Occupancy detection in smart home space using interoperable building automation technologies

Abstract

To detect whether people are occupying individual rooms in a smart home, a range of sensors and building automation technologies can be employed. For these technologies to function in tandem and exchange useful data in a smart home environment, they must be interoperable. The article presents a new interoperable solution which combines existing decentralized KNX building automation technology with a KNX/LabVIEW software application gateway using visible light communication to track occupancy in a room. The article also describes a novel KNX/IoT software application gateway which uses an MQTT protocol for interoperability between KNX technology and IBM Watson IoT platform. We conducted an experiment with the originally designed solution to detect occupancy in an office room. We used KNX and BACnet building automation technology to produce an interoperable KNX/BACnet hardware gateway which allowed the application of artificial neural network mathematical methods for CO2 waveform prediction. The best results in detecting occupancy in a room were R = 0.9548 (Levenberg-Marquardt algorithm), R = 0.9872 (Bayesian regularization algorithm), and R = 0.8409 (scaled conjugate gradient algorithm), which correspond to the results obtained by other authors and a minimum system prediction accuracy of 96%.