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The Integration of Wi-Fi Location-Based Services to Optimize Energy Efficient Commercial Building Operations

Technical Report ·
DOI:https://doi.org/10.2172/2331520· OSTI ID:2331520
 [1];  [2];  [3];  [3];  [3];  [4];  [5];  [5];  [6];  [6];  [7];  [7];  [3]
  1. Center for Energy and Environment (CEE), Minneapolis, MN (United States); L Shen Technical Services LLC
  2. Ramboll, Arlington, VA (United States); Center for Energy and Environment (CEE), Minneapolis, MN (United States)
  3. Center for Energy and Environment (CEE), Minneapolis, MN (United States)
  4. Design.Garden, Madison, WI (United States)
  5. Slipstream, Inc., Madison, WI (United States)
  6. HGA Architects and Engineers, Minneapolis, MN (United States)
  7. Leede Research, Minneapolis, MN (United States)
+ Show Author Affiliations

This project investigated and demonstrated the use of Wi-Fi Location-Based Services (LBS) to perform occupancy sensing in commercial buildings. Wi-Fi LBS can be used to detect the presence of Wi-Fi enabled mobile devices and laptops that accompany occupants as they move through the building. These signals can be used to determine occupant presence, head count, and location. When integrated with the building automation system, this emerging technology approach can be used to manage other connected systems such as lighting and HVAC to reduce energy usage in the building and improve occupant comfort. An open source location detection algorithm was developed, which uses data collected from three or more Wi-Fi access points to determine the presence and estimate the location of mobile devices and laptops. Access points can detect Wi-Fi enabled devices even if they are not connected to the existing Wi-Fi network. Building occupancy is determined based on the presence, location, and movement of these devices through the space. From lab and small-scale in-situ testing, the Location Detection Algorithm (LDA) was found to be accurate to within 10 feet and could be further refined by tuning the algorithm for the specific space characteristics such as layout and obstructions (walls, furniture, etc.). An open source method to integrate the occupancy data with existing building automations systems was investigated. The Wi-Fi occupancy sensing approach was then demonstrated and validated at commercial buildings located in Saint Paul, MN; Madison, WI; New York City; and Fort Worth, TX.

Research Organization:
Center for Energy and Environment (CEE), Minneapolis, MN (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
DOE Contract Number:
EE0008684
OSTI ID:
2331520
Report Number(s):
EE0008684; Building; Technologies; Office; (BTO); under; the; Buildings; Energy; Efficiency; Frontiers; &; Innovation; Technologies; (BENEFIT)-2018; DE-FOA-0001825; 1825-1573
Country of Publication:
United States
Language:
English

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Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
AFMS
AHU
Air Handling Unit
Airflow Measuring Station
BAS
BTO
Building Automation System
CBI
Commercial Buildings wi-fi
EBI
Honeywell Enterprise Building Integrator
Wi-Fi location-based services
location analytics
occupancy sensing
occupancy-based building control
real-time locating system