Slick Sheet: Project
The University of Colorado, Boulder (CU-Boulder) will develop an integrated occupancy detection system based on a radio-frequency identification (RFID) sensor network combined with privacy-preserving microphones and low-resolution cameras to detect human presence. The system may also analyze electrical noise on power lines throughout a residential home to infer occupancy in different areas.

Slick Sheet: Project
Duke University will develop a residential sensor system that uses a dynamic meta-surface radar antenna design to determine occupancy in residential buildings. Traditional line-of-sight movement sensors suffer from high error rates. To increase accuracy, the Duke team will develop a sensor that monitors electromagnetic waveforms that are scattered both directly and indirectly off a person, eliminating the need for a direct line-of-sight between the sensor and the person. The sensor hardware continuously generates distinct microwave patterns to probe all corners of the house.

Slick Sheet: Project
Endeveo will develop an occupancy sensor system to accurately determine the presence of occupants in residential buildings and enable temperature setbacks to provide energy savings of 30% per year. Their technique uses standard Wi-Fi-equipped devices, such as routers, to monitor an environment using the wireless channel state information (CSI) collected by these devices and occupancy-centric machine learning algorithms to determine occupancy from changes in CSI.

Slick Sheet: Project
Scanalytics will develop pressure-sensitive flooring underlayers capable of sensing large areas of commercial buildings with a high-resolution and fast response time. This technology will enable the precise counting of people in commercial environments like stores, offices, and convention centers. The floor sensors will consist of a material which changes electrical resistance when compressed.

Slick Sheet: Project
Rensselaer Polytechnic Institute (RPI) will develop a method for counting occupants in a commercial space using time-of-flight (TOF) sensors, which measure the distance from objects using the speed of light to create a 3D map of human positions. This TOF system could be installed in the ceiling or built into lighting fixtures for easy deployment. Several sensors distributed across a space will enable precise mapping, while preserving privacy by using low-resolution images.

Slick Sheet: Project
N5 Sensors and its partners will develop and test a novel semiconductor-based CO2 sensor technology that can be placed on a single microchip. CO2 concentration data can help enable the use of variable speed ventilation fans in commercial buildings. CO2 sensing may also improve the comfort and productivity of people in commercial buildings, including academic spaces. N5 Sensor's solution will determine CO2 concentrations through absorption of CO2 when the concentrations are high in the environment, and desorption of CO2 when the concentrations are low.

Slick Sheet: Project
Matrix Sensors and its partners will develop a low-cost CO2 sensor module that can be used to enable better control of ventilation in commercial buildings. Matrix Sensor's module uses a solid-state architecture that leverages scalable semiconductor manufacturing processes. Key to this architecture is a suitable sensor material that can selectively adsorb CO2, release the molecule when the concentration decreases, and complete this process quickly to enable real-time sensing. The team's design will use a new class of porous materials known as metal-organic frameworks (MOFs).

Slick Sheet: Project
United Technologies Research Center (UTRC) will develop a low-cost occupancy solution that combines radar sensing technology with an infrared focal plane array (IR-FPA) to determine occupancy in buildings. The solution will also be deployed as a radar-only residential sensor for true human presence sensing. The radar will detect respiration or heartbeat of non-moving occupants by measuring the radar signal reflections caused by chest movement.

Slick Sheet: Project
Texas A&M University will develop an advanced, low-cost occupancy detection solution for residential homes. Their system, called SLEEPIR, is based on pyroelectric infrared sensors (PIR) a popular choice for occupancy detection and activity tracking due to their low cost, low energy consumption, large detection range, and wide field of view. However, traditional PIR sensors can only detect individuals in motion. The team proposes a next-generation PIR sensor that is able to detect non-moving heat sources and provide quantitative information on movement.

Slick Sheet: Project
Purdue University will develop a new class of small-scale sensing systems that use mass and electrochemical sensors to detect the presence of CO2. CO2 concentration is a data point that can help enable the use of variable speed ventilation fans in commercial buildings, thus saving a significant amount of energy. There is also a pressing need for enhanced CO2 sensing to improve the comfort and productivity of people in commercial buildings, including academic spaces.