This paper provides a Deep Learning (DL) based design framework for forecasting respiratory behaviors of factory floor workers in a smart factory environment (or Industrial Internet of Things (IIoT)). A continuous 30 min breathing responses were colle...
This paper provides a Deep Learning (DL) based design framework for forecasting respiratory behaviors of factory floor workers in a smart factory environment (or Industrial Internet of Things (IIoT)). A continuous 30 min breathing responses were collected through Ultra-Wide Band (UWB) sensor and then applying Artificial Neural Network (ANN) models to acquire the highest prediction accuracy. Eight ANN models with different input, hidden, and output nodes were compared with the proposed scheme code-named ANN-5. The result shows that the proposed ANN-5 outperformed other algorithms with 87.43% precision.