DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces

Jun Ma; Georgios Bouloukakis; Ajay Kattepur; Roberto Yus; Denis Conan

doi:10.1145/3631319.3632303

DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces

Jun Ma
, Georgios Bouloukakis
, Ajay Kattepur
, Roberto Yus
, Denis Conan

Telecom Sudparis
Ericsson Research
Biochemical and Environmental Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of
Subtitle of host publication	MIDDLEWARE 2023
Publisher	Association for Computing Machinery, Inc
Pages	1-6
Number of pages	6
ISBN (Electronic)	9798400704611
DOIs	https://doi.org/10.1145/3631319.3632303
Publication status	Published - 11 Dec 2023
Event	1st International Workshop on Middleware for Digital Twin, Midd4DT 2023 - Bologna, Italy Duration: 11 Dec 2023 → 15 Dec 2023

Publication series

Name	Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023

Conference

Conference	1st International Workshop on Middleware for Digital Twin, Midd4DT 2023
Country/Territory	Italy
City	Bologna
Period	11/12/23 → 15/12/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

digital twin
middleware
self-adaptive systems

Access to Document

10.1145/3631319.3632303

Cite this

Ma, J., Bouloukakis, G., Kattepur, A., Yus, R., & Conan, D. (2023). DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces. In Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023 (pp. 1-6). (Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023). Association for Computing Machinery, Inc. https://doi.org/10.1145/3631319.3632303

Ma, Jun ; Bouloukakis, Georgios ; Kattepur, Ajay et al. / DEMSA : a DT-enabled Middleware for Self-adaptive Smart Spaces. Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023. Association for Computing Machinery, Inc, 2023. pp. 1-6 (Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023).

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title = "DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces",

abstract = "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.",

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author = "Jun Ma and Georgios Bouloukakis and Ajay Kattepur and Roberto Yus and Denis Conan",

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Ma, J, Bouloukakis, G, Kattepur, A, Yus, R & Conan, D 2023, DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces. in Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023. Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023, Association for Computing Machinery, Inc, pp. 1-6, 1st International Workshop on Middleware for Digital Twin, Midd4DT 2023, Bologna, Italy, 11/12/23. https://doi.org/10.1145/3631319.3632303

DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces. / Ma, Jun; Bouloukakis, Georgios; Kattepur, Ajay et al.
Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023. Association for Computing Machinery, Inc, 2023. p. 1-6 (Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Conan, Denis

PY - 2023/12/11

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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.

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Ma J, Bouloukakis G, Kattepur A, Yus R, Conan D. DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces. In Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023. Association for Computing Machinery, Inc. 2023. p. 1-6. (Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023). doi: 10.1145/3631319.3632303

DEMSA: a DT-enabled Middleware for Self-adaptive Smart Spaces

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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