A smart building approach consists of a combination of facilities, infrastructure and services coordinated to provide a user-centric and usage-centric experience. These intelligent buildings can manage different standards of use, especially in mixed commercial or residential areas.
The most comprehensive standardization approach for smart buildings is the Building Information Modeling (BIM) standard, which has been around as long as the ISO 19650 standard for construction and building services. However, even with these standards, the possibilities for extension are limited because the design of the different infrastructures of the installation is different.
The Data Fabric underpinning smart buildings
A data fabric approach is recommended to integrate the different data flows of a smart building. It is a “system of systems” approach that enables interoperability between asset-based building management and the management services and functions provided by a building management system (BMS). Data streams from various operating systems, including data collection from IoT sensors and unstructured media-related sources, are orchestrated through the building platform. Some of these tools are also classified as Building Asset Management (BAM) systems.
Companies should be wary of different families of build platforms targeting different buildings, markets, and service development. Some platforms focus on building management or construction planning and execution, while others focus on the sustainability aspects of a building or facility.
With this diversity of tools and systems, companies need to define the data capabilities of their platforms. In other words, it is necessary to define the orchestration requirements of the different data flows to manage the buildings organized in an integrated “system of systems” approach rather than a single platform environment.
The management flow between BMS and BAM through the command and control environment supports the provision of contextual, event-based services such as concierge, business services, and health and safety management. A shared data environment orchestrates and manages smart buildings, including internal and external data lakes, data warehouses, and PLM or ERP systems. In many building environments, there are different silos of data in different systems. Companies should develop tools and capabilities within the system to create data naming conventions for standardization and automation, and to develop low-code/no-code workflow management capabilities.
Examples of scalable smart buildings
Let’s look at the use cases of data-driven smart buildings, where building owners and building and facility managers can use data from their existing operating environment. In a fragmented market of platforms and solutions, a common data environment is key to the smart building roadmap, which requires new skills in data analytics and data science. It also helps to develop a data hub structure that matches the systems approach to the system.
Create resilient and sustainable building environments through flexibility in space design based on events that cause congestion at times or overuse of facilities such as elevators, turnstiles, and concession stands.
Improve user and employee experience through location analysis and movement patterns of anonymized people. For example, through application development and user preferences, routes to work, airports, sports facilities, etc. can be customized. Users with special needs can also take advantage of special services such as VIP or concierge. In factories and sensitive places, security measures can protect people and machines. This allows landlords and property managers to reduce the likelihood of tenant changes and increase the size and sustainability of their buildings.
Cost-effectiveness, net zero standards and green spaces promote the sustainability and circular economy aspects of smart buildings. For existing buildings, the infrastructure can pull and orchestrate data from asset management systems to provide real-time controls for resource efficiency, green environments, irrigation, climate control, and building of microgrids. When designing new buildings, digital twins can be used to simulate carbon neutral architecture and sustainability to understand the impact of design criteria, construction and materials throughout the building lifecycle .
IoT sensors control the greening of roofs, the irrigation of vertical gardens for greening and the air conditioning of building walls and installations. Building management systems also support recycling and reuse models, waste-to-energy (WTE), or designing plastic-free environments. New technological approaches such as autonomous drones, robots and vehicles will enable the delivery of goods and products to neighborhoods and to all floors.
Ecosystem for data collection and analysis
It is important to build an ecosystem to integrate different asset management systems for building management. Integrating, operating and managing these platforms requires complex technology, data management and innovation, often acquired through solution providers as part of professional services.
Consolidation will accelerate further, as real estate and business administration CIOs and municipalities often see the concepts of smart buildings, smart neighborhoods and smart industrial parks as catalysts for digitalization for integrated services . This makes it possible to use microgrids to charge electric vehicles or to create new facility management systems with customizable demand portals and reporting points.
Finally, it should be noted that much of process integration requires in-depth data modeling, which requires collaboration between IT and operations departments toward a common goal. This requires interactive enterprise-wide change management as well as a digital foundation for data governance.
*Bettina Tratz-Ryan is Vice President of Research at Gartner, responsible for areas such as Digital Transformation, Smart Enterprise, Smart Cities and Industry 4.0.
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