Abstract
A system is disclosed for generating a localized activity chronicle within a private environment. Local cameras capture sparse static snapshots of room environments over a local network. A local smart hub platform receives each snapshot directly into an ephemeral, volatile memory buffer. An on-device vision model, such as a quantized vision-language model executed by a local hardware neural processing unit or other local processing resource, processes the snapshot to generate a time-stamped natural-language description of activities within the private environment. Immediately following text generation, the raw snapshot is purged from the volatile memory, preventing raw image data from being stored on non-volatile media or transmitted over external networks. A localized text-processing engine compiles and formats the descriptions into a chronological, text-only event narrative of the private environment, which is displayed on a user interface. This edge-only architecture helps maintain user privacy while reducing cloud-hosted processing costs and network transmission overhead.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Tao, Karl and Arora, Gaurav, "Localized Generation of Privacy-Preserving Ambient Chronicles", Technical Disclosure Commons, (September 02, 2026)
https://www.tdcommons.org/dpubs_series/11547