With the advent of a mobile workforce and space sharing initiatives, it has become increasingly difficult to plan occupancy and estimate accommodation rates and usage (Guo et al., 2010). The introduction of IoT and Big Data Analytics can alleviate this problem by a comprehensive approach with data-driven solutions to monitor the changing occupancy landscape and provide efficiencies in the process. (Breur, 2015).

In partnership with Embedded Sense, Inc. (ESI), Humber College researchers have successfully built a dashboard and IoT sensor interface, creating a more granular view of the sensor data being collected, with the ability to create a time-based random forest model for predictive capability on occupancy of areas.

Learn more about this impactful project in the Applied Research and Innovation article here.