Having reviewed the origins of the concept of Intelligent Buildings and its increasing importance in the development of residential and commercial projects, it’s worth spending some time discussing its future.
For there are a number of technology developments which are set to have a profound impact. These are: (1) the Internet of Things, (2) Big Data, and (3) Artificial Intelligence.
The Internet of Things (IoT)
According to Wikipedia, the Internet of Things (IoT) is “the network of physical objects—devices, vehicles, buildings and other items—embedded with electronics, software, sensors, and network connectivity that enables these objects to collect and exchange data.”
In other words, IoT blends wireless technologies, micro-electromechanical systems (commonly used in building automation), microservices and Internet technologies. IoT is important because it pushes the frontier of facility automation further: devices can take actions automatically upon receiving data or commands from other devices. The need for human intervention is reduced accordingly; according to McKinsey, the number of objects will grow by 15-20% annually, to 26-30 billion in 2020.
Device interconnectivity is largely helped by the ubiquity of the Internet, which provides the IP-based network infrastructure and communication protocols onto which building sensors can connect. What’s more, countries and telecom operators have initiated public-private partnerships to prepare for the upgrade to 5G networks around 2020. While 5G network specifications are still being fleshed out, the goal is to provide infinite capacity at speeds faster than today’s fastest optic fiber broadband. Crucially, support for IoT is part of 5G networks development plans.
For facility and asset managers IoT may feel like an old concept given a new marketing gloss. After all, building automation systems have been around for some time. But there are reasons why IoT is set to play a more central role in their work. First, IoT is turning into a growing source of revenue and profit growth for chips manufacturers. As they expand their production capacity, costs are going down and R&D investments are going up. In turn this is driving IoT innovation and adoption.
Second, the attention garnered by IoT has led to a race to developing new IoT applications and business models. The field of energy optimization is an obvious area of focus. Expect more far-fetched application too, as an ever greater number of (previously unrelated) systems are able to inter-operate with one another. What’s more, as a world of IoT innovations opens up, so do risks and solutions to mitigate them.
A commercial building with 1000 sensors, each generating 5 data points per hour, generates 44 million data points per year. Purpose-built facilities such as airports, ships, hospitals, etc. generate many times that amount. This does not even take into account the proliferation of data generated by the interaction of building systems and appliances with one another, as IoT becomes more entrenched.
The buzz around “Big Data” –a term describing large structured and unstructured data sets– has led to the growing number of methodologies and toolkits that facilitate the extraction of deep insights from these data sets. Crucially, progress made in the field of unstructured data analysis extends the analysis to previously un-analyzable data, whether machine-generated, such as surveillance video, or human-generated, for example observations recorded during maintenance and inspection rounds.
For facility and asset managers this has at least three implications: First, to turn the sheer amount of structured and unstructured data into meaningful actions, they will need to adopt Big Data technologies, methodologies and skills: from running database; to handling analytics tools, extracting information, and visualizing them. Second, growing compliance pressures are pushing data storage, organization and retrieval at the center of their concerns. Third, improved pattern-recognition capabilities are likely to lead to ever greater emphasis on preventive maintenance work, with the view to minimize asset downtimes, maximize asset performance, ROI and so on.
Artificial Intelligence, or moving towards intelligent “Intelligent Buildings”
Today “Intelligent Buildings” are able to adjust various settings according to pre-programmed instructions. These instructions are created by humans and are set in stone. Progress made in the field of Artificial Intelligence (AI) however is leading to the development of building software capable of learning and adapting, with little pre-programming, or human intervention required.
For example, imagine a residential building constantly seeking to minimize energy consumption, while maximizing the comfort of its occupants. This requires taking into account the individual preferences of each of its occupants; adjusting the temperatures and lighting of each room dynamically, depending on weather conditions, the time of day, day of the week, whether it is occupied, how many occupants are in the room, whether the windows are opened, whether they are using an appliance that diffuses heat (e.g. an oven), whether the trees facing the south window have been pruned, whether solar panels or satellite dishes are added to the roof, and so on. Importantly, not only should it do so in response to a change of conditions, but also in anticipation of future events –for example the expected wake up time of its occupants.
Creating a system capable of handling so many variables and feedback loops is the sort of things that AI is cut out for. For facility and asset managers, integrating AI solutions is a way to deliver on their targets –whether building productivity, maintenance costs, or user satisfaction.
While it’s tempting to dismiss the above claims as science fiction, it’s important to remember that the typical life cycle of a building spans decades. Also, if the history of Intelligent Buildings is any guide, IoT, Big Data, and Artificial Intelligence are first going to transform high value-added facilities such as airports or hospitals, before trickling down to the commercial building and residential building sectors.
In the next post we will evaluate the ramifications of all this for the maintenance side of things.
McKinsey & Company (2014). The Internet of Things: Sizing up the opportunity.
The Economist (2016). Wireless: the next generation.
Chung Yim Yiu (2008). Intelligent building maintenance — A novel discipline, Journal of Building Appraisal, 3, 305–317.
Abinger, T., Kastner, W., Luber G., Neugschwandtner, G., (2008). Enhancing Residential Automation Systems With Artificial Intelligence.