current social context reflecting social composition, such as solo, with-partner, hosting, kids-home, or user-defined contexts. A behavior policy engine maps the social context to coordinated actions across environment dimensions including notification routing, shared-surface content visibility, ambient settings, device routing, and security. Privacy routing rules prevent sensitive information from appearing on shared surfaces when non-primary household members are detected and instead route such information to personal endpoints such as smart glasses or phones. Embodiments include gradual transitions as context evolves, per-room context assignment, guest preference learning, departure anticipation, and emergency override behaviors. Integration with existing smart home platforms may be provided via standard device APIs.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Anonymous, "Multi-Modal Social Context Detection and Automated Environment Behavior Adaptation", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/10622