1. What is the intelligent campus?


The term intelligent campus is becoming more popular, but what does it mean?

How can a campus be intelligent, and is it achievable or desirable?

Readers of this blog will be familiar with the concepts, but this post is one of a series developing content for a “guide” on intelligent campus, and so we’ll step back to the basics first to more fully explore the origins.


To be intelligent is often defined formally as having the ability to learn, understand and make judgements about something (Cambridge) or to be able to acquire and apply knowledge and skills (Oxford). However, definitions exist that are specifically in the context of computers and machines, such as “able to vary its state or action in response to varying situations and past experience” (Oxford).

The field of artificial intelligence (AI) is relevant here, which aims to study the extent to which machines and computers can be developed with aspects of intelligence. As general intelligence is a rather complex concept to tie down, AI helpfully breaks it down into a series of central problems (or goals) – including reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.

In understanding what the intelligent campus is (or could be), these AI topics are a useful starting point to describe, evaluate or even design “intelligent” actions or devices.

Perception and action

Perception is a good place to start, with the use of sensors for measuring changes such as temperature or motion and more complex devices such as cameras or GPS enabled equipment.

Data from such sensors could combine with knowledge about the environment (objects, concepts, relations) and lead to reasoning – logical deductions from the data. If we take this a step further, goals could be set, actions taken to adapt the environment, and learning could help the devices improve through experience.

This cycle of perception, reasoning and action is a simplified version of what humans do, and the replication of this, or parts of it, is what AI attempts to do with computers and machines. The extent to which the intelligent campus concept spans these different stages will be something discussed as we explore the topic further.

Central to this are several things, including data, devices and connectivity. If we have devices with sensors that can collect data, we connect them together to enable the data to be transmitted and shared, and then process the data in some way.

The Internet of things

Current everyday devices such as mobile phones can collect data on various aspects of activity including location. Mobile phones also have connectivity, through the telecommunications network or wifi through to the internet.

In fact, not only are mobile devices connected to the internet, but many other common devices, from webcams and printers to central heating systems and baby monitors within the home. Out on the streets we can see connected vehicles, ticket machines and lighting, and engine maintenance and healthcare in industry and public services. An interesting extension to this is the concept of wearable devices, for example used for health monitoring or fitness applications.

This has become known as the internet of things – a wide variety of devices connected to the internet with the ability to collect and transmit data. This provides the potential to integrate all manner of data and use it in aspects of the intelligence concept for example reasoning or adaptation of the environment.

Data and analytics

Data is all around us, and is the subject of much topical debate, including work on open data, big data, and analytics, not to mention ethical issues including privacy and security.

In many ways the collection of the data is easy, it is when we try to interpret and make sense of it that we hit many of the challenges. Analytics has become a common term used to refer to the identification of patterns and interpretation of data. However, it can span a wide spectrum of sophistication of usage, from presenting and describing through to developing insight and making predictions.

See how Jisc are developing Learning Analytics.

Becoming smart

So the concept of intelligent campus hinges on several key points

  1. The availability of connected devices and sensors
  2. The ability to collect, store and process data
  3. An understanding of what the data is and how it can be used
  4. A set of goals to benefit the recipients in making use of the data

Many would argue that the last of these is crucial in making this a meaningful and useful topic to explore and apply. What is also important is to consider the combination of these aspects together, and not one in isolation, for example having a high quality network infrastructure is only one part of the jigsaw.

Sometimes the term “smart” is used in the same context to explore what a smart campus is or the use of smart devices. In many ways this is synonymous with intelligent campus, although subtle differences in meaning between the two terms do surface in discussions on the topic. Some technological definitions for example refer to smart sensors that possess the ability to collect and transmit data but lack the reasoning aspects of intelligence. Perhaps the important point here for those attempting to develop smart or intelligent campuses is to see beyond the data and the technical capability to more fully understand the purpose and the benefits or otherwise.

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