TY - GEN
T1 - DEMSA
T2 - 1st International Workshop on Middleware for Digital Twin, Midd4DT 2023
AU - Ma, Jun
AU - Bouloukakis, Georgios
AU - Kattepur, Ajay
AU - Yus, Roberto
AU - Conan, Denis
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/12/11
Y1 - 2023/12/11
N2 - Heating, Ventilation, and Air Conditioning (HVAC) systems account for a significant portion of energy consumption within buildings. In order to balance the effect of thermal comfort vis-a-vis energy savings, HVAC control strategies have been proposed. However, the strategies are static and do not take into account dynamic changes of consumers, hence creating sub-optimal outcomes. This paper proposes DEMSA, a Digital Twin (DT)-enabled middleware for the self-adaptation of smart buildings. The DEMSA middleware interconnects and coordinates intelligent data exchange between the building edge server, digital twin and Artificial Intelligence (AI) planning nodes in order to invoke appropriate strategies. Moreover, DEMSA is paired with a self-adaptive mechanism that can detect the anomaly of generated planning and adaptively modify it. This process ensures balancing building energy consumption and thermal comfort requirements, without human intervention. The DEMSA middleware is described over a real smart space scenario.
AB - Heating, Ventilation, and Air Conditioning (HVAC) systems account for a significant portion of energy consumption within buildings. In order to balance the effect of thermal comfort vis-a-vis energy savings, HVAC control strategies have been proposed. However, the strategies are static and do not take into account dynamic changes of consumers, hence creating sub-optimal outcomes. This paper proposes DEMSA, a Digital Twin (DT)-enabled middleware for the self-adaptation of smart buildings. The DEMSA middleware interconnects and coordinates intelligent data exchange between the building edge server, digital twin and Artificial Intelligence (AI) planning nodes in order to invoke appropriate strategies. Moreover, DEMSA is paired with a self-adaptive mechanism that can detect the anomaly of generated planning and adaptively modify it. This process ensures balancing building energy consumption and thermal comfort requirements, without human intervention. The DEMSA middleware is described over a real smart space scenario.
KW - digital twin
KW - middleware
KW - self-adaptive systems
U2 - 10.1145/3631319.3632303
DO - 10.1145/3631319.3632303
M3 - Conference contribution
AN - SCOPUS:85181826017
T3 - Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023
SP - 1
EP - 6
BT - Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of
PB - Association for Computing Machinery, Inc
Y2 - 11 December 2023 through 15 December 2023
ER -
