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‘Architecture, we imagine, is permanent,’ wrote Stewart Brand in his 1994 book How Buildings Learn. ‘And so our buildings thwart us. Because they discount time, they misuse time.’
We live, work and engage with the world in buildings, and as we grow and evolve, so too do the buildings around us. They age and bits break off. They get painted, upgraded, enhanced and defaced. Buildings are dynamic, and yet our relationship with them remains strangely fixed. And so, as Brand suggests, they thwart us.
Buildings are dynamic and we must keep up
We’ve been thinking about the dynamism in buildings for many years at IBM. We know that buildings and how we use them is constantly changing- especially when it comes to energy. When the weather changes, patterns of use change. For example, people stay longer in the building in the evening when it’s raining than they do when the sun is shining. Similarly, at different times of year – such as when schools are closed – people come to work earlier.
Buildings are increasingly used for different purposes. It is not uncommon in cities to have buildings with retail, residential and commercial all combined. The interaction of these functions is important to model and understand as we consider how to make each more energy friendly.
Tenants are demanding deeper understanding of building functions
The relationship between the owner and the tenant has often been at arms-length, resulting in a lack of integrated thinking for building performance. Increasingly, however, tenants are demanding access to deeper understanding and control of core building functions. They care about sustainability and how energy friendly the spaces they occupy are.
Tenancies too are becoming shorter. From retail pop-up and seasonal stores, to space sharing and on-demand cubicles, real-estate models are changing. The ability to arbitrage space, to move it around, and to deploy quickly, can offer significant uplift to the building owner, and value to the tenant.
The Internet of Things (IoT) offers significant opportunity with its tiny sensors and cheap computing and cloud designs. It doesn’t just allow us to see into the spaces in buildings. It also allows us to model that dynamism and to understand the processes within which buildings exist. We can visualize the current behavior of the building, model its past ,and predict its future. Using these technologies, we can effect an ongoing design of the building based on how its uses change, and as the seasons come and go.
The value of artificial intelligence in the future of buildings
For owners, tenants, visitors and suppliers, the people who operate within and around buildings learn intuitively how to get the best out of it. At certain times of the day, you learn it’s best to take the stairs. You get to know where the best places are to park. You figure out what settings are right on the thermostat, and whether it’s a better idea to just open the window. As human beings, we are constantly learning within our spaces and our worlds. The promise of artificial intelligence (AI) is that machines can learn too.
The combination of AI with the IoT is where Stewart Brand’s conception of buildings that learn finds expression. It is not necessary for these buildings to thwart us. Our technologies can make them, in some primitive respects, self-aware. It pulls data in from weather feeds and device feeds from HVAC controllers, lighting and security, footfall analyses and elevator loading data. It runs live into a comprehensive model of the building and its functions. The building can then acquire a capacity to make intelligent decisions about how its services are delivered and maintained. Increasingly, our buildings can be aware of what we need, and evolve that understanding.
Introducing IBM IoT Building Insights
IBM IoT Building Insights is now available on the IBM Cloud. The goal of the solution is to ensure that the design of the building doesn’t stop after the builder hands over the keys. It enables the space to continue to grow and evolve – not in an unpredictable or chaotic way – but in a managed and more effective model. Temperature regulation improves; oppressive crowds are reduced; elevators and people movers are more useful, and even sales conversion rates in a retail setting can be improved.
[IBM]