Sentient buildings
Artificial intelligence is transforming everything, from our homes to the vehicles we drive. But what about buildings? We’re entering a new era where buildings are no longer just functional spaces, but adaptive and intelligent entities. Imagine a building that not only knows what it needs, but learns from its daily use. In this article, we explore self-learning in smart buildings: how it will work, what the impacts will be, and whether your building will soon be ‘googling’ solutions to solve problems on its own.
From a Smart Building to a Learning Building
The idea of a building that ‘learns’ may sound like science fiction, but reality is fast approaching. Self-learning in buildings goes far beyond automation. Instead of just reacting to commands or sensors, a self-learning building uses artificial intelligence (AI) and machine learning to analyse usage patterns, predict needs and adapt autonomously. According to Deloitte, smart buildings can reduce energy consumption by up to 35% by adapting their use based on the occupants’ habits.
Imagine that the building identifies unexpected temperature peaks at the end of the day. Instead of simply switching on the air conditioning, it learns that these peaks only happen on Fridays and adjusts the climate control preventively. This optimised process means less wasted energy and a more effective response.
The Role of Data: The More the Better?
For the building to ‘learn’, it needs data. Lots of data. From the temperature in each room to occupancy levels and energy consumption peaks. Every modern smart building is equipped with thousands of sensors that constantly collect data. It is from this avalanche of data that machine learning systems begin to learn, identify patterns and predict needs.
But how far does the data go? The Harvard Business Review points out that buildings with self-learning systems tend to capture between 50 and 100 per cent more data than traditional systems, but the question of privacy and security is just as relevant. Knowing where people are at all times and what they do with the space can become a double-edged sword. Companies and managers have a responsibility to ensure that all data collected is used ethically and securely. After all, nobody wants to feel that the building knows more about us than we do!
Benefits and Applications of Self-Learning: Fewer Interventions and More Efficiency
The great appeal of a learning building is its ability to drastically reduce the need for human intervention. Instead of technicians making constant manual adjustments, the building is able to adjust settings automatically based on usage and historical patterns. According to Statista, integrating AI into buildings can reduce maintenance costs by up to 30% and improve operational efficiency.
For example, a building that uses machine learning can adjust the lighting in each room based on the presence of natural light, maintaining optimum comfort levels and reducing energy consumption. However, machine learning goes even further: by identifying repetitive faults in specific equipment, the building is able to proactively notify the maintenance team before the problem becomes critical. It’s as if the building itself takes on the role of manager, keeping operations within optimum levels.
Sustainability and Carbon Footprint: Intelligence at the Service of the Environment
Self-learning is not just a technological luxury, but a real response to the growing need for more sustainable buildings. With the European Union setting ambitious targets to reduce the carbon footprint, every building needs to do its bit. Learning buildings are more efficient at managing resources and avoiding waste, directly impacting carbon emissions.
According to the International Energy Agency, intelligent buildings with self-learning systems can reduce CO₂ emissions by up to 40% over their lifetime. Through automatic adjustments and predictions based on usage, lighting, air conditioning and other systems consume only the energy they need, avoiding excesses and ensuring that the building meets environmental efficiency targets.
Could Your Building ‘Google’ Solutions in the Future?
The question raises an important point: how far can self-learning take buildings? There are already algorithms capable of connecting to external data sources to obtain additional information. In theory, there’s nothing to stop buildings from connecting to larger data networks in the future, consulting ‘information’ they don’t already have in order to solve problems internally.
Imagine a building that, when it detects a problem with the HVAC system, automatically searches for specific solutions for the equipment model and even contacts certified technicians, scheduling maintenance. Although still an innovative concept, the idea of buildings that ‘learn’ on their own and search for external data is a promising area.
According to the MIT Technology Review, buildings with self-learning systems will be able to access information on shared AI networks in the next five years, allowing them to ‘learn’ from each other. This exchange of information would transform buildings into an autonomous and resilient ecosystem, where collective knowledge is applied to solve individual problems.
Self-learning in smart buildings isn’t just the future; it’s an ongoing revolution. This transformation represents a unique opportunity to improve efficiency, reduce costs and promote sustainability by transforming the way we interact with physical space. However, with self-learning capabilities and external data integration, we are entering an era where buildings begin to make decisions, anticipating our needs and, who knows, one day even ‘Googling’ solutions.
WiseBuilding® is technically qualified to support any project that includes integrating intelligent controls into your building. Consult-us.
WISEFRAMEWORK is a BACnet B-AWS certified software solution for state-of-the-art integration, control, management and visualisation in building automation systems. Designed to redefine the way buildings are operated through an open platform and seamless harmonisation between building-generated data by supporting multiple protocols including BACnet, Modbus, KNX, OPC-UA and MQTT. Through the use of Haystack technology, the software also empowers the building for the future at the forefront in the integration of the various technical systems.