Computational Occupancy Sensing System (COSSY)

Heating, ventilation, and air conditioning (HVAC) consume a significant portion of the energy used in buildings. Much of this energy is wasted when buildings are occupied well below their maximum capacity. Traditional PIR (passive infrared) sensors, that detect movement, cannot estimate the number of people in a room. While COsensors can provide a proxy measurement of occupancy level (inferred from COconcentration), their response to changes in occupancy is very slow due to air mixing. A new type of sensor system is needed to enable advanced HVAC control. Deployed in commercial buildings, such sensor systems have the potential for a significant reduction in energy consumption and the associated reduction of COemissions.

The Computational Occupancy Sensing SYstem (COSSY) estimates the number of people and monitors how this number changes over time. The system is designed to deliver robust performance by combining data from thermal door sensors and overhead fisheye cameras. Data streams from the sensors and cameras undergo advanced processing to jointly provide an accurate occupancy estimate. All the processing is performed locally within a building’s infrastructure (no processing in the cloud) to mitigate security concerns.  The system features a modular design to accommodate various room sizes and geometries.


The project is currently in the final stages of development. COSSY has undergone extensive in-house testing at Boston University and third-party testing at Michigan State University. For a detailed description of COSSY research, please follow the links below:

This project is expected to help reduce the amount of energy (by up to 30%) needed to effectively heat, cool, and ventilate commercial buildings without sacrificing occupant comfort or privacy, but also has potential for other applications.

  • Economy: Buildings will require less energy to operate, reducing HVAC costs for businesses. In addition, better controlled ventilation may lead to improved indoor air quality and increased worker productivity. Also, learning occupancy patterns over time, COSSY can help optimize space usage in office buildings, commercial spaces, etc. by means of the so-called spatial analytics.
  • Security and Safety: Lower electricity consumption by buildings eases strain on the grid, helping to improve resilience and reduce demand during peak hours, when the threat of blackouts is greatest. Also, knowing the number and location of people in a building is key for emergency response in fire, chemical-hazard, actives-shooter, etc. scenarios.
  • Environment: Using significantly less energy could help reduce emissions attributed to power generation. In addition, improved interior air quality could help prevent negative effects on human health.