Simeio: Anomaly Detection for Building Automation System – Year two

Buildings are an important energy consumer and are equipped with hundreds of sensors and control systems. The analysis of such massive data can reveal insights for building owners to optimize the building infrastructure. Currently, usage of such data is limited to traditional control systems, energy commissioning, and maintenance on a regular basis. Real-time monitoring and analysis of data can reveal insights about the performance of the building helping to reduce operating costs, lower utility bills, increase equipment life, improve tenant comfort, retention, and leasing rates; all while lowering carbon emissions. Simeio (A Cloud based software application developed by UCtriX team) is leveraging powerful artificial intelligence (AI) analytics to automatically detect anomalies and faults in the HVAC system and pinpoint any abnormalities or failures in a building. Simeio is a platform used by building owners, building managers, or higher authorities to ensure the sustainability and efficient operation of buildings.

Faculty Supervisor:

Fariborz Haghighat

Student:

Milad Ashouri

Partner:

EnerZam

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

Concordia University