Putting the value on data in smart buildings

It's raining data - but how can you control the flood?

When we have data we can’t understand or contextualise, we may as well have no data at all. Mark Bouldin of Johnson Controls looks at how to make the most of your building data. 

Every building has a purpose. Whether it’s the building you shop, work or socialise in. They make a difference to our lives every day. It’s no surprise then that we spend 90% of our time indoors. However, the very basis of how our buildings function depends on the safety, security, and well-being of the people that use them.  

The way we use our offices, for example; has massively evolved since the start of 2020. We have become more flexible, often only attending the office when there is a clear purpose and advantage in doing so. The building itself is no different, but we now need to evolve the way our buildings operate to work for our new requirements.

Research from McKinsey Global Institute estimates that data and analytics could create value worth between $9.5 trillion and $15.4 trillion a year if embedded at scale, showing the true impact that siloes are having across industries. So, we need to start valuing and understanding our data. Only then can we improve occupant safety and comfort, save on costs and achieve sustainability targets. 

When we have data we can’t understand or contextualise, we may as well have no data at all. Siloed data is dumbing down our smart buildings, but the challenge is that we need to manage the combination of operating technology, bringing together multiple data sources and different systems together to drive value. Right now, the data from each of these point solutions is siloed and disconnected. This is preventing building managers, developers, and owners from seeing the bigger picture, limiting them to small, incremental changes that don’t help realise the full potential of their investment in smart.   

From here, it is then possible to move up the data value ladder, unlocking the true benefits of ‘smart’. On the surface level, data can be descriptive, telling us what is happening now. This insight then informs how we move up the levels; diagnostic, predictive, prescriptive and finally, the zenith of cognitive data where AI and automation come into their own.  


Identify the link

There needs to be a link between the building and the data, as it provides invaluable insights into how the building is used. You can take a snapshot of the energy in a building and understand its performance, but this won’t help until you have the context of other data, and how that influences the building. Understanding siloed data as a connected network means we can approach each building differently, to make recommendations that are more energy efficient and cost saving. By connecting the siloes, we can enrich the data to provide the diagnostic data as well as the descriptive data that will help climb the stairway to value. 

What’s more, many buildings house multiple occupants, with various needs and expectations. This is especially true as we are working in a new hybrid world, with flexibility as the focus for many. Needs will vary from building to building, and data averages in the industry aren’t applicable because it’s about the individual building’s requirements. However, some things will remain consistent: The need to drive down energy usage, move towards carbon Net Zero, improve indoor air quality and provide an impressive and comfortable experience for occupants. All of this is harder to achieve when a building’s data is sitting in siloes, underutilised and unable to provide a 360° view of what a building can really offer.  

To reach this potential, we have to get deep below the surface level of smart technologies to unlock the insights they generate. This happens when we connect smart technology systems together to create an ecosystem or platform for smart solutions, looking at the bigger picture. The data and insights this creates can then be analysed to make vast improvements across a building, and even the whole enterprise.   

To make this a reality, the data needs to be connected and easily accessible in the cloud. Then decision makers can analyse the data in its entirety and identify areas of improvement. They can focus this analysis on processes such as maintenance, energy savings and sustainable development  or wherever needs attention at that time. Then, they can pinpoint the smart technologies that can make these adjustments autonomously and improve the experience that tenants receive. From these foundations, building and office decision-makers can create something which is truly smart.  

Once the building data is embedded and utilises technologies such as Artificial Intelligence (AI) and Machine Learning (ML), we can truly reap the rewards and increase occupant safety and comfort, while saving on costs and achieving sustainability targets.  

With the use of technology, including data and tracking software with AI and intuitive dashboards that follow indoor air quality and energy consumption, our buildings can make predictions with smart algorithms.  

Based on historical patterns, algorithms predict load profiles as well as plant and equipment-level energy performance at different operating conditions. Every major piece of equipment, including chillers, boilers, pumps, cooling towers and energy storage, has an energy model that predicts the equipment’s performance under different operating conditions. The optimisation algorithms run every 10-15 minutes to decide dispatch decisions. Here, it decides which equipment to turn on or off and what system level setpoints to run for a wide variety of cooling, heating, and power generation systems. This continuously minimises costs and reduces energy.  

Analytics and AI solutions have historically focused on solving one goal at a time, whether it be clean air, energy efficiency, safety, or even comfort and experience. However, measuring, tracking and acting on data gives us control over every single goal we want to achieve.  

As the UK is in a time of ongoing economic instability, businesses are doing all they can to ensure that costs are low and return on investment is high. However, we must remember lowered costs, energy efficiency and clean air can all go together. With AI, ML, and democratised data, we can start to see a change in our buildings that will better our future.  

Mark Bouldin is Clean Air Expert at Johnson Controls 

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