Abstract

A Bayesian method for determining occupancy in a buildings using motion and presence detectors. This was done by gathering data from different locations and then analyzing the data to determine occupancy within a certain location. The data was collected from a set of motion detectors and then compared against a presence detector to verify the results of the motion events. These motion events were then used to build the conditional tables to generate the belief from the Bayesian Network. The results were then again compared with the presence detector, along with a comparison between a clean data set and a data set with errors to view the change in the belief of the network. The preliminary results demonstrate that the Bayesian theory held true within the beliefs and that with errors, the beliefs maintained their accuracy. This is an ongoing research project in building environments.

Presenters

Avery Schwer
Professor, Architectural Engineering and Construction, University of Nebraska - Lincoln, Nebraska, United States

Donald Levi Tryon
University of Nebraska, Nebraska, United States

Dale Tiller
University of Nebraska

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

Constructing the Environment

KEYWORDS

BUILDING ENVIRONMENTS, OCCUPANCY DETECTION, BAYESIAN METHOD, HIGH PERFORMANCE BUILDINGS

Digital Media

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