Description

As occupants and their behaviors are responsible for a significantshare of the energy consumption in buildings, it isof important to gather occupancy data. In fact, gatheringoccupancy data is considered as one of the grand challengesin building information modeling. Capitalizing onthe pervasiveness of mobile devices with Bluetooth (BT)functionality, in this paper, we propose an occupant detectionsystem that uses the BT signal to infer occupantpresence. We present the low-cost hardware based on theRaspberry Pi and the open-source software. We apply ourapproach in a real building environment with two experimentalscenarios: 1) Occupancy estimation of a wholebuilding level, and 2) Characterization of occupant types ina shared office. We estimate the ratio r of detected BTdevices to actual number of people to be r ≈ 0.64. Ourresults show robust detection of occupants, as well as successfulcharacterization of occupancy types as stationary,regular occupants, and visitors. Our method can be deployedquickly, and does not require the occupants to installa specific software. Thus, the proposed approach isespecially useful for retrofit solutions.

Citation: ASHRAE/IBPSA-USA Bldg Simulation Conf, Sept 2018

Product Details

Published:

2018

Number of Pages:

8

Units of Measure:

Dual

File Size:

1 file , 1.1 MB

Product Code(s):

D-BSC18-C111