Join us for a discussion on measuring room-level occupancy using temperature and CO2 data to better control building operations.
buildsense.io (http://www.buildsense.io), a startup in Urban-X (https://urban-x.com/)’s cohort 2, is developing machine learning software that analyzes data from building HVAC automation systems already installed in office buildings to measure occupancy in any room, in real-time. No sensors to install means 10x lower costs to deploy than the next cheapest occupancy measurement solution. Understanding how many people are in a room in real-time enables responsive ventilation to improve indoor air quality for occupants and drive energy savings between 10% and 20%. Designers, property managers and owners get a high resolution view of how spaces are being used over time, without compromising occupant privacy. We will talk about some of the challenges inherent in parsing human presence from these existing environment sensors and hope to engage in an interactive discussion.
Bio: Gabriel Peschiera has been working with buildings for the past seven years, first as a consultant focused on energy efficiency retrofits and operational improvements, then as Director of Energy Engineering for Ecorithm where he worked on algorithms to turn HVAC data into actionable insights to make buildings more comfortable for occupants and more energy efficient. Gabriel is a licensed Professional Mechanical Engineer, and holds a B.A. in Architecture as well as a B.S. and M.S. in Civil Engineering from Columbia University, where he led research on energy use behavior in buildings.