The inclusion of space analytics in connected buildings alongside other integrated systems can have significant benefits, in terms of decarbonisation, occupant wellbeing and optimum space utilisation. This is a summary of our webinar which discussed the advantages of space analytics (There are links to the full transcript and to watch the video at the end)
The challenge relates to the many and varied types of space. For example, universities are effectively small towns, with teaching spaces, residences, and specialist spaces such as laboratories, sports halls etc.
Usage is not constant, it varies with time and time of year. Measurement of occupancy cannot be based on a single data point, it has to be dynamic and ongoing. As much data as possible needs to be captured to understand the real situation.
Decisions about space usage, for example, managing HVAC and lighting require you to have a high level of granularity in control terms. There is no point shutting one floor in a building, if you cannot turn off the HVAC or lighting to that one floor.
Room booking systems should, in theory, help, but even if a room is booked, it does not mean that it will be used to full capacity, if indeed it is used at all Space utilisation, therefore, requires the use of sensors to inform managers of the number and movement of the occupants. The difference between expected and actual room use is striking.
There is a rhythm to buildings and spaces that can only be determined with good data. When you have that you need an appropriate level of control to act upon it
There are lots of available technologies used to collect space analytics data, from hard-wired sensors which collect data into a central system or onto a network, or a wide range of wireless (IoT) technologies.
But, it should be stressed that these are just enablers to gather the information used to make decisions based on the findings.
Software analytics tools similarly are just the engine to drive how that information is used.
To make decisions about what technologies to use the key is to understand what the client’s objectives are and what they are trying to achieve. The aim should be to collect and structure as much data as possible from the chosen technology. Whilst improving conditions for building occupants is important, one of the main financial implications is to determine whether upsizing or downsizing is required. If you can identify areas of high (occupancy) traffic this can be used to improve conditions and situate resources such as food availability to best advantage. The same sensors used to indicate people can also be used to locate expensive equipment to speed up workflows. They can also be used to identify areas of high use and expected failure, thereby aiding preventative maintenance.
If space analytics data is shared with the BEMS it facilitates truly demand-led control (ISO 52120 Class A). Utilising your older existing building better as a 21st-century organisation eliminates the need for new build and its associated embodied carbon. It also helps by reducing the demand for more space, with the associated energy and carbon savings that result.
Only 1% of building projects are categorised as ‘new construction’, but the carbon impact of this 1% is equivalent to building a new New York City every month for 40 years. By reducing the need for new build the level of decarbonisation can be huge. Space analytics data can also be used to divert people to areas of estates that are better served with solar power, or lower heating or cooling.
Space is an emotional, and subjective subject. Space analytics data enables a fact-based and rational conversation to be had. Providing direct feedback can help to drive behavioural change. Live data on water usage in showers can encourage people to use less. Instead of using a particular meeting room, it may be possible to use other rooms, of an appropriate size, that are slightly further away. Unified booking systems combined with space analytics data can facilitate such behavioural change. Rewards linked to behavioural change, such as free coffees in return for an increased number of steps taken, and gamifying data are also powerful tools as well as facilitating greater collaboration across organisations, and better well-being.
It’s not all about dashboards! Data needs to be presented in a manner that is understandable to everyone. The relevance of a percentage occupancy number is hard to determine, but a Red/Amber/Green indicator is. Most people do not want to be looking at dashboards as well as their day job. Space analytics data is most relevant when it is presented in a way to make specific recommendations for action, rather than requiring interpretation and analysis. Sometimes the data can be used, even from something simple such as a heat map, to identify unexpected behaviour patterns that would otherwise not be seen.
Some practical initial thoughts on how to start.