Lumisafe is designed as a privacy-friendly fall detection system. Our core mission is to provide reliable safety monitoring while ensuring that personal privacy is always protected. Unlike many systems that rely on traditional cameras or cloud processing, Lumisafe takes a different approach, focusing on local data handling and privacy-preserving technology.

A key element of Lumisafe's design is its commitment to processing all data directly on the device. This means that sensitive information never leaves the Lumisafe unit itself. The system uses Time-of-Flight depth sensors, which capture distance information rather than traditional visual images. This type of sensor inherently avoids capturing identifiable features, forming the first layer of privacy protection.

To enable this 100% local data processing, Lumisafe utilizes open source hardware solutions. By building upon open source platforms, we ensure transparency and control over how the device handles data. This choice in hardware architecture is fundamental to our privacy-first philosophy. It allows the device to capture depth data, run sophisticated machine learning models, and even train personalized models based on the specific environment, all without needing an external connection for processing.

The integration of open source hardware with local processing provides significant benefits. It eliminates the risks associated with transmitting sensitive data over networks or storing it in remote servers. Users can have confidence that the information used for fall detection stays securely within their own space. This approach is particularly crucial for sensitive locations like restrooms, bathrooms, and healthcare facilities where privacy is paramount.

Within the Lumisafe device, pretrained machine learning models analyze the depth data to accurately detect falls. These models, including those for pose estimation and fall detection, operate entirely locally. Furthermore, the system can continue to train these models locally using the captured depth data, improving accuracy over time based on the unique characteristics of the installation environment. This local training capability is also facilitated by the robust, open source hardware platform.

In summary, Lumisafe's use of open source hardware solutions is integral to its ability to perform 100% local data processing. This combination ensures that the system is not only effective at detecting falls but also maintains the highest standards of privacy. By keeping all data processing on the device using transparent hardware, Lumisafe offers a trustworthy and privacy-friendly safety solution. Lumisafe is set to release in the summer of 2025. You can visit thelumisafe.com to learn more about our privacy-focused technology.