RoshaniVijayan/gesture-control-interface

This is an educational/demo project built on commodity hardware (Nicla Vision) and a platform (Edge Impulse). With zero stars, forks, or activity velocity, it has no user adoption or community. The approach—fusing IMU and ToF for gesture control—is a standard sensor fusion pattern, and Edge Impulse handles the heavy lifting of model training. The project is tightly coupled to specific hardware (Nicla Vision) and Edge Impulse's proprietary tools, making it difficult to generalize or extend. No novel ML architecture, no novel sensor fusion algorithm—just a straightforward application of existing tools. Platform risk is HIGH because both Microsoft (Windows Gestures, Kinect legacy), Apple (gestures on Mac), and major IoT platforms (Arduino, STMicroelectronics ecosystem) have far greater resources to build gesture control into their OS/hardware stacks. Market consolidation risk is MEDIUM because accessibility/gesture control startups (e.g., Control Labs acquired by Facebook) and established HCI firms could trivially clone this with better hardware integration and software polish. The 95-day age with zero engagement signals this is likely a portfolio or hackathon project with no commercial intent or sustained development. Displacement horizon is 1-2 years because platforms will formalize gesture APIs as edge devices proliferate; by then, this hardcoded Nicla implementation becomes obsolete.