SBIR-STTR Award

The SENSOR FOA clearly identifies a need for people counting in commercial spaces to efficiently allocate HVAC energy, potentially saving 30% in annual energy costs. Scanalytics proposes a materially different, categorically superior floor sensing technology coupled with a device-agnostic platform and real-time processing algorithms to accurately measure occupancy within a space a space such as a room or within a zone of a open-office layout. In essence, the sensor mats will capture a ""video"" of pressure on a floor in a large area and the basestation will use image processing techniques similar to background subtraction and image recognition on these data to identify the number and location of people in a zone. Pressure-sensitive sensor mats have several advantages over other occupancy-counting technologies. Mats do not require people to carry or wear additional equipment such as beacons, and are insensitive to variations in clothing color, skin tone, or room lighting. Mats have a consistent ""view"" of the room and are immune to obstructions, corners, or missing sight-lines which require custom install considerations. By measuring weight rather than motion, the sensor mats will be able to identify people standing still or sitting in office chairs. Other sensors require discrete points of human activity observance like doorways, which limits deployment applicability. The accuracy of a whole-floor sensor provides a better baseline for predictive algorithms to counterbalance thermal inertia. At the conclusion of this project, Scanalytics aims to deliver an environment-agnostic sensing platform.

The SENSOR FOA clearly identifies a need for people counting in commercial spaces to efficiently allocate HVAC energy, potentially saving 30% in annual energy costs. Scanalytics proposes a materially different, categorically superior floor sensing technology coupled with a device-agnostic platform and real-time processing algorithms to accurately measure occupancy within a space a space such as a room or within a zone of a open-office layout. In essence, the sensor mats will capture a ""video"" of pressure on a floor in a large area and the basestation will use image processing techniques similar to background subtraction and image recognition on these data to identify the number and location of people in a zone.