Collecting Indoor Environmental Sensor Values for Machine Learning Based Smart Building Control

This research presents a solution for collecting indoor environmental sensor values and how the gathered sensor values then could be used for green building certification and in turn also machine learning based smart building control. We have created and implemented a proof of concept system consisting of a sensor collecting device using off the shelf hardware to complement the existing sensor information from buildings, as well as a cloud system for persistently storing this data for later usage. We have measured and evaluated our implemented system for our envisioned scenarios. In which we could observe that our proof-of-concept could scale to handle almost four sensor value updates per second at maximum stress, as well as having a latency for uploading a sensor value from our sensor of about 130 ms. Finally, we present our future and ongoing work based on these results which outlines our work for smart building control, green building certification, and the energy signature of buildings.