Low-Power Gesture Recognition Using Convolutional Neural Networks and Ambient Lighting

This paper presents a study focused on developing an efficient signal processing pipeline and identifying suitable machine learning models for real-time gesture recognition using a testbed consisting of an Arduino Nano 33 BLE and three OPT101 photodiodes. Our research aims to address the challenges of limited computational power whilst...

Designing an adaptable and low-cost system for gesture recognition using visible light

This paper describes the design of an adaptable, low-cost, and energy efficient gesture detection system. The system leverages the ambient light available in the environment to perform Visible Light Sensing (VLS) using powerful Convolutional Neural Networks. The focus lies on designing a system that is capable of robust gesture detection in any...