Latest trends in campus design that is Smart


Though I left the project in March, in my new job and as part of Jisc’s job on Education 4.0, I still have an interest in that area and what’s potential and what benefits it may bring universities and schools.
Last year I wrote a post for Educational Technology about just what the distinction is between an campus and a smart campus.
In the Westminster Higher Education Forum on the December I presented a short presentation entitled Newest trends in campus design.

Latest trends in campus design

I wanted to talk about how the past’s campus is evolving into the smart campus nowadays, but look ahead to a future where we might have an campus.
The campus is currently here; data analysis capacity and the technology, sensors are available, however it isn’t all joined up and so has limited scope in terms of what we can learn and how we may use the knowledge. What we need is the campus, where data in the online, electronic and physical environments can be combined and analysed, starting up vast possibilities for more effective utilization of learning and non-learning spaces.
I asked this question, what’s a campus? Round the UK (and the rest of the world) there is not any standard model for an university campus. Some university campuses have been based on a single campus, many others have multiple websites, some across a town or a city. Some campuses are the university, the university has not over others, they’ve acquaintances. These might be related businesses and businesses, but it will be just at times individuals, and other acquaintances, a few retail company, occasionally educational providers.

You might have buildings. Some a few old, some not so brand new and will be brand new.

When a few of them were constructed they were really”dumb” buildings. They’d have experienced heating and lighting, but it would have been designed at that point with few if any controls to the consumers of that construction. Well there might have been light switches!
Picture by dmvl out of PixabayYou could assert that called clever buildings have been around for a while now, a thermostat is something of a smart technology, they enable the heating system (or the air-conditioning) to come on when the temperature in the spaces reaches a desired setting. Though in some places that setting can be adjusted by the users of the spaces the configurations are fixed and can not be changed. In a similar way sensors enabled lights to be turned off if no moment could be detected, although sensitivity was hard, as is often seeing people in classrooms and offices waving their arms about when the lights go out.

In most ways a smart construction is one in. Building a data image of this construction, from usage of electricity, heating, water, lighting, energy use. Utilisation, occupancy can be also measured by some buildings.

That data could be stored in a data hub and portrayed in a dashboard of some kind, visualising the narrative that the data is telling us. We may understand what interventions to make to reduce energy costs, improve utilisation and so forth.

Among the challenges for the smart campus, is that it is unlikely that each building has the very same capabilities in regards to the collection, storage and visualisation of data. Partly because buildings were probably built at various times, but the lifespan of building program that is clever is not a lot longer than the lifespan of buildings. The final result is that with bigger campuses, you might have multiple sensors, multiple data hubs and vastly various dashboard and visualisations.

You could argue that the first real smart estate is one where the construction data is aggregated and the dashboard and visualisation provides a general view of this campus, but you can drill down to individual buildings, possibly even individual rooms. You might need to think about how to record that data in a format that is consistent that is conventional, so that it used and may be aggregated.

So a campus?
What will make it intelligent?

Well a campus does not exist in isolation. As well as all of that buildings and estate data there is a wealth of other data been gathered as well.
The challenge often though is that data is in silos. Locked away in it’s own data hub and dashboards. If we could permit the data to violate…. We create a campus with a more profound enriched set of data than just the buildings data. Could we add in data about the consumers of this campus, how they’re using the campus, where they’re employing the spaces around the campus. Transfer utilisation and congestion. Weather and other environmental factors, such as air quality, might be taken into account. What’s happening that afternoon on the campus, will there be less or more individuals than usual. Will there be guests around? What about differentiated energy expenses? Are there some days when energy is cheaper? What about the program, who’s in that afternoon for teaching, who will be in the library? Are there any examinations? You might go on.

Picture by Edgar Winkler in PixabayA smarter campus will take data from a range of resources, not only the physical areas of the campus and the way they’re being used, but also the data from electronic systems such as attendance records, the virtual learning environment, the library, student records, digital point-of-sale and online services.

This approach can provide intelligence and insights into the student experience that we would otherwise miss. These tips can inform and encourage decision-making by people across the campus, including students, academic and professional support staff. By employing live and dynamic data, decisions can be made that are based on the current state of the campus.

But it isn’t just about collecting data, could we create personalised dashboards for various areas of the university, including in real life and estate data into their datasets to create a deeper richer image of what is happening. Allowing for interventions that take into consideration a dataset as opposed to a data collection.

This would enable us to build a more glowing campus.

What do we mean by the intelligent campus? Well a wider and deeper dataset provides us with a much better image of what is happening on a campus, it provides us with the intelligence to produce date-informed decisions about changes we want to make to the campus, the student experience, and much more.

But could we begin to envision a future in which we can begin to predict the way the campus will be used, so instead of react to what’s happening campus, we can be proactive and make interventions before something becomes an issue. Using a selection of processes and methods to improve that overall student experience.

The next level of this intelligent campus is to move beyond using this live data to bring a machine learning element to the analysis, providing further insights. Bringing in historic data, feedback and evaluative data, we can begin to put in a level of predictive analytics that will enable staff and students to make informed decisions about what’s likely to take place.
Picture by RHMemoria out of PixabayHowever…

It is not always going to be so simple is it?

Some of our data is locked away in proprietary programs, we are not able to access that data and add it to a central data hub. Should be be today, systems that do not allow the data to be accessed by us ?
Will they use them, although you can provide individuals with dashboards? Will they understand how to use them?

Ethical use of data is critical, these systems may stem, sorry monitor, people across a campus, they can see where they are, what they’re doing and who they’re with. There are.

Legal use of data can also be important, you can’t afford to ignore GDPR and other legal requirements in using individual data.

Having said this, there are some real problems that need to be solved. How can you define a distance? How can you define occupancy and utilisation? Can you understand what people are currently doing and how they’re employing a distance.

Another aspect is validity because there is correlation, this does not mean a connection is between the data sets. The data tells a part of this narrative to you.
Universities across the united kingdom are building campuses, however the real cutting edge stuff is when people begin to move from the smart campus, earn predictions , more analytics and more data, and begin to build the campus.


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