TY - GEN
T1 - Towards a Real-Time Occupant Behavior Monitoring System
T2 - 2024 ASCE International Conference on Computing in Civil Engineering, i3CE 2024
AU - Chung, Jihoon
AU - Shelden, Dennis
AU - Karlicek, Bob
N1 - Publisher Copyright:
© ASCE.
PY - 2024
Y1 - 2024
N2 - Obtaining high-resolution occupancy data is crucial for applications related to occupant behavior and occupant behavior modeling to achieve a significant reduction of unnecessary building energy consumption. Various types of occupancy sensing technologies have been proposed to enhance the occupancy data resolution. However, most of these technologies are rarely integrated with building information to monitor the interaction between occupants and building systems. In this paper, we present a framework for occupant behavior monitoring systems that aims to understand the dynamic interaction between indoor environment, occupant behavior, and building systems by integrating BIM, IoT sensors, and Building Automation System (BAS). As a preliminary study, we have developed a prototype and conducted a pilot test to demonstrate the feasibility of combining IoT sensor data with BAS data based on a BIM model for real-time monitoring of occupant behaviors. This result can be a basis to develop a data acquisition system to provide detailed occupant behavior information for data-driven occupant behavior modeling.
AB - Obtaining high-resolution occupancy data is crucial for applications related to occupant behavior and occupant behavior modeling to achieve a significant reduction of unnecessary building energy consumption. Various types of occupancy sensing technologies have been proposed to enhance the occupancy data resolution. However, most of these technologies are rarely integrated with building information to monitor the interaction between occupants and building systems. In this paper, we present a framework for occupant behavior monitoring systems that aims to understand the dynamic interaction between indoor environment, occupant behavior, and building systems by integrating BIM, IoT sensors, and Building Automation System (BAS). As a preliminary study, we have developed a prototype and conducted a pilot test to demonstrate the feasibility of combining IoT sensor data with BAS data based on a BIM model for real-time monitoring of occupant behaviors. This result can be a basis to develop a data acquisition system to provide detailed occupant behavior information for data-driven occupant behavior modeling.
UR - https://www.scopus.com/pages/publications/105025032821
U2 - 10.1061/9780784486115.113
DO - 10.1061/9780784486115.113
M3 - Conference contribution
AN - SCOPUS:105025032821
T3 - Computing in Civil Engineering 2024: Artificial Intelligence, Automation and Robotics, and Human-Centered Innovations - Selected papers from the ASCE International Conference on Computing in Civil Engineering 2024
SP - 1069
EP - 1078
BT - Computing in Civil Engineering 2024
A2 - Akinci, Burcu
A2 - Berges, Mario
A2 - Jazizadeh, Farrokh
A2 - Menassa, Carol C.
A2 - Yeoh, Justin
PB - American Society of Civil Engineers (ASCE)
Y2 - 28 July 2024 through 31 July 2024
ER -