S.M.A.R.T Sensor

Scanning MeAn Radiant Temperature Sensor

More information about the SMART sensor is available through our startup: Hearth Labs

Knowing people and their thermal comfort.

While it accounts for ½ of human comfort, radiant temperature is rarely measured, or controlled, in existing building systems. This prevents us from heating and cooling buildings in a truly effective way.

SMART Sensors collects geometry alongside thermal data, correlating the two with an algorithm that allows us to characterize the occupants’ location and their comfort levels at all locations in a room.

Heat People NOT Spaces.

Save Money. Save Energy.

Moving from heating spaces to heating people could lower energy input by up to 50%.[1]

Data gathered on a SMART Sensor can provide accurate head-counts on a per-room basis. This previously unavailable data will allow buildings to selectively condition spaces only when occupants are present.

In pilot studies where occupant tracking technologies were used, the amount of time spent heating empty rooms dropped by a factor of 12[2], from a conventionally programmable thermostat. In addition, high-resolution occupancy data is a valuable asset to building owners, operators, and designers.

Personal. Comfort.

Pilot research suggests that measuring occupant skin temperature can accurately characterize their individual comfort level. By integrating with location-specific heating, SMART-enabled buildings could accurately assess and cater to individual people, without the need of any thermostat or system programming.

Powerful Diagnostics.

SMART Sensor can send real-time data to your mobile devices.

Drastically increased resolution of temperature readings alongside geometry measurements collected by the SMART Sensor allows more insight to the radiant environment to be used by not only building operations staff as much as consumers,  while dropping costs by 80%.

How it works.

The SMART sensor collects angular information alongside readings a Lidar-lite rangefinder and Melexis temperature sensor through sensor window with 2-axis movement.

A diagram of the completed sensor showing the two axes of rotation.

The sensors rotates 360˚ around B axis and 180˚ around A axis to provide a full synopsis of the radiant environment surrounding the location of the sensor. The spherical coordinates can then generated from the angular direction and distances at the point of measurement, essentially allowing a thermal map to be generated(following figure is unwrapped in 2D for better viewing:

Thermal Map of Open-plan research space (Unfoloded)

Patent Pending:

The SMART building sensor and 3D thermal renderer used to quickly  measure surface temperature and distance and then render a 3D thermal model of the surroundings – at a fraction of the cost of thermal imaging products.

New data and processing techniques have been developed for the CHAOS Spherical Motion Average Radiant Temperature (SMART) Sensor in preparation for conference publications. Building off previous work with a rotating infrared temperature sensor, a LIDAR Lite sensor was added to construct a 3D representation of a room.

Below are four videos showing the initial prototype device in operation and the preliminary 3D models output using Matlab

SMART Sensor Operation:

2-D Office, and 2D personACEE_side_2D_2Full_contour
3-D Office Surface Contours, surface reconstruction.

3-D Office Point Cloud, same office as above, in point cloud representation:

Thermoheliodome rendered using the SMART sensor, and driving force for its development as thermal cameras had too small of a field of view to image the novel reflective radiant system properly:


[1]Hoyt, T., Arens, E., & Zhang, H. (2015). Extending air temperature setpoints: Simulated energy savings and design considerations for new and retrofit buildings. Building and Environment, 88, 89-96. doi:10.1016/j.buildenv.2014.09.010

[2]Scott, James, A.j. Bernheim Brush, John Krumm, Brian Meyers, Michael Hazas, Stephen Hodges, and Nicolas Villar. “PreHeat.” Proceedings of the 13th international conference on Ubiquitous computing – UbiComp ’11 (2011): n. pag. Web.

Research team led by Prof Forrest Meggers, faculty jointly appointed in the School of Architecture and the Andlinger Center for Energy and the Environment.