Intelligent Campus project update

Since it began, the Intelligent Campus project has consisted of a number of streams. One stream has been to develop a new service that enables data from physical places and things to be collected, decoded, stored and presented. We have been developing the service this year through a pilot with Morley College, as well as internal pilots in the Jisc offices.

Through the lessons learned from these pilots, and further discovery undertaken with members, we have decided not to continue developing this service. However, we have identified a number of new opportunities where Jisc can deliver value to members. We’d like to explore these opportunities as new products/services with names that accurately reflect their goals.

This does not signal an end to our interest in the smart/intelligent campus space, which we view as a useful concept for aligning stakeholders to drive change. Other streams from this project will continue in the future:

  1. We will continue funding the winners of our March 2019 IoT competition. We will organise an event/webinar to share the outcomes of these nine pilots in due course.
  2. Jisc will continue to play a role in the promotion and dissemination of activities in the smart/intelligent space through the Jiscmail, ongoing community events, and other mediums to keep members informed.
  3. We are running our own internal pilots in the Jisc offices, and we will share any relevant insights and lessons. The innovation lab in our new Portwall Lane office will have a number of sensors installed, and a number of products we developed for the Morley College pilot available to demo.

Thank you to everyone who has engaged with the project so far, and we look forward to 2020 and the new opportunities it will bring.

Intelligent Campus Community Event – University of East London, 21st November 2019

The fourth Intelligent Campus community event is taking place on 21st November 2019 at the University of East London from 9:30am to 3:30pm, with lunch provided.

Anyone working or interested in the smart/intelligent campus space is encouraged to attend. You will have the opportunity to discover more about the work Jisc is doing in the space, as well as hear from others about their work. There will be plenty of opportunities for discussion and networking.

Please put this date in your diary, and book onto the event for free using this link where you will also find the agenda and further details:

Green Gown awards – campus of the future category

As sponsors of the Campus of the Future category at the annual Green Gown awards we’re pleased to share details of the finalists as they offer some great examples of innovation and emerging technologies on the university estate.  University College London (UCL)University of NorthumbriaUniversity of the West of England (UWE)University of the West of Scotland (UWS) and University of Worcester are all shortlisted in the Jisc-sponsored category of the annual Green Gown awards, which recognise sustainability best practice in further and higher education.

Read more about the finalists on our corporate blog.

At Jisc we’re always keen to support innovation and drive the use of emerging technologies.  We sponsored the campus of the future category as it aligns with our Intelligent Campus project, plus our Education 4.0 vision, and we’re really pleased with the quality of entries.

You can find out more about Jisc’s vision for Education 4.0, which embraces many of these trends, on this page. Winners of the Green Gown awards will be announced on 26 November at a ceremony in Glasgow.

“State of the art” – the Intelligent Campus in China

This month’s blog is taken from the introduction to a technical briefing on the Intelligent Campus in China, written by Li Yuan, a Learning Technology Advisor at Cetis.

“Compared with the UK HE ad hoc approach to the implementation of the Intelligent Campus, ”one-stop-shop” solutions have been developed to take advantage of the latest data-enabled technologies and AI applications on university campuses in China.

It is a myth that China’s approach to AI is defined by its top-down and monolithic nature. There are ambitious policies and funding from central government, but also provincial and local governments together with private companies, academic labs and other agencies are all pursuing their own interests in staking out their role in fulfilling what is called China’s AI dream. This gives universities a strong impetus to set up AI labs and experiment with all the AI technologies on the market, often in a strong partnership with major players like Huawei, Tencent, Weidong, Alibaba, iFlytek, Squirrel AI and others.

For example, Huawei used their Atlas Intelligent Computing platform with the latest AI technology with a focus on intelligent campus management. On the other hand, Tencent is using its existing mobile technologies to develop various intelligent applications to build intelligent campuses which connect students, teachers and parents within and outside campuses to promote interactive teaching and learning approaches. iFlytek have used their advantages in speech recognition technologies to expand into the educational vertical with language processing technology improving the efficiency of high-stakes testing. Squirrel AI has established a great number of schools across China offering university entrance exam preparation.

A number of Chinese universities are taking part in a national pilot project to test out the most commonly used AI technology: facial recognition. The new system enables students to enter or exit their dormitories using facial scanning at the entrance instead of swiping their electronic pass which is seen as improving the university’s dormitory management efficiency and better ensuring students’ safety on campus. Face recognition technology has also been used in university libraries, canteens and in lecture rooms to identify emotions to register students’ psychological state, which is considered an important parameter for teachers to evaluate throughout Chinese education.”

It will be interesting to keep track of developments in China, where major tech companies are powering ahead with new products and services in the absence of many of the ethical and privacy concerns present in the UK education sector.

Morley Pilot: The Design Process – UX Research

Following our introductory meeting with Morley College, to discuss the Intelligent Campus pilot, we started to implement the first stage of design which focussed primarily on user research. During this, we explored the predicted target audience and discovered how the users would interact with the product through a number of user-centred design steps

The initial meeting enabled us to determine both the purpose of the product and how Morley College envisaged using the dashboard. We were also able to discover what the potential benefits of using the technology may be. From a simple brain-storming workshop it was evident that the dashboard would be used to report on current and historic room temperatures and monitor room usage. We discussed how it could act as a visual aid to monitor motion activity in terms of campus safety in the future. This would allow Morley College to monitor potential patterns or extremes in data over time which they could then look to resolve in order to help improve the running of the campus buildings. Following the meeting, we were able to start our user research process and create a clear product timeline consistent with newly defined requirements.

At Jisc, we have developed our own design sprint process to enable us to create high-quality digital products, meeting client requirements, and deadlines, like this pilot. The process is split into various research methods which are grouped together into 3 main categories: – Understand, Imagine, Build. These stages will be carried out sequentially with the ability to revisit previous stages as the project progresses. In some organisations, certain task and methods may overlap across the stages depending on the type of project and the amount of time available.

Our initial research involved us carrying out competitive analysis case studies, looking in-particular at similar data-driven dashboards available on the market. This gave us a general feel of comparable products, how they function, which elements worked well, and highlighted which elements could be improved. This helped us to understand their design, and we could then take this knowledge to feed into our decision making on whether it would be a useful feature to include within our product.

After researching the market industry, our next task was to clearly understand our target audience and build a set of user personas which we would then refer to whilst designing the overall dashboard. Typical persona data included – Name, Age, Job Title, Interests, Technology, Personality, Behavioural Patterns etc. This then helped to inform our design decisions. These personas were created by using a Morley College staff questionnaire (created in-house), UK education demographic data and previous Jisc UK education persona research. We created two personas which best represented the tutoring staff at the college but who would both have a different practical and behavioural purpose in using the dashboard.

By creating multiple user personas, it helped us to develop empathy with the user in order to understand why they would be using the product and how they would like to interact with it. One way of documenting this was to produce proposed user stories. This detailed how we think the user might navigate the product and document their potential thoughts alongside the scenarios encountered. With our user personas fixed, we were able to create multiple user stories of proposed directional flows and thought processes which would show us any potential obstacles the user might come across during their experience. Based on this information we have been able to fix the issues with small UX modifications, avoiding timely and expensive fixes, further in the process.

From our user stories and user journey mapping, we have been able to collate a list of features and ultimately a list of pages which has helped to build the basis of our dashboard product. Alongside this, we have created a simple sitemap diagram showing the natural flow of the product architecture which we can then refer to throughout the creation of the project to help aid our future design decisions. This is something that may change over time as new features and components are added during the build process. This is the last stage of research before we start creating rough wireframe sketches of how we think the layout of the dashboard could look based on our feature list and sitemap diagram.

Throughout the future pilot design and build stages, we will use this research as a reference point. This will help us to make informed decisions that will result in a finished product that meets both the requirements of the stakeholder and a great experience for the user. Next, we will be focussing on the conceptual stage of the build process which will see us carrying out sketch wireframing, component UI themes, mood-boarding and mockups.

Meeting Morley

A team from Jisc recently took a visit to one of our Intelligent Campus pilot sites recently, Morley College main campus, situated in central London where Lambeth meets Newington.  With technical expertise, user experience expertise and project management there were quite a number of us!  Also joining us were our two SafeHouse Technology Ltd colleagues who are supplying Morley with senors for data collection.

Morley College is very much focused on the arts and music with dedicated art studios, music practice rooms and a it’s own radio station.  The project team at Morley made us very welcome, beginning our visit with a tour of the building.  The building is an interesting one with original parts dating from the 1930’s combining with 1970’s extensions.  This combination throws up a number of problems regarding room temperatures and acoustics.

The Morley team had given a lot of thought to their requirements and selected a number of rooms with different uses and different concerns from which to gather data. It was good to see the amount of thought and preparation that the team had put into the pilot.  In addition to measuring temperatures and other environmental factors in their selected rooms Morley are also very interested in room use, security of rooms out of usual hours, and inconsistencies between room bookings and actual use.

Following our tour of the site we had a in-depth discussion about data requirements, data sharing and protection, user design and dashboards and planning next steps.  We also talked a lot about bringing the student body on board with the idea of the pilot by emphasising the aims of improving the student experience.  We agreed it was important that the college be transparent about the pilot and the use of sensor so that the student body (and staff) can be reassured of their purpose.

Morley were impressed with the dashboards already produced by Jisc and also had a lot of suggested additional developments that could be made. While initial data gathering will be from sensors in the room the ambition is to combine this data with existing data sets from Morley’s systems for a better understanding of the building use.  Overall there was a great combination of what can realistically be achieved in the short term with more ambitious visions of what the future could hold.

The next steps are to get sensors in place and start gathering and analysing the data to see what insights can be gathered.  Both Jisc and Morley are excited to see what can be learnt and developed through this pilot and how a project like this can improve campus life for staff and students alike.

Internet of things competition

We started a new IoT programme to raise awareness about potentials of this technology among  our community.  We wanted to hear new ideas and existing challenges that can be addressed by LoRaWAN technology and through our Jisc and Digital Catapult initiatives, 9 colleges and univerisities will be receiving LoRaWAN Gateways on a long-term loan to test ideas as small-scale pilots.

The successful applicants were:

University of Glasgow – Clean Campus aims to detect the filling level of the bins placed on campus, track their usage and inform the relevant services the requirements about the bin collection/replacement in time to make the campus cleaner as well as save on the time and cost of the services by intelligent planning of their bin collection/replacement visits.

Cardiff University – Smart Facility Monitoring aims to provide a smart facility monitoring and analysis system in the university, including monitoring free chairs and desks in public forum and discuss zone in the library to help students to use and university to manage these university resources intelligently.

NMiTE Ingenuity Studio – Networked Kinetic Sculptures aims to create and site kinetic, physical sculptures at various venues across the higher, further education and skills sector within the Janet community. The sculptures will respond to physical and/or online activity of one and/or various institutions within the Janet community.

Cardiff and Vale College – LoRa Geolocated e-paper.  Aggregating all of the internal challenges of running a multi-site campus, it soon became apparent that most of the frustrating issues were based around losing objects and communications – and this, despite the advantages of mobiles. Putting aside the issue of low bandwidth but given the impressive penetration, distance and low power of the LoRa signal the following idea emerges – ‘LoRaWAN Geo-located e-paper!’

University of Westminster – Realising Sustainability project proposes a new way of transforming our Campuses into unique, Internet of Things (IoT) enabled learning environments. It offers an excellent learning experience for our students, raises awareness of issue of sustainability, and contributes to better performing buildings for the well-being of all at Westminster, and provides a platform to expand our digital capabilities in IoT, data visualisation, asset digitisation and AI.

Bournemouth University – Fine-grained and efficient management of Open Work Spaces in Talbot Campus aims to provide BU staff and students with an automated means of identifying in real-time available and appropriate places/spots at the corresponding Open Spaces of the Talbot Campus thus improving their working and learning experience while increasing utilisation of the facilities.

Keele University – Understanding Library Learning Spaces will use IoT sensors to build an evidence base around library usage in three main ways, to highlight where books are in the library, gather data about book usage and collate data about space utilisation, lighting, heating, Co2 levels etc.

Morley College London – Piano Perspective aims to track and monitor usage of musical equipment to demonstrate return on investment, minimise costs of maintenance and enhance asset security.

CDN & Fife College – FifeNet will develop a multi-sensor LoRaWAN in Fife generating open data sets for educational use in local schools and colleges.

We look forward to sharing updates as these pilots commence and we can hear about the impact they are having.

What’s on the menu?


Use Case: Intelligent Catering

What’s the issue?

Increasing demands and varying expectations from customers at the campus canteen, combined with business needs to operate efficiently, create a challenging environment for the staff and management of these essential facilities. How do catering outlets constantly improve their service whilst also offering interesting and varied menus in a cost effective way? Is everyone able to choose something that matches their preferences, including eating healthily or for special dietary requirements? And how does the canteen cope with all this information, make a profit and encourage people to come back?

What could be done?

Knowing what stock is available and what is being used is critical to efficient supplies on the shelves and counters. A range of methods can help monitor stock and sales including counting people entering, sensors that detect food removed from the shelf, barcode scanning and image recognition. Automatic re-ordering can replace items regularly, and data can be analysed to predict demand in different circumstances and adjust deliveries and production in anticipation. Such techniques could also help minimise waste, perhaps by putting out special offers where stock levels are higher than necessary on disposable items.

Once-only purchases are different from repeat orders, and customer feedback on items can provide more confidence about re-stocking. Feedback could be collected via a mobile app, and indeed selection, ordering and payment could also be combined into app features, allowing customers to pre-order food for delivery on arrival and rate the food afterwards. Individual preferences such as dietary requirements, favourite foods or healthy eating targets could be automatically matched to menu items, providing tailored suggestions on what to eat.

Integrating other data sets moves from smart catering to intelligent catering. Access to data on the location and flow of people in and around the canteen can help estimate likely changes in footfall, as can timetabling data showing when lectures, conferences or events finish. Digital maps of campus can combine with timetabling to indicate where classes of students are currently, and closeness to catering outlets. Similarly, location and timing of events and conferences can influence likely demand for food. Attendance data could complement flow and location to give a picture of how many people are on campus (or parts of campus) at any time, as could data from car park in and out flow.

Predicting demand (and responding more quickly) can help manage stock and menu choices more effectively. Various factors could influence demand for different dishes, including changes in the weather – for example are more salads likely to be requested on a hot day, and soup on a cold day? Using not only the weather forecast, but hourly changes in weather and temperature data, could allow additional preparation or re-stocking of certain dishes, and even promote them via digital screens or apps on mobile devices. Over time, historical data and trends can be analysed and used to predict how likely changes in location and flow of people are to result in food orders, or even which types of events drive demand for which foods.

What examples are there?

Tablets and mobile phones are now seen commonly in the hands of restaurant staff for taking orders, sending the information immediately to the kitchen. Online ordering apps such as exist that send orders to a cafe or restaurant in advance, and allow remote bill paying and electronic receipts, aiming to beat the queues and provide tailored rewards. Some apps also support splitting the bill with others in your group, saving time for waiting staff and providing detailed nutritional information to support different requirements. Others use RFID technology to locate the customers’ tables to deliver their order.

McDonalds is one of several fast food chains that provides a click and collect service through their own app. Customers preorder using the app then scan the QR code at the front of the store. This notifies the restaurant that you’ve arrived so they can start preparing your order. Other services are available that use GPS to detect your proximity to trigger food preparation. Take away ordering apps also track the progress of your order so you can see when it is being prepared, cooked and delivered. Others such as a digital menu that tracks browsing behaviour and collects feedback.

Various strategies are used in stocking and supply chain processes, with RFID transmitters and GPS systems monitoring stock as it passes through the logistics of getting to the store. Inside the cafe, sensors connected to refrigerators, freezers and ovens monitor and notify levels, particularly when safe limits are reached or cooking times are completed. This can help to reduce staff effort in manually monitoring equipment and food preparation. This also extends to humidity, vibration and other environmental factors that impact on the shelf life and hygiene of foods. In isolation this data can ease the use of individual pieces of equipment, but combined with information on sales, orders and stock purchases, staffing and resources, business intelligence can be gleaned. The data is analysed to streamline productivity, enhance safety and security, maximise resources utilisation, including energy and waste reduction, and provide input to marketing.

What about ethical and other issues?

Various sources and types of data are involved, depending on the strategy used. Some of these are generic environmental data such as the weather, or anonymised data on people flow. Data on personal preferences, dietary requirements or healthy eating plans could be considered sensitive in the same way as location of individuals, so clarity on sharing of data and consent is important. Equally, there would need to be confidence that menu recommendations are made for the benefit of the consumer, not just to maximise profit.

Who needs to be involved?

Depending on the type of data, access to other systems may be needed, such as weather forecasting, suppliers’ stock systems, lecture or event timetabling. Some data may be available locally through environmental sensors, such as temperature or humidity externally, and operating data on specific pieces of kitchen equipment – assuming equipment manufacturers provide such sensors that can be securely managed. Other data can be accessed through open APIs such as weather data, although more specific data currently may involve subscriptions. Ingredient suppliers would be a critical partner in logistical processes, and IT and estates departments along with academic services would need to be involved in integrated analytics systems. Personal data would require app-specific sharing permissions from the individual.



Oh no, not another meeting…

meeting in the workplace

Use Case: Intelligent Meetings

What’s the issue?

Meetings are one of the most complained about aspects of the work environment, however, generally it is acknowledged they are necessary, and that good meetings can be highly productive. Can the Intelligent Campus offer some help with the most negative aspects of meetings?

The problems with meetings

Many of the issues relating to this dissatisfaction with meetings are to do with attendees behaviour and motivation. Examples include:

  • Meetings taking too long
  • Poor participant engagement
  • Information not available during meeting
  • Key attendees not available
  • No suitable space or venue available
  • Poor meeting administration – minute taking, actions recorded, etc.
  • Lack of follow up to results and actions

While the Intelligent Campus can not provide solutions to all of these issues it can assist with some.

Provide support and a nudge

Many individuals are not comfortable with the technology that is already available when using a range of data sources to enhance meetings. The Intelligent Campus needs to provide easy to use systems, and better support and training, for individuals who are not confident in their use.

The use of nudge theory to encourage better behaviour is also be a feature of high quality meetings. Examples include:

  • Having a large clock in the room
  • Providing a phone charging station near the door, away from the meeting table
  • Making the meeting attendance voluntary

In “nudging” towards shorter meetings, one simple method is the “stand up” meeting. Meeting spaces need to be designed with higher level (or adjustable) tables along with wall or trolley mounted interactive screens and white boards. Attendees can then move around the room to use these aids to access resources and illustrate their discussion.

An added benefit of this type of meeting is its contribution to attendees health – the benefits of standing up and walking around are clear. “Stand up” meetings, however, should be no longer than 15 minutes or so.

What next?

In future we are likely to see the roll out of greater, and more diverse, data use along with new   technology, in meetings. The use of artificial intelligence (AI) and virtual reality (VR) is already becoming more common.

meeting in the workplace

Find a meeting space with data

The poor availability of suitable spaces is often a factor when scheduling meetings. A range of data that is being collected has the potential to help in finding meeting rooms.

Rooms can have recurring bookings that aren’t actually taken up and block their use by others. However, increased monitoring and sensoring, to collect a range of data, helps. Types of data collected includes:

  • Audio and video – recording the meeting and who is present
  • Temperature changes – simply indicating that people are occupying the room
  • Movement and door access – including smart card use
  • Equipment and wireless use – individual login records
  • Facial recognition – matching attendees to their photograph in HR records

Much of this data can indicate whether a space is actually being used by individuals. if it is found not to be in use, when booked, a request to release the room can be sent to the bookee. Similarly, poor utilisation, with large spaces being under used, is revealed through data collected by room sensors. Suggestions of more suitable alternative rooms can be made.

Data is available to use in real time so a that an unused room can be found for a meeting called at very short notice, even if all available rooms appeared to be booked, since they may not actually be occupied.

If availability is still a problem systems can suggest available spaces that are not designed for meetings, such as teaching rooms, reception and social areas. Other data, such as car park use, predicts that these areas will not be busy.

Also timetabling and historical data can be used to predict that high or low levels of room demand. This helps in smoothing out demand for example, suggesting scheduling a meeting a few hours later, after an event, where demand was very heavy. Other data such as term dates, exam timetables, conferences, open days, etc. affecting demand, can be accessed seamlessly to organise meeting spaces.

Clearly there are always periods during which meeting space demand is high. Are there incentives to move meetings off peak? For example, a coffee machine in the meeting room that is be free to use outside the peak periods. Also bookings slots during busy periods that are very short, may be 30 minutes maximum, while 1 or 2 hours bookings are available outside these peak times.

Translation and accessibility

The Intelligent Campus uses data sources such as HR and personnel records to check on the languages spoken by attendees. If not all meeting attendees speak the same language, instant translation is available through earbuds, but also through real time speech to text translation on screen. This is available for both physical and virtual attendees. Additionally this service is of great benefit to those with hearing impairment.

Virtual Reality

When discussing physical locations, buildings, equipment or objects the use of VR is available to enhance the meeting. Using a VR headset allows a 3D rendering of the data describing an object to be available in the room. All attendees do not need to use headsets. If one attendee wears the headset their view is available on screen for other attendees to receive a tour through or around the object.

Taking care of the administration

Many of the administrative tasks can be fulfilled by technology. As the meeting attendees arrive facial recognition technology, matched with images from staff records, records who is attending as they arrive. Upon recognising them the system logs them into the collaborative tools and resources needed during the meeting. The meeting is recorded (both audio and video) using voice recognition systems. In real time the system transcribes the discussion from speech to text along with who said what. This is instantly displayed on screen. Key phases are recognised to assign to the discussion to the relevant agenda item, also action points are highlighted.

Chatbots (or Smartbots), often using AI, provide a conversational interface (text and audio). Using these to organise meetings is likely to become common(1). Chatbots access a range of data from different sources including:

  • Identify a suitable meetings rooms from campus space management systems
  • Interrogate attendee data such as calendars to suggest a suitable time/date and collate responses
  • Document and data archives to prepare the agenda, previous meeting minutes and papers
  • Equipment inventories and schedules to arrange remote access (video conferencing etc.) for attendees at other locations

Over time a Chatbot also learns about more frequent meetings and anticipate future meetings, attendees and agenda items as well as setting up the environment in terms of adjusting temperature, lighting etc.


The Intelligent Campus provides a variety of meeting spaces, depending upon the meeting timings, requirements and size, along with appropriate technology and resources, to make meetings as efficient and productive as possible. These spaces should provide a pleasant, comfortable environment encouraging collaboration and a collegiate atmosphere to achieve the task at hand. Many of the mundane tasks can be fulfilled through systems organising, recording and following up the meeting.

Useful links (correct April 2019)

(1)Chatbot Magazine discusses the use of AI to enhance meetings. See:

(2) Microsoft have produced a short video providing a view of the future of meetings using some of the technology discussed here. See:

(3)Instant translation for meetings is demonstrated by Translate Your World (TWYI) at:

Intelligent Campus: Risks, Benefits and Ethics

Smart city technologies – from measuring air quality to tracking individuals – have been promoted as hugely beneficial, but also criticised as surveillance environments that deprive citizens of privacy and increase existing inequalities. Intelligent campuses use similar technologies in locations where the boundary between public and private spaces and activities is even more complex. Users who feel their intelligent campus is “creepy” will change behaviour in ways that damage both the campus’s intelligence and its teaching and research functions. Campus managers must therefore select, design and operate their activities in ways that make their value clear to all those who visit, teach, research, study or live on the campus.

In 2011, European Data Protection Regulators endorsed a toolkit for assessing and managing the risks of using Radio Frequency Identification (RFID) tags. Intelligent Campus applications share many of the same issues, so Jisc has generalised and extended this toolkit to help universities and colleges assess the intrusiveness of their intelligent campus projects and determine whether the risks can be managed to an acceptable level. We’d welcome your comments on the draft version of the toolkit, and will be trying it out in a workshop at our next Community Event, in Birmingham on May 7th.

Data Protection law is, however, an incomplete guide to the appropriate conduct of an intelligent campus. In particular, principles of notice and choice are less effective when there is continual monitoring of physical and digital infrastructures that are essential for the campus’s research and teaching purposes. Organisations need to consider ethical questions: what they should do with sensors and data, and how they should make those decisions. Ethical codes already guide the use of online data in research and policy development. Applying these to the intelligent campus highlights a key role for campus users in choosing the purposes technologies are used for, how those are implemented and monitored. A successful intelligent campus, or city, must be based on the intelligence and insights of its citizens.

The Journal of Information Rights, Policy and Practice has just published my paper exploring these issues: See No… Hear No… Track No…: Ethics and the Intelligent Campus.