Lumisafe is designed with your privacy as a top priority. A core feature of our fall detection system is its commitment to processing all data 100% locally on the device. This means that sensitive information never leaves the Lumisafe unit itself, providing a robust layer of security and privacy.

Unlike systems that might send data to external servers or the cloud for processing, Lumisafe keeps everything in-house. The device captures data using a time-of-flight depth sensor. This type of sensor is crucial for privacy because it captures depth information, not traditional visual images (RGB data). This ensures that personal details or identifiable features are never recorded.

The depth data captured by the sensor is immediately processed by built-in machine-learning models directly on the Lumisafe device. These models are specifically trained for tasks like pose estimation and accurate fall detection. The entire analysis happens locally, eliminating the need to transmit raw or processed data over a network for analysis elsewhere.

Furthermore, the machine-learning models on Lumisafe devices can continue to train and improve locally based on the specific environment they are installed in. This personalized training also occurs entirely on the device, using open source hardware solutions. This local training enhances accuracy over time without compromising privacy by sending data externally.

This 100% local processing architecture is fundamental to Lumisafe's privacy-friendly design. It ensures that the system can accurately detect falls in sensitive areas like public restrooms, bathrooms, and healthcare environments without collecting or storing personal visual information or transmitting data that could be intercepted or misused. By keeping all data processing on the device, Lumisafe provides peace of mind, knowing that your privacy is protected while ensuring safety through reliable fall detection.