Bijan Raahemi Teams Up With SensorSuite in New Project Funded by NSERC

Professor Bijan Raahemi leads a data analysis project in collaboration with SensorSuite using a grant from the Natural Sciences and Engineering Research Council (NSERC). A post-doctoral fellow and two Ph.D students are working with Dr. Raahemi in the Knowledge Discovery and Data mining (KDD) research laboratory at the Telfer School.

Project Description

A Toronto-based company, SensorSuite produces wireless sensors and controllers for the HVAC industry with solutions that capture, process and deliver real-time information to property managers and building owners. The KDD lab will develop a customized solution for managing large volumes of data that cannot be processed using traditional techniques. Data from SensorSuite’s sensors positioned in different locations will be captured and analyzed using big data analytics for pattern recognition, prediction, and anomaly detection. The ultimate goal of the project is to achieve fewer inefficiencies, a reduction in operational risks, and cost savings. 

More about the KDD lab

Bijan Raahemi established the Knowledge Discovery and Data mining (KDD) lab at the University of Ottawa with grants from the Canada Foundation for Innovation (CFI). Supported by several research grants, including two NSERC discovery grants, the research in the KDD lab focuses on data analytics, information systems, and their applications in engineering and business. 

The research in the KDD lab undertaken by Post-Doctoral Fellows, Ph.D and M.Sc. students focuses on big data analytics, data summarization, and stream data mining. It includes the recent industry-funded project, “Brain-based Biomarkers for Depression Diagnoses” supported by IBM and Royal Ottawa Hospital. This work focused on development of predictive and descriptive models to diagnose depressed individuals based on the EEG monitoring of brain activities in three frequency bands. Data were analyzed through the use of various analytical methods including neural networks, decision trees, and k-means clustering. Undertaken with the cooperation of the Royal Ottawa Hospital, the project identified significant biomarkers in the EEG signals to support clinical decision making.