Artificial Intelligence in Facility Management
Future and Potential
Artificial Intelligence (AI) is considered a key technology of the future and is already being applied in areas such as autonomous driving, medical technology, and workplace automation. In facility management, automated systems are increasingly being utilized, although self-learning AI remains the exception. The use of deep learning appears particularly beneficial in public buildings with high visitor frequency. Networked AI solutions contribute to ensuring the safety of people and buildings while optimizing workflows.
Using data from surveillance cameras and IP-based video management systems, such as those offered by Milestone Systems, AI-powered systems can monitor processes and ensure smooth operations. Many modern buildings are already automated: heating and cooling systems adjust based on usage or time of day, and sunshades retract automatically in strong winds—simple “if-then” rules simplify operations.
However, AI solutions go far beyond mere automation. They analyze large datasets, primarily collected by cameras. Deep learning systems learn from experience, recognize patterns, and can make predictions. Such a system can identify abnormal behavior, such as unusual movements of people or vehicles. It then reports potential security risks to surveillance personnel, who can make decisions based on this information.
Artificial Intelligence in Facility Management: Future and Potential
Another useful application is the targeted search of video footage for specific events. Filters allow relevant data to be quickly located and analyzed, enabling the identification of people or vehicles in the shortest possible time. In large building complexes such as train stations or shopping centers, AI systems significantly ease operational tasks.
Advances in graphics processing unit (GPU) technology have enabled the faster processing and analysis of the massive data generated by cameras. As a result, AI systems can detect deviations from normal movement patterns earlier and make precise predictions. Face recognition and reliable license plate recognition (LPR) are already used in many buildings to grant access only to authorized individuals.
AI also holds great potential in infrastructural facility management. Intelligent building technology can adapt to the individual needs of users, such as regulating lighting and temperature in workplaces or assisting with parking. For designated parking spaces, AI can automatically activate the elevator as soon as the car is parked.
AI also proves to be valuable in monitoring building functions. Automated processes, such as fire protection measures or the management of emergency exits, can be intelligently networked. For example, if the AI detects people suddenly moving toward an exit while a fire alarm is triggered, it can automatically activate the emergency plan. However, if only a smoke detector is activated without any indication of danger from people or camera footage, the system might suspect a false alarm. Despite these advancements, the ultimate decision-making authority remains with humans.
While countries like Dubai and China already extensively use AI in facility management, Germany lags behind due to strict data protection regulations such as the GDPR. There is room for improvement, particularly among small and medium-sized enterprises. It is time to establish the framework for deploying AI in facility management in Germany to enhance the safety of people and buildings.
