A lot of things are “smart” these days—but we rarely think about what the term actually means. “Smart” stands for “specific, measurable, achievable, relevant and time-bound” and the word is used in a variety of contexts, from smartphones and smart homes to smart buildings and smart cities. But what makes a building smart? What technologies and solutions are behind it? What goals can it achieve? And how will this area evolve in the future?
In contrast to the smart home, the term smart building refers to commercial and/or purpose-built properties (such as hospitals or airports) in which the individual components of the building technology are networked and exchange data so that the respective systems can be automatically controlled in an optimal manner. These are intelligent, sustainable buildings that are connected to their ecological, economic and technological environment, offering a high level of user comfort and making a positive contribution to environmental and, in particular, climate protection. At the same time, the aim is to increase user convenience, efficiency and cost-effectiveness.
To make a building truly smart, many very different areas and functions need to be captured, controlled and connected. Connecting the physical and virtual worlds requires the Internet of Things (IoT) and a digital twin of the building.
IoT is the term used to describe the network of physical objects (things) equipped with sensors, software and other technologies to send and receive data to and from other things and systems and make it available throughout the network so that physical and virtual objects can work together. The goal is for heating or ventilation, for example, to automatically “adapt” to the situation—for example, summer or winter day, one person or many people in a room at the same time, temporary or permanent use. This requires sensors to collect environmental
information, a computer system to evaluate the data and actuators—drive elements that convert electrical signals and electricity into mechanical motion or light—to implement the control commands and, for example, open the windows or adjust the lighting to the time of day or whether a room is being used or not.
A digital twin is needed to automatically adapt to the situation and continuously improve the functionality of each element. A digital twin is a computer model that not only represents the building itself, but also the building services equipment and all of the building's functions and processes, making them controllable. It can be used to link data from individual components. In addition, the digital twin provides not only data on the current situation, but also access to data from the past, thus offering more knowledge about the building and its operation and more transparency. This makes it easier to optimize the use of resources and implement new services.
Building automation—the automatic control, regulation and monitoring of building functions such as heating, air conditioning and ventilation, lighting or shading, as well as the recording of operating data in a building or building complex—is a prerequisite for a smart building. The term encompasses all the equipment involved, including the software. Building automation also includes management functions such as performance analysis, energy management and information.
Security solutions such as hazard detection systems (fire, intrusion, assault), access control systems and surveillance systems are not part of building automation, but can be linked to it. Automated solutions are required here as well. For example, in the event of a fire, it is not only important to warn and evacuate people as quickly as possible, but also to isolate and extinguish the source of the fire. It is equally important that the associated components, such as fire detectors, function reliably. Again, data can be used to monitor and manage system performance.
Biometric access systems or access control, can also protect against unauthorized entry while greatly simplifying the administration of access authorizations.
Building management has been digitalized for some time, enabling efficient control and management of functions and processes. Artificial intelligence (AI) is expected to further increase transparency and efficiency in smart buildings. The focus is on AI’s ability to identify long-term trends and make quick decisions in complex situations. Data collected from building automation and connected systems serve as the basis for AI to learn how building systems are controlled. Based on this knowledge, AI can make connections transparent and perform learned follow-up actions.
Smart buildings offer greater sustainability, convenience for the user, security and maintenance efficiency.
Smart buildings enable effective energy management to save energy, as well as other resources such as water. With approximately 35 % of energy consumption and 30 % of CO2 emissions caused by the operation of buildings, there is significant potential for savings that can be realized in smart buildings.
While reducing energy and resource consumption, smart buildings can significantly improve occupant comfort. Features range from customized heating, ventilation, air conditioning and cooling technology for a consistently comfortable indoor environment, to automatic control of lighting and shading when the sun is strong, to automatic access and enhanced personal security in the building.
Another factor that contributes to user comfort is the ability to detect and quickly repair potential equipment failures. Smart buildings not only enable greater energy efficiency, but also more efficient building management.
What is also essential for smart buildings is a high level of cybersecurity. With smart building components connected to the internet, hackers have many opportunities to infiltrate a building’s IT system, manipulate data and block building functions. It is important not only to take appropriate technical precautions, but also to make people aware of the dangers of inadvertently becoming a “gateway.”
Today, there is no new commercial or purpose-built building that is not “smart.” IoT and digital twins are now state of the art in new buildings, which means that all the possibilities of a smart building are already being used and the digital twin is already being created during the construction of the building. In contrast, it is more difficult to transform
older, existing buildings into smart buildings, although this transformation is a pressing issue not only from a sustainability and climate change perspective, but also in terms of maintaining and increasing the value of the property.
Even in existing buildings, there are often technologies, software, systems and sensors for building, lighting, energy and security management. The data from these devices can be used to create a digital twin. The difficulty, however, is that these technologies and systems are often incompatible and cannot communicate with each other. This calls for solutions that can integrate these different communication standards.
Data about the building itself, such as information about the floors, rooms and how they are used or consumption data, is almost always available. This data can also be integrated and used to create a digital twin.
The technical equipment often needs to be “upgraded” as well. However, it is often difficult to run additional cables at a later date. This challenge can be overcome by connecting sensors and actuators wirelessly.
Basically, it is also possible to transform existing buildings into smart buildings. The costs are around EUR 100 per square meter and are the pure additional investments for extra building technology features, IoT sensors and a smart building software platform.
While the systems and technologies used in smart buildings should be as easy to use and understand as possible, they still require well-trained professionals. Advanced and specialized training is critical in the face of accelerating technological development and, more recently, the increasing use of AI. But there is also a need to foster cross-disciplinary skills—skills that bridge the technical and commercial realms—and the development of so-called soft skills, such as adaptive thinking and problem-solving skills.
Use cases are scenarios of how software is used, combining possible scenarios that may arise when a user tries to achieve a specific goal with the help of the system in question. The purpose of any software is to create value for the customer, and the same is true for software in smart buildings.
After all, smart buildings are not just office buildings, but also logistics facilities, manufacturing plants, shopping malls and other purpose-built structures. It is not just about “smart building technology.” Users expect the software to help them optimize their work processes. Therefore, the most important use cases should be defined at the outset and the goals should be identified. Use cases do just that. They provide an overall picture of the purpose of the software and help to design it accordingly.
The advantage of these use cases is that they are relatively easy to create, document the different actors and applications and show the relationships between them. They also serve as a guide to the requirements placed on the system.
Without digitalization, the development of smart buildings would not have been possible. Digital technology was initially used primarily in building services, but today the goal is holistic building management. The use of artificial intelligence is expected to further automate and optimize many processes, especially in the area of energy conservation. This is because the use of AI makes it possible to create accurate predictive models for energy demand and consumption, enabling proactive control of facilities and resources. And in the longer term, AI can lead to autonomous self-regulation of building systems.
In general, the integration of AI technologies into real estate processes will lead to an increase in ecological, economic and social sustainability. However, there are also risks associated with the use of AI, such as ensuring data sovereignty and protection against manipulation.