IOT device code translators using LSTM networks
Kelly Cashion, Satish Ravindran, Nilesh Powar, Joshua Gold · 2017
Currently, the Internet of Things (IOT) platform used by large buildings to manage the indoor climate uses different controllers and sensors from multiple manufacturers. Communication between these devices requires a human in the loop to translate each devices data to to be compatible with a common integration engine and storage historian. The subject matter expert needs to decipher the non-standard naming convention used for each device and manually translate thousands of codes each time a new device has to be integrated. To aid the human translator, we propose a technique to implement a smart translator using Deep Neural Networks (DNN) by automatically assigning any registers with recognized data patterns to standardized labels.