Hotspot Enabled Building Occupancy Sensor

Default ARPA-E Project Image

Boston, Massachusetts
Project Term:
07/16/2018 - 01/15/2021

Technology Description:

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. The developed algorithms will distinguish between humans and pets, sense presence even when occupants are stationary for extended periods of time, and possess the flexibility to adapt to activities of daily living such as furniture being moved or opening doors. While their sensor hardware components use so-called “Wi-Fi protocols” to wirelessly probe an environment, they do not require nor utilize any internet access, Wi-Fi or otherwise. If successful, the system could offer cost-effective occupancy sensing to homes with and without internet service or broadband access.

Potential Impact:

If successful, SENSOR projects will dramatically reduce the amount of energy needed to effectively heat, cool, and ventilate buildings without sacrificing occupant comfort.


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.


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.


Buildings will require less energy to operate, reducing heating, cooling, and ventilation costs for businesses and families. In addition, better controlled ventilation may lead to improved indoor air quality (ensured by an accurate occupant count, and validated via widespread CO2 detection) may lead to improved worker productivity and academic performance.


ARPA-E Program Director:
Dr. Marina Sofos
Project Contact:
Eric Giler
Press and General Inquiries Email:
Project Contact Email:


Oak Ridge National Laboratory
Carnegie Mellon University

Related Projects

Release Date: