3D Computer vision for online activity detection. Case study: metabolic rate estimation for connected thermostat

The ability to detect human activities in computer vision has gained importance over the years due to its potential in many applications such crime prevention, healthcare, public safety, human-computer/robot interaction, smart homes, videogames, monitoring, etc. A way to achieve those applications is by doing a Human Activity Recognition (HAR) process in which an activity is identified by a series of physical actions that construct one physical activity. The identification requires sensors to obtain the data for processing and classifying it. These kinds of sensors are often found inside a smart home. Therefore, it is proposed to use noninvasive sensors in combination with digital signal processing to develop a platform for detecting human activity. Moreover, a case study is proposed for validating the platform by proposing a strategy to save energy on HVAC systems without affecting the thermal comfort of the occupant

https://orcid.org/0000-0001-7035-5286