The Intelligent Campus Community – a lightning talk at Digifest

The intelligent campus community

At Jisc’s Digifest 2018 in Birmingham I gave a ten minute lightning talk on the Intelligent Campus Community we are building to support the Intelligent Campus project.

The community of practice gives people an opportunity to network, share practice, hear what various institutions are doing and what Jisc is doing in the intelligent campus space. The community will understand how the intelligent campus project is developing and progressing. This ten minute lightning talk will provide an overview of the intelligent campus project. Why we are building a community and what they will gain and benefit from by being part of the community. They will also find out how to get involved.

As well as chatting about the community, I gave a brief overview of the project as well as introducing the community.

The first of these events is being hosted and taking place at Sheffield Hallam University on the 23rd March 2018 from 10:00 to 4:00, and lunch will be provided. Book now.

The second of these events is being hosted and  taking place at the University of Glasgow on the 10th April 2018 from 10:00 to 4:00, and lunch will be provided. Book now.

Chat Bot Ready

chat bot

Kate Nicolson, a Graduate Education Technologist at Jisc at the end of January attended the Social Software Development Meetup in Manchester. Here she discusses some of the presentations and thinking from the various presentations.

The talk ‘the future of chat-bots’ by Gary Pretty in Manchester was not what I expected. Anticipating a social hypothetical discussion on the application of chat-bots the group received insight to the current technological climate of customer relations followed by a series of practical demonstrations of the application of chat-bots using Microsoft Azure Bot Service.

Mr Pretty opened with a brief introduction of himself as the technical strategist, senior developer and one of the Microsoft MVPs at Mando in Liverpool. The scene was soon set with a quote:

“The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.” – Mark Weiser, Chief Technologist at Xerox.

There is a world of ubiquitous technology where the act of ‘talking’ to devices now being a widespread ‘norm’, so much that non-technical folk old and young are comfortable with AI like Alexa and Siri; this gives chat-bots an opportunity they have not previously had. Chat-bots have been around a long time, however people are now aware of them and understand they are a tool, not a novelty or a trick.

There are now more installations of messenger apps than social media apps. Messenger apps are a domain that are commonplace and part of people’s daily lives. Companies that utilise chat-bots on messenger platforms can reach people in their own familiar territory. Making people come to a website, dial a phoneline or travel to a store, forces them to learn unfamiliar layouts or territories to find a way to get want they want or need. A chat-bot understands the language they use, is in a format they use every day and is laid out in way that is easy to navigate and revisit.

Example: Proactive customer service

The lights go out in your street, you pop on a messenger app and start a conversation with your local utilities company. It greets you, you ask what is wrong with lights in your street, it takes your postcode, it gives you a status update and lets you know it will message you with updates. The messages stay, your details are kept, a few months later you’re at work, you get a message saying that there are issues in your area and they will be resolved asap. This enables you to plan ahead, you’re happy that they have kept you informed and you didn’t have to chase them when you got home.

Example: Cross-platform support

You’re doing research on education technology trends. Using outlook to email a research chat-bot gives you a good 5 articles to start your framework. After laying the framework you start a skype chat with the bot to pull out more supporting arguments and recommended journals around an area. The recommendations spur on ideas that you comment on as your conversations will archive in outlook to build up your notes for later. Later that week as you shape up your report you get a SMS from the bot notifying you that a new journal has come available that has strong correlation to the themes of your report and supplies you with a link.

Bot creation is not artificial intelligence, it is conversation design. The code is a combination of sections listening out for triggers and cascading flows of programmed responses. A bot could listen for the person to ask a question, it will check if something particular is mentioned and will give the appropriate information. The bot can be programmed with defaulting responses like “sorry I don’t understand can you rephrase it”. Depending on the app it is plugged into the bot could present premade options to make the conversation easier to progress through. The bot designer will usually aim to craft a conversation path that gives the desired outcome or information as efficiently as possible.

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Artificial intelligence (AI) is available as plugins, optional attachments, that the bot can use to be more sophisticated and adapt more effectively to the needs or goals presented. Some AI require training before the bot is launched, this means running it through sample scenarios about 200 times so it learns what it should be doing given its context.

Example: Image Analysis

A casting agency app asks potential models, actors or extras would create a profile and upload a picture. The picture would be analysed to check that someone was in the picture, that they didn’t seem scary or aggressive, check there was only one person in the image and that it was ‘suitable for all audiences’. The bot was then able to accept or advise appropriately by responding with something like ‘Hi, I’m afraid there are too many people in this picture, I won’t know which one is you’.

Example:  Sentiment analysis

A useful plug in that can detect levels of anger, stress or upset and score it between 0 and 1. In linking it to a first line customer service chat-bot, it will know when to hand over the enquiry to a human ‘college’ when the sentiment hits a certain level. Issues can be resolved in the most appropriate way, quick and efficient bot for the easy FAQs and complicated ones passed to trained advisors before well before the stress escalates too high.

Some AI plugins are ready to be used by the bot without training.

Example: Translation

Of course, it is recommended that if you have a large proportion of your users from a particular country then you should invest the time and money on translators and cultural consultants. However, to cater to smaller demographics quickly and cheaply the translation AI can do real-time audio and PowerPoint slide translation for live/streamed audiences. It can utilise the context of the words to increase accuracy, but note it may not be able to handle obscure technical, subject-specific or scientific terms.

Excellent free open source bot makers are available, and so easy to use you could make a bot in minutes with minimal technical know-how. The community of bot makers is always expanding and forging tools to make it easy for anyone to create their own.

Example: QnA Maker

Microsoft My QnA service maker is a super slick easy tool to instantly have a bot that can tackle all frequently asked questions. All that is required is to upload a document, spreadsheet or simply point the maker at a web address of the product’s manual or a company FAQ, this is then automatically converted into a knowledgebase. The bot is then immediately able to respond to any question in the knowledgebase with the appropriate answer. This gives a way for the customer to get solutions on channels that are quick, convenient and familiar.

The talk was educational and energising, finding that not only is the world ready for this approach to service delivery and that it is extremely simple to achieve with the right tools. The applications for not only educational services but also resources are endless. It is exciting to think ahead and look forward to having a wide range of bots each tailored to facilitate processes, research, education, collaboration and so much more. This is a great leap towards technology adapting to the natural behaviours of people, contrasting to the old ways of people bending to restrictions of device design.

Sherif Keynote

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There has been plenty of hype over artificial intelligence and the internet of things. Is it time to put aside the cynicism that this kind of hype generates and look seriously at how we can take advantage of these emerging technologies to improve the student experience and build an intelligent library?

This was the opening for my recent keynote at the Sherif event at CILIP headquarters in central London on the challenge of the intelligent library.

The internet of things makes it possible for us to gather real-time data about the environment and usage of our library spaces.  It is easy to imagine using this data to ensure the library is managed effectively, but could we go further and monitor environmental conditions in the library, or even, using facial recognition software, student reactions as they use the library so that we can continually refine the learning experience?

Most smartphones now make use of artificial intelligence to make contextual recommendations based on an individual’s location and interests. Could libraries take advantage of this technology to push information and learning resources to students? If we could, it offers some interesting possibilities. On-campus notifications could nudge students to make best use of the available services such as the library.  Off-campus notifications could encourage them to take advantage of the learning opportunities all around them. Could we use approaches like this to turn student’s smartphones into educational coaches, nudging students towards the choices that lead to higher grades and prompting them to expand their learning horizons.

As we start to use a range of tracking technologies, smart cards, beacons, sensors we are facing a deluge of data in the use of buildings, spaces and equipment across a college or university campus. We are faced with a breadth and depth of data which can be challenging to use effectively and have greatest impact.  These tracking technologies are already widespread in environments such as airports and retail. Often using wifi tracking to track users via their wifi enabled devices and smartphones. In addition sensors are used to track space utilisation and occupancy. Interpreting the data is fraught with challenges and difficulties, as well as potential ethical and legal issues. However this wealth of data does offer the potential to deliver more satisfying experiences for students and staff as well as ensuring the library is used as effectively as possible. I also clarified how the intelligent campus space is big and wide, but our project is focused on one small aspect.

My talk was based on previous talks in this space I gave at the CILIP conference last year in Manchester and more recently in October for CILIP in Scotland. However the talk included more updated information on the potential technical architecture behind the intelligent campus and some of the use case ideas we are looking at.

I ensured we covered some of the core issues when gathering data, consent, ethics, GDPR, technical and even validity of the whole process.

It was great to have the time time to talk about the concept of the intelligent library with an interested audience.

Westminster Higher Education Forum Keynote

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I was recently invited to give a ten minute keynote in trends in the intelligent campus space across higher education.

There has been plenty of hype over artificial intelligence and the internet of things. Is it time to put aside the cynicism that this kind of hype generates and look seriously at how we can take advantage of these emerging technologies to improve the student experience and build an intelligent campus?

I introduced my talk about looking at what was happening (and has been happening) over the past few years in smart and digital campus development.

I briefly spoke about how we now use digital mapping and layers on campus. How a range of technologies are now being used to measure space utilisation. The use of sensors and now connected sensors to provide data on the environmental conditions in spaces across the campus, including lighting, temperature, humidity, CO2 levels and even noise. I talked about smart buildings that take these sensors and start to manage levels in the physical building. I mentioned how timetabling has become digital, though sometimes no more sophisticated than an Excel spreadsheet. I mentioned RFID and Wi-Fi tracking, as well as CCTV and the Internet of Things.

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My keynote described these as smart campus initiatives, but the intelligent campus took all this data and then some and did more. By bringing in data from other places, like the VLE, library systems, even EPOS, doing analysis and predictive analytics, could we by analysing when and how rooms are used organisations will be able to make smarter, more effective use of learning spaces and other facilities across campus and to improve curriculum design and delivery. An intelligent campus could also enable organisations to reduce their environmental impact by monitoring and managing energy use in real time, to streamline waste management, to move supplies around site more efficiently… the list of potential benefits goes on.

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I then quickly described the potential technical architecture behind the intelligent campus.

Overall it was a brief and quick overview of what is happening in higher education now, but with an eye on a possible future.

Intelligent Campus Data Sources

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Within the Intelligent Campus project we have been reflecting on the data sources that we would need to extract data from in order to undertake relevant analytics and also display on a future dashboard.

When it comes to the physical campus and estate there are similar kinds of data that can be gathered about the physical estate itself, but also how people (students and staff) move around that estate.

The following are potential data sources from the estate:

Maps
Space utilisation
Learning space description
Movement and tracking data
Sensors
Temperature
Humidity
CO2 levels
Timetabling
Fitness Apps
Mobile Apps
CCTV
IoT
Smart buildings
RFID Tracking
Wi-Fi Tracking

The following are additional non-physical potential data sources:

Registration system
Attendance monitoring
Student Records (MIS or SIS)
VLE
CMS
Library Systems
Progress checker (eg Promonitor)
e-Portfolio
Assessment planner
Target settings
Web Analytics
Tutor reports
Quality reports
e-Book platforms
Video Server

Some of these may be in the same system, but what is important is understanding how to extract data from these systems in a format that can then be stored in the Learning Data Hub (the new name for the Learning Records Warehouse).

Considering we can define the requirements on how this data should be structured, then it won’t matter which systems are used, the data can be extracted and added to the Learning Data Hub. In some cases standards already exist, which we will use.

Some of this data will be static, or generally static, whilst other data sets will be constantly changing and updating on a regular and irregular basis. That will also define how the data is entered into the system. For example mapping data is static (it changes very infrequently) whereas tracking data is dynamic and changing all the time.

Once the data is in the hub then we can start to analyse the data and see what we can learn and see how we can improve the student experience and see what efficiencies can be gained from more effective use of the estate.

Of course there are ethical and legal issues that need to be considered and taken into account, as well as ensuring consent from the learners and staff who may be tracked.

Intelligent Campus Community Event 10th April 2018 – Glasgow

If you are working in the area of the Intelligent campus and are interested in work being undertaken in this space by others, then we would like to invite you to attend the first of our community events.

The community of practice gives people an opportunity to network, share practice, hear what various institutions are doing and what Jisc is doing in this space.

  • Smart City
  • Smart Campus
  • Wayfinding
  • Wi-Fi Heat Mapping
  • Mapping
  • Space Utilisation
  • Smart Buildings
  • RFID tracking
  • Wi-Fi tracking
  • Facial recognition
  • Chatbots
  • Robots
  • Artificial Intelligence

The second of these events is being hosted and  taking place at the University of Glasgow on the 10th April 2018 from 10:00 to 4:00, and lunch will be provided.

The focus of this community event will be the Smart City.

Learning & Teaching Hub

You will have the opportunity to discover more about the Jisc project that is being undertaken in the Intelligent Campus space as well as hear from others about their work in this exciting topic. There will be plenty of opportunities for discussion and networking.

Book now.

Intelligent Campus Community Event 23rd March 2018 – Sheffield

If you are working in the area of the Intelligent campus and are interested in work being undertaken in this space by others, then we would like to invite you to attend the first of our community events.

The community of practice gives people an opportunity to network, share practice, hear what various institutions are doing and what Jisc is doing in this space.

  • Smart City
  • Smart Campus
  • Wayfinding
  • Wi-Fi Heat Mapping
  • Mapping
  • Space Utilisation
  • Smart Buildings
  • RFID tracking
  • Wi-Fi tracking
  • Facial recognition
  • Chatbots
  • Robots
  • Artificial Intelligence

The first of these events is being hosted and  taking place at Sheffield Hallam University on the 23rd March 2018 from 10:00 to 4:00, and lunch will be provided.

Sheffield Hallam University Eric Mensforth Building

The focus of this community event will be the Intelligent Estate.

You will have the opportunity to discover more about the Jisc project that is being undertaken in the Intelligent Campus space as well as hear from others about their work in this exciting topic. There will be plenty of opportunities for discussion and networking.

Book now.

Join the mailing list

As the project moves through Alpha we will use the blog to update members and the community on progress.

We have also created a mailing list for people who are interested in the work we are undertaking, to find out more about the project, and how potentially to get involved in the alpha and beta phases.

The mailing list can also be the place to discuss issues that interested organisations are facing in the intelligent campus space.

We will also use the mailing list to tell people about forthcoming community events, other Jisc events such as Digifest, and other relevant events and workshops.

You can sign up to the mailing list using this link.

Hot wifi

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There are numerous software applications that allow Universities and Colleges to create wifi heat maps. This is a very competitive market with many different free, freemium and charged for products.

The Jisc Technologies Wireless Advisory Service in 2015 recommended the Ekahau product for both mapping existing wifi networks and for planning new networks. Jisc Technologies published a guide on how to do this a few years ago.

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As part of the intelligent campus discovery phase, the use of data from heat map software was seen as a potential data source for institutional analytics.

So why are heat maps useful for the intelligent campus?

We know they help IT teams understand where there are challenges and issues with wifi coverage, allowing them to move or add wireless routers to the network to ensure better coverage and experience for learners.

However could we use the data from these heat maps to see if we could make other interventions and improve the student experience?

It may not be just about adding wireless routers, if we know where wireless devices are being used extensively on a campus, could we ensure that those spaces are suitable and appropriate for learning? Conversely if there are learning spaces which we have already, but the heat maps show us they are been under-utilised, could we reflect on the reasons why?

Could we combine the wifi heat maps with maps of air quality, temperature and see if there are environmental issues that may have an impact of student wellbeing? Would we then turn off the wifi in order to nudge students to a different location on campus?

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Currently a lot of universities and colleges have systems such as wifi heat mapping, these are often narrow systems with a focus on one aspect. Wifi heat maps are about improving the wifi. If we could bring the data from wifi heat maps and undertake analysis with data from other systems, could we have a better idea of how to improve the campus, enhance the student experience and a positive impact on learning?

What do you think?

Useful links

https://www.ekahau.com/products/ekahau-site-survey/overview/

https://community.jisc.ac.uk/system/files/222/Designing%20a%20Wi-Fi%20deployment%20using%20Ekahau%20Site%20Survey%20Pro.pdf

https://community.jisc.ac.uk/library/advisory-services/wireless-technology-advisory-service

Location, location, education

Use Case: Location aware learning

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Location, location, education

Location aware learning provides universities and colleges with a range of student learning opportunities which take advantage of their current physical location. Consequently, the potential for location aware learning to take place on the intelligent campus is being explored in a range of ways.

Starting with QR codes

Many mobile devices are already location aware but, even without this facility, location based learning is taking place on campuses through the use of the camera on mobile devices along with QR codes. Students can explore learning resources and opportunities across a campus relating to their field of studies, for example, architectural building features, museums objects, gallery artefacts, laboratories or gardens. QR codes are Quick Response Codes in the form of a matrix barcode providing a unique identifier that can be attached to a learning object. The Appalachian State University provides an example having created a learning resource in the Daniel Boone Native Garden using QR codes to identify native plants. (http://bit.ly/2z15d4e)

mobile phone

Moving on to GPS

The technology available in most mobile devices, such as smartphones, can provide much more than QR scanning. They incorporate a range of location aware technologies. Most devices can use a number of these technologies to identify their location. These include:

  • Global Positioning System (GPS) – using satellite signals this technology is accurate to approximately 10 metres and is particularly effective outdoors
  • Mobile phone transmitter towers – generally good in cities
  • Wi-fi – coverage maybe limited but a high degree of accuracy
  • Device’s internal sensors, such as inertia, compass, accelerometer and gyroscope – no external input is required but this is only usable for a short time being very useful in locations such as tunnels
  • Bluetooth beacons –  the beacons need to be close together but they can provide very accurate location data

This all means that the technology is available for the intelligent campus to constantly locate an individual and for the individual to know their whereabouts. This could be useful for security and safety purposes providing reassurance to vulnerable or less able individuals, particularly at night.

Location awareness is a useful facility for a newcomer or visitor to the campus who requires a self-guided tour or directions to a building or room. Student attendance, for example, at lectures, could also be monitored using this location awareness.

Location learning

However, more ambitiously, location awareness could be taken advantage of in module teaching or when informal learning opportunities occur. Systems such as the Adobe Captivate 8, content development suite, utilise the GPS features in mobile devices to create location aware mobile learning modules, for example the Australia Zoo App (https://adobe.ly/2xHe5be). As mentioned previously a wide range of opportunities exist on most campuses to take learning out of the classroom or lecture theatre using all of the campus resources, assets and facilities.

Beyond the campus

As the intelligent campus becomes more integrated with the smart city these learning opportunities will be taken beyond the campus to include the cities museums, galleries, businesses, transport system, utility infrastructure, government and public buildings. Indeed the whole city, in effect, becomes part of the campus. The University of Tampere in Finland is working with the city of Tampere to improve services through location awareness. This pilot includes the use of wi-fi and Bluetooth location techniques to provide indoor location coverage (https://citytrack.fi).

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Augmented Reality check

A significant enhancement, both on the campus and across the city, to location based learning could be achieved through the development of augmented reality (AR).

The use of mobile and wearable technology will increase the functionality and popularity of AR combined with location awareness. Apps such as Lookaround (http://bit.ly/2iQY2Fp), developed at  the  International Institute of Information Technology, Bangalore, allows the provision of location based information on a mobile device using an AR interface. The Wikitude app is being use to explore and understand the Terracotta Warriors exhibition at the Franklin Institute ( http://bit.ly/2zUzMWc  ).

The location aware learning environment

At Athabasca University , Canada, Dr Qing Tan is investigating the “Mobile Virtual Campus (MVC)“ which could provide an interactive platform for online mobile learners using the location awareness and other built-in sensory components in mobile devices. Students will be able learn collaboratively and interactively either face-to-face, across the campus or elsewhere in the MVC at any time. Augmented Reality techniques and the location of learning objects, will allow learners to see the suitable learning contents superimposed upon these specific learning objects including interactive elements. (http://bit.ly/2lB5Snp )

And so…

If the technology hurdles are overcome, it is clear that location aware learning shares many of the ethical issues that are of concern with respect to other intelligent campus developments. Privacy, intrusiveness and security questions will need to be resolved if location aware learning is to take off.

Also, the range of people and departments from across the institution that will need to be involved which will add further difficulty to the management and administrative requirements.

However, location aware learning may well be considered an enhancement to the student experience for the Pokemon Go generation.