We spend a huge amount of our days and nights in a building of one form or another. The US EPA estimates that Americans spend at least 90% of their time indoors1! Yet oftentimes, when buildings are designed, constructed and/or retrofitted, the users of the buildings (ie the people) can become an oversight, with the focus being honed on aesthetics, capital costs and yield.
There are many reasons for this oversight, with limited capital budgets, project costs, poor communication along the supply chain and speed to complete projects being just a few. Building information modelling (BIM) is helping to course correct a few of these issues, but research shows that it is abundantly clear that the majority of workplaces in use do not meet the requirements of today’s workforce. Take The Stoddart Review (2016)2 for example, it highlighted that only 53% of workers in the UK and Ireland agree that the place where they work enables them to be productive – this is a startling statistic!
As the workforce continues to change, and with a deeper focus on productivity within companies, we have to deliver buildings that are central to the users needs. And this does not just apply to the workplace, think about the last time that you went to a hospital – were you able to navigate your way around easily? Could you find where you needed to go without asking member of staff?
So what can we do about this? The good news is, buildings are a wealth of data and information. Since the 1980’s and the advent of building automation we have been collecting data about our buildings. In the early 2000s companies started to take data building data and began writing business rules which enabled engineers to understand that assets within the building were not operating as-commissioned, or that they were about to fail, generating insights that we used to drive down energy costs and deliver operational efficiency. But as with automation, this approach, whilst extremely valuable, does not provide any direct value or interaction with the main users of the buildings- the employees – yes they are reasonably comfortable, but they do not have any control over their personal spaces.
Now with the onset and proliferation of IOT devices, the amount of data that is generated on a daily basis by our buildings and surrounding environs has grown exponentially. This is our opportunity to provide buildings which start to work for, and provide value to, the end users, which in turn should increase the coveted productivity which businesses desire.
We can provide users of the building with cognitive concierge services, enabling them to be able to ask for and receive services using natural (conversational) language, via an employee app, such as “I need some coffee”, “Where is the nearest free meeting room”, “How long is the queue in the cafeteria”, “Which is my fastest route home”, “Who am I meeting at 10:00?” for example. Over time the systems will start to understand your preferences and will ensure that the desk you are allocated in any particular office has the light levels that you like, that the correct type of coffee is delivered to your desk and so on.
Using adaptive machine-learning models that explain the consumption by the individual influences such as day of week, weather, occupancy, etc, operators of the building can start to learn and predict behaviours in energy utilization at the building level, at speed and at scale. If anomalies are detected, they can be tracked down to the submeters that caused the anomaly using the meter hierarchy. The models then can help to explain the cause of the anomaly at the asset level. Operators can use augmented reality (AR) to diagnose problems and even control the assets. Using the same approach with machine-learning, space managers will have the capability to learn how space is utilized, at the building, floor, room, desk level and be able to ensure that they have the right type of space for users, today and in the future. They can put a very accurate cost, per person per sqm, and show exactly how much space is costing at its current utilization rate – often this is a very sobering figure.
Think also about closing the loop between design, construction and operation of a building. What level of intelligent and sustainable buildings could we collectively deliver if the data and insights from the operational phase of a building was fed back into architects and designers? They would be able to verify that the designs and materials they chose are fit for purpose, years after construction, and that they are still delivering what they were designed to do. Or they could quickly identify areas that we were not so successful and address them in future designs.
The use cases are limitless, but what we need are forward thinking companies who put their employees and their productivity at the centre of the workplace, ensuring that buildings are working for the people, not the other way around. We have the sensors, we have the data, we have the analytics, we have the platforms, we have the security – now we just need to deliver!
Dr Claire Penny, Global Industry Leader, Watson IOT for Buildings
It is an absolute honour to welcome Dr Claire Penny on stage to talk about “Big data to smart data – how to get the most from your building”. And as a bonus there will be an interview Q&A session with her as well. June 14th and 15th, Nordic Smart Building Convention 2017 in Helsinki.