When Smart Buildings Become Intelligent
“Good morning and welcome to TheOffice on Main Street”, said the intelligent building, “I see you are here to visit Mr Stevens from FutureCo on level 22. I have notified Mr Stevens of your arrival. He is currently running five minutes late, and has asked me to show you to the meeting room which is currently being prepared for you. Please follow me.”
An automated guide appeared in front of me, personalised with my picture. “Due to a public event in the auditorium we are a little busier than normal. To avoid this and to provide you with the best air quality during your visit, I will take you to your meeting via the bank of lifts on the East side of the building. Would you like a refreshment along the way?”
In this not-so-futuristic scenario, the building is using information about the visitor (facial recognition), data about the location and schedule of the building occupants, and knowledge of the ambient environment (flow of people and air quality) to make an informed decision about how to optimise the visitor’s experience of the building.
So how far away are we from that? Not so far, really, but there’s still work to do.
Making Sense Of Sensor Data
In 2017 the smart building market was worth a cool $7,458.5 million. That’s a lot of smarts in a lot of buildings, but this is set to grow to more than $27,650 million by 2023.
Included in that enormous figure are sensors and systems that, according to the report, “monitor everything remotely”. Being able to remotely and automatically monitor lighting, elevator and washroom use can provide very valuable insights to building owners and facility managers.
For example, instead of having the cleaning crew clean the floors of every corridor, on every floor, every day, with data about how often people have walked down each piece of the corridor, they can avoid underused areas, and focus more of their efforts on tidying up after the party in the auditorium.
From a safety and security point of view, knowing when there is movement in a restricted area or an elevator seems to be taking longer to move between floors can be critical. Having real-time data on occupancy and environmental conditions such as air quality, temperature and humidity can also help reduce a plethora of risks.
All of the information gathered from sensors placed across, and in the building structure can provide a vast amount of useful insight to allow human operators to better manage the building, and the occupant’s experience within it. From this information, owners and managers can help make buildings more efficient (saving costs), more pleasant (improving health and comfort) and safer (reducing risk and insurance costs).
However, as one company I spoke to said, often there can be hidden benefits and values that the human operators perhaps weren’t thinking about, or simply didn’t have the capability to identify.
Using data science and machine learning techniques, the boundless amount of instantaneous data can be analysed to find patterns, trends and anomalies that can help inform decisions about not just ambient factors like lighting and air, but the physical characteristics of the building too.
Discovering Hidden Critical Insights
I spoke with BEAD.digital about the systems they’ve been deploying in commercial properties from Australia, to Europe and the USA.
BEAD have created small, battery powered devices that are packed full of sensors. These devices pick up on light, humidity, infra-red, air pressure and carbon dioxide levels. Some also have the ability to measure air quality factors like Volatile Organic Compounds (VOCs).
BEAD deploy these devices in all sorts of commercial properties, from supermarkets to car showrooms and large office blocks. The devices regularly take measurements and pass them back to a central system using a low-power-wide-area-network (LPWAN) called LoRA. This means that the devices can be placed wherever they are needed, high in ceilings, in restricted spaces, connect and send information, and will last for about three years on one set of batteries.
Beauty In The Unexpected
EAD told me that their original intent for the devices was to measure the ambient characteristics of the buildings, to allow building managers to operate the buildings more efficiently – e.g. turn the heating/cooling on/off as needed, and to know when the lights need to be on.
However, as they analysed at the data that was being collected they made a few really interesting discoveries.
First they discovered that through conflation of the different sensor data they could actually determine how people were moving around the building, they could measure the flow. From this, they could see that the behaviour of occupants in the building had a direct correlation on operational cost.
This opened up many more avenues of enquiry for them and their customers.
Perhaps one of the most astonishing insights BEAD shared with me was that one of their customers used their data to analyse the flow of people through their facility.
When looking at what people actually did and how they moved around, they discovered that their initial assumptions on how the space would be used were wrong, and in fact the emergency exits were in sub-optimal (wrong) locations.
This insight has literally been a life saver. If there were to have been an emergency in that facility, some emergency exits would have been overcrowded, and some underused. Now they building can be reconfigured to improve safety for all.
Federated Data Platforms
BEAD’s system is an easy to deploy solution for both new-build and legacy properties. The passive data sensors mean that valuable information can gathered about the infrastructure, space and people in it, without fear of exposing sensitive personal information. Additionally, with their federated data platform, data can be made available beyond the building owner’s and managers and be safely given to Smart innovators.
Enabling anonymised data to be shared with different entities enables the type of blue-sky innovation I mentioned above, and indeed, BEAD are working with universities to discover more uses and insights for their data.
Actionable Data
As the secrets of the data are unlocked, business rules and logic can be created to enable the buildings to react automatically to certain scenarios. Currently many property owners are a somewhat reluctant to handover too much unsupervised control to computers, but human-supervised autonomous responses are becoming increasingly common place, as data exposes more of the relationship between cause and effect.
The journey towards the intelligent autonomous building I described at the top has definitely begun, but there are still many steps, technical, regulatory and cultural that need to be taken. Perhaps one of the most significant steps on this journey using IoT and data science to codify concrete.
The Importance of Smart Building Data Platforms
Currently most Smart Buildings a silos unto themselves. This makes innovation and collaboration very challenging, expensive and not particularly efficient.
It is only when the building, their attributes, contents and occupants can be described openly in data structures, in a federated platform will innovators be able to explore the potential of how buildings, streets, vehicles and people can work together in smart, intelligent ways.
Only then will I be greeted by Pepper from my autonomous taxi and escorted (via the East lifts), Latte in hand for my meeting with Mr Stevens.
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