Towards an Interoperable Approach for Modelling and Managing Smart Building Data: The Case of the CESI Smart Building Demonstrator
2. Related Works
3. Research Methods
4. Industry Perspective on BIM Solutions and Their Utilization for Building Energy Management
4.1. BIM Practices Used by French Building Energy Engineering Companies
- Their involvement in and contribution to construction projects;
- Whether they adopted BIM;
- The stage at which they performed their BIM uses;
- Whether they received an architectural BIM model as a point of departure or they created the model themselves;
- Whether they shared the model between the project participants;
- The added value of BIM for them;
- The barriers of using BIM for their organisation and as a collaborative process on the project;
- The BIM-based technologies used by the company and the reasons for this.
4.2. BIM Solutions for Managing the Building Energy in the Operation Phase in France
- No effective solution currently exists that enables building energy monitoring and management using BIM and smart systems.
- Building data use is restricted by regulations, such as the General Data Protection Regulation (GDPR). This is a challenge for most approaches requiring retrofitting existing buildings with sensors. However, this challenge can be resolved if the building occupants and/or building management systems’ operators consent to data access.
- Sensor manufacturers want to protect the protocols of their technologies, but when using these systems (such as sensors, IoT and actuators) in open BIM models, they need to be represented and modelled. A potential solution would be to standardise the output data from these systems to display them without revealing the way they work.
- The concept of a smart building is not clearly defined and is challenged by unpredictable user behaviour. A conceptual definition of a smart building, based on the interviews and expressed in SysML language, is given in Section 5.1. A smart building would allow for empirically-based prediction of user behaviour patterns but the said behaviour varied too much. Thus, the participants believed that sensor-driven data could help by enabling users to control building energy systems and adjust their behaviour accordingly.
- Open BIM, particularly the IFC format, had some deficiencies regarding the representation and visualisation of smart system data and their management, including those related to sensors and IoT actuators. This was shown in several research projects that propose and present extended IFC schemas . An approach to address this challenge which is at the core aim of this paper is proposed and tested in the following sections.
5. Proposed Smart Building Conceptualisation
5.1. Smart Building System Architecture
- Requirement diagram: enables visualising system requirements, both functional and non-functional. It also describes the inter-relationships between requirements. As shown in Figure 3a, a smart building contains (i) a smart system that will manage the actuations and information exchanges from the physical asset to its digital replica and vice versa, and (ii) manages many trade components such as facades, stairs, ceiling, insulation, partitions, HVAC and electrical and fire safety components. Furthermore, the smart system of a smart building requires a set of sensor and actuator components, as well as a decision-making engine to manage the building energy consumption in view of the data taken from sensors and energy simulation.
- Block definition diagram: Aims to specify system static structures that will be used for objects. It represents system components and their contents, interfaces and relationships. Figure 3b shows a smart building as being dependent on the exterior environment (meteorological data, etc.) and using energy consumption and user behavior data for managing building energy. User behavior is impacted by comfort, which, in turn, depends on energy settings that are tuned and monitored by the smart building.
- Sequence diagram: A dynamic behavioral diagram that represents interactions between system objects and blocks via sequences of exchanged information. In Figure 3c, the exterior environment affects user behavior, which will, in turn, act upon trade components, such as light, heating, air conditioning and windows. Data is captured by sensors and processed by the smart system, which informs monitoring actions that can be triggered and performed (if necessary) by actuators on trade components to control the building energy consumption and provide comfortable indoor conditions for users. This may affect users’ behavior again and recursively restart the same process until the desired state is reached.
- Use case diagram: Shows the system functions at a macro level by providing a high-level representation of the system and its top-level requirements from a non-technical perspective. It represents interactions between the system’s main functions and its external users. Figure 3d shows two building uses considered in this study, which were (i) controlling and optimising energy consumption through the smart system and its components, and (ii) providing indoor comfort for users by acting on trade components.
- Internal block diagram: Shows the internal structure of one of the blocks that make up the system. Figure 3e is a zoom-in showing the encapsulated structural contents of the smart building block.
5.2. Modelling Interoperable Information in Smart Buildings
5.2.1. Evaluation of the Approaches for Modelling and Managing Smart Building Information
5.2.2. First Prototype—Using ‘Proxy Elements’
5.2.3. Second Prototype—Using ‘Object Types’
5.2.4. Third Prototype—Using ‘Property Sets’
5.2.5. Fourth Prototype—Visual Programming
5.2.6. Fifth Prototype—Extension of IFC Schema
5.3. Comparing M2SBI Approaches
- Simplicity: The effort involved in developing and using the solution including time and skills.
- Accessibility: Access to the development and solution application tools.
- Completeness: The amount of required data that is exportable using IFCs.
- Readability: Viewer readability of IFC model generated.
- Reproducibility: Ability to reproduce this solution on different buildings properties and in different applications than sensor viewing.
5.4. Visualisation of Building Energy Consumption in BIM
6. Case Study—CESI’s Smart Building
6.1. Smart Building Modelling
6.2. BIM Modelling of Smart Buildings for Building Operations
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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|A||SME||Engineering and maintenance company|
|D||Large||Building product manufacturer|
|E||SME||Data engineering consultancy|
|G||VSE||Building product manufacturer|
|I||VSE||Building product manufacturer|
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Doukari, O.; Seck, B.; Greenwood, D.; Feng, H.; Kassem, M. Towards an Interoperable Approach for Modelling and Managing Smart Building Data: The Case of the CESI Smart Building Demonstrator. Buildings 2022, 12, 362. https://doi.org/10.3390/buildings12030362
Doukari O, Seck B, Greenwood D, Feng H, Kassem M. Towards an Interoperable Approach for Modelling and Managing Smart Building Data: The Case of the CESI Smart Building Demonstrator. Buildings. 2022; 12(3):362. https://doi.org/10.3390/buildings12030362Chicago/Turabian Style
Doukari, Omar, Boubacar Seck, David Greenwood, Haibo Feng, and Mohamad Kassem. 2022. "Towards an Interoperable Approach for Modelling and Managing Smart Building Data: The Case of the CESI Smart Building Demonstrator" Buildings 12, no. 3: 362. https://doi.org/10.3390/buildings12030362