Occupancy-Driven Facility Management and Building Performance Analysis

Occupancy-Driven Facility Management and Building Performance Analysis

D. Ioannidis S. Zikos S. Krinidis A. Tryferidis D. Tzovaras S. Likothanassis 

Information Technologies Institute, Centre for Research and Technology Hellas, Greece

Pattern Recognition Laboratory, Computer Engineering and Informatics, University of Patras, Greece

Page: 
1155-1167
|
DOI: 
https://doi.org/10.2495/SDP-V12-N7-1155-1167
Received: 
N/A
| |
Accepted: 
N/A
| | Citation

OPEN ACCESS

Abstract: 

Accurate and automated real-time building monitoring is a challenging task due to the large number of different parameters that are involved. This paper presents several aspects of a building monitoring and control system that has been developed. The system is based on a multi-sensorial network which is able to capture sustainability-related metrics due to the use of heterogeneous sensors such as occupancy detection sensors, environmental sensors, power consumption sensors and actuators. The availability of occupancy information at room or zone level which is achieved via the occupancy sensors, offers the opportunity to extract valuable information about the way the building is utilized. Furthermore, as the occupancy patterns considerably affect the building’s indoor environmental condition and the consumed energy, occupancy estimation turns into a useful tool for the facility manager to analyze and then improve the building’s energy performance and enhance the indoor environmental quality by applying control actions through the actuators. The building information is visualized in the spatio-temporal domain to both the facility manager and the occupants via two different components. The system has been evaluated in real-life conditions at a building which is comprised of different types of spaces. Results showed that useful conclusions are drawn when occupancy information is combined with the other monitored parameters.

Keywords: 

energy conservation, occupancy estimation, sensor network, visualization

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