Human Presence Detection

Human presence detection aims to accurately and reliably identify the presence of individuals within a given space, often without requiring the person to actively participate. Current research focuses on developing robust and efficient algorithms, employing diverse sensing modalities such as radar, cameras, and WiFi signals, and leveraging machine learning techniques including convolutional neural networks, recurrent neural networks, and Bayesian methods for improved accuracy and real-time performance. These advancements are driving progress in applications ranging from contactless building access control and smart home automation to improved traffic monitoring and enhanced safety features in autonomous vehicles. The field is also actively addressing challenges like privacy concerns, energy efficiency, and the ability to function reliably in complex or cluttered environments.