A Context-aware Architecture for Energy Saving in Smart Classroom Environments
Prabesh Paudel, Sang-Kyoon Kim, Soonyoung Park, Kyoung-Ho Choi · 2019
In this paper, we present a novel context-aware architecture for a classroom environment, recognizing student activities and saving energy. In contrast to previous models which are mainly focused on either video or image, various sensor data such as temperature, humidity, and luminance are combined with a video sequence in the proposed context-aware architecture. More specifically, student activities are classified using the convolutional 3D network (C3D) model and classroom temperature and humidity are predicted using a long short term memory (LSTM) network. Then, the outputs of the C3D model and LSTM network are combined and fed into fully connected layers to produce control parameters such as turn on/off air conditioners/heaters/dehumidifiers. Experimental results show that the proposed context-aware framework can be used for energy saving in classroom environments.