Smart Building Growth Pushes Tech Leaders To Separate Sensor Traffic From Business-Critical Systems

The modern workplace is filled with connected devices. Occupancy sensors, environmental controls, desk monitors, and building management systems now report into the network, and each smart-building upgrade adds to what is becoming a sensor estate in its own right. Each device draws little on its own, but together they take enough bandwidth to slow the business systems employees rely on. Those devices were often installed one project at a time, and few organizations decided in advance which network the sensor traffic should run on or what the readings would be used for.

Peter Wilson is Chief Technology Architect at Fujitsu, where he is the senior technical authority on a large public sector account and works directly with the client's CTO. He is a Fellow of the British Computer Society, a Chartered IT Professional, and a TOGAF-certified architect. His career has run through major transformation programs across UK government, and his work now covers technical strategy, innovation, and mentoring the technologists on his team.

"You're seeing the smart building take off, and a lot of that is driven by sensors and other devices that need connecting into the network but have the potential to consume significant bandwidth. The value of 5G is being able to separate those devices so the important networks people use for their day-to-day work do not suffer under that load," says Wilson. The dedicated channel he describes is private 5G, kept clear of the corporate network that carries email, applications, and calls. Wilson wants technology leaders to make that split early, while the number of connected devices is still small enough to plan around. The devices themselves are already doing more than a network diagram would suggest.

Presence, not just booking

Occupancy sensing already does more in most buildings than the people working in them notice. "Many organizations are managing their shared meeting rooms not just by how you book them but by what the presence is in those rooms. Is it booked, are there people in there, how many people are we detecting? Is it an appropriate use for the right size of office, or is it just somebody camping out doing calls?" Wilson says. Desks and shared equipment carry the same kind of sensing, and it joins the building management data on power use, temperature, and cooling that facilities teams already collect.

Facilities teams put that building management data to work on energy consumption first. Heating, cooling, and lighting often run on schedules set long before anyone had occupancy data, so a building spends money conditioning empty rooms. Sensor coverage replaces that schedule with a record of use, and it gives property teams the same record for space by showing which floors fill up and which stay half empty through the week. Wilson attaches a limit to the savings available. "You're always going to want to reduce costs in terms of your building management, within the boundary of the regulatory aspects about the range of temperature that building should be for human use."

Data with a purpose

A sensor estate produces far more data than most teams have questions for, and Wilson begins with the decision a team needs to make before looking at what the sensors report. "There is a massive data opportunity to understand and optimize the use of space and the productivity of the humans working in it. Having a really good view of the cost base, the data points being collected, and how those data points support your understanding of that cost base is pretty important," Wilson notes.

Tuning the building

Occupancy and environmental readings also support finer decisions about how the space runs day to day. "The more information you have about the way people use the space, what time they come in, how that relates to the time of year, and what rooms they're using, the more you can optimize the environment in all those spaces and, in theory, the utility bill side of things," Wilson explains.

Heating, lighting, and space each improve on their own once a team can see how they are used. Pulling all three into one model of the building is the larger step, and that model has a name and a history outside the office. Manufacturers built the first digital twins around a large machine or a ship's engine. Sensors tracked the condition of the equipment against the readings a healthy unit produces, which let engineers predict failures early enough to service it before it stopped. Wilson applies the same construction to any environment worth understanding. "It's about being able to model the environment that you're interested in and then understand what the behavioral cues are," he notes. "What does normal operation look like, and what are the parameters for that?"

The digital twin

A workplace introduces far more variables than a ship's engine, though the construction carries over. "A digital twin models the environment and captures the behavior taking place within it. In an office, that means understanding where people congregate, which entrances and exits they use, and how different areas should be heated and lit based on actual use," Wilson explains. The model is only as detailed as the sensor coverage behind it, which brings the question back to device density and the network that carries it.

Wilson points to public sector organizations running facilities for their staff, transport organizations operating stations, and water companies managing sewage and drainage networks. The water industry is where he first saw the case for private 5G, with sensor technology monitoring leaks and flood warnings across infrastructure spread over a wide area. Each of those organizations runs a physical operation at a cost, with people moving through it and equipment that has to keep working. "Any organization that has to manage resources of a human and non-human nature is going to get some value out of understanding how those resources interact with each other and how they're used," Wilson concludes.