I Put Face Recognition on My Front Door. It Never Touches the Cloud — and That's the Point.

This report explores the decision to install face recognition on a front door, with the goal of keeping all processing local and avoiding cloud involvement. The author explains that biometrics and cloud integration are not a good fit, as storing face templates in the cloud poses significant security risks. Instead, the system runs entirely on locally owned hardware, with no data leaving the home.

The core insight is that face recognition on modest local hardware can now be achieved in real-time, requiring only a few seconds of processing time. The enrolled faces are stored in a small local database, and the camera performs a quick preliminary check to determine if a person is present, before running a more complex recognition algorithm. This approach minimizes alert fatigue and focuses the system's attention on unfamiliar faces.

The author emphasizes that recognition should function as a filter, silently allowing known individuals while generating alerts only for strangers. However, they caution that local face recognition alone is not reliable enough and should be combined with other inputs, such as whether household members are present, to create a robust system.

The key takeaway is that a multi-layered defense architecture, where multiple independent inputs contribute to a final decision, provides superior security and reliability compared to relying on a single sensor. The system described in this report offers a way to maintain privacy, security, and control over biometric data, without relying on a third-party cloud service.