Due to the restrictions imposed to halt the spread of COVID-19, namely lockdown and social distancing, buildings emptied out. It is only recently that people have returned to offices, as well as pubs and restaurants, and even then there are strict rules in place to prevent an outbreak. But—as many an embattled waiter, bartender and barista has found—it is hard enough to manage even a small space, let alone a many-storied, multi-purpose building.
IoT is an elegant solution. Sensors reading light and motion, analysing critical equipment for damage or wear and tear, recording footfall and movement of people between floors—all of this gives building owners and managers a level of knowledge never before possible in the built world.
Of course, the data alone is not enough. An organisation needs analytics to perform a statistical analysis of collected data and reveal patterns, correlations and cause-and-effect relationships. It is only through analytics, in other words, that you can make sense of the data and uncover meaningful trends. Using a private cloud, you can analyse data on demand, turning raw fragments of knowledge into intelligence: gathering, integrating, analysing, and then presenting insights to the building owner. This will increasingly be made far quicker and more stable by the widespread deployment of 5G, which combines high-speed connectivity with very low latency.
But even as it is, owners in the COVID era can and have used the intelligence afforded to them by the complementary technologies of IoT and analytics to control the flow of people through a building as needed and identify potential bottlenecks in enclosed spaces like lifts, where the risk of infection is greater. They can direct cleaning teams to those areas of the building through which people frequently pass in order to keep them hygienic. They can make spaces ever-more secure, and track the use of desks, meeting rooms and other utilities, especially in co-working environments.
Over time, the data gathered by IoT and made intelligible through analytics can reveal trends—for instance, relating to peak hours and other metrics and measurements. It is unrealistic to expect building owners, even armed with a great deal of data, to be able to control everyone and everything in their buildings as-needed. But with sophisticated modelling based on that data, they can predict and take anticipatory action. There may be an overused meeting room, for instance; or the lift to the first floor may be overused when the stairs are a viable (and safer) option for occupants.
IoT is also a key part of predictive maintenance, and predictive maintenance is essential to creating a frictionless experience within buildings. The breakdown of critical equipment, from escalators to elevators, forces potentially large numbers of people to take whatever remaining options are available to get where they need to get, which in turn creates bottlenecks and a greater risk of infection. IoT allows building owners to assess the wear and tear of machinery and dispatch an engineer or team of engineers to undertake a repair or replacement before a fault renders the equipment unusable.
Commercially, IoT has allowed for much greater flexibility in the contractual relationship between building owners and building services teams. Provisions can now be made in contracts so that maintenance, for instance, relates to usage, and this would not be possible if the building owner did not have an accurate understanding of how the building was being used. At a time of great financial uncertainty and general unpredictability, especially in real estate, this is an enormous advantage. It protects potentially vulnerable organisations from getting tied up in contracts only to find that they are overpaying for a service that does not correlate with how their building is being used.