 Hi everyone. So today we want to talk a little bit about the Internet of Things and how it was supposed to save the world. What I wanted to start off with is a little bit of an exercise. So this morning I got up and most of us, you know, I start off with a bit of positivity in our life. And what I want to ask the audience is what kind of decisions did you make today? How did you get to here? So hands up if you had a shower. Good. Hands up if you had a bath. Not too many, one or two. But there was a decision there, there was water usage associated with that. We all had breakfast, I hope, most important meal of the day. Hands up if you had the dirty Irish fry. Couple of people, okay, quite health-conscious. Hands up if you had some fruit or something a bit lighter. Much more people doing that. And again, the amount of water used in creating the fry is a lot more as well as the energy as well. Transportation, we've talked about this a lot. Who got here by car? Hands up. Good, few naughty people you shouldn't drive. Hands up if you came here by bus. Much, much better. And for the really healthy people, did you come here by walking or on the bike? Okay, a nice mix. The point here is that there's a lot of choices that we have. We're in a room it's at probably about 26, 27 degrees, it would actually be much more energy efficient if it was 19 degrees. If you take your holidays, you use an incredible amount of carbon in your flights, your accommodation, etc. The big challenge here is that we're making decisions all through our day and we don't really understand about what's the cost of those decisions? Do we actually understand what kind of energy has been used in in our dirty fry? What kind of water usage has been used in that? And it's very, very difficult for people to figure this out because every decision has a consequence and it's difficult for us to understand this. So this is really the core challenge that I'm talking about today. It's how do we get people aware of what are the consequences of their choices in terms of their everyday decisions? And more importantly, how do we actually try to enable them so that they can take positive actions? How do we motivate them to try to save water and energy and usage within these smart environments that we've been talking about? Now, we've heard a lot about great technologies, IOT, AI, big data, and wasn't all this supposed to be solved? You know, once you plug in a few smart devices, everything takes care of itself. Well, I'm here to maybe burst the bubble a little bit. By pointing out that these technologies are incredibly challenging. From a technology point of view, data sharing is not simplistic, technology interoperability is a major barrier. All of these systems are incredibly complex from a configuration point of view and administration point of view. And the return on investment is still not 100% clear cut in a lot of situations. I'll refer back to John Elder this morning as well where he talked about the people problems, the social problems that exist with these solutions as well. We're collecting lots of data, it's really interesting, it's really fascinating as a computer scientist, I love this stuff. My mother, not so much, she still doesn't know what I do with my day. So information overload is a big challenge, data interpretation is a very big challenge as well. And just trying to make this a little bit more interactive, a bit more seamless in everyday user's life is a big challenge as well. And ultimately, this leads to low levels of user engagement within a lot of these environments. And this is the realism of the situation today. So what I want to talk about in the next few minutes is to present a model for how we can use IoT to try to enhance user experience. And this is a very simple model here. We look at the world as being from the physical to the cyber world, but also to the social world as well around human interaction. We look at the need for the digitalization part, which is critical for collecting and analyzing the data. But also, what's missing there on that human interaction part? How do we actually engage users in the process and make them feel part of it? First, we'll talk about the easy bit, digitalization, that's where we're here for. There's no need to talk about the technology trends that's driving this. We've had some fantastic presentations just before this and this morning. But data is at the heart of it, devices are at the heart of it, people and engage them in the process is all very, very important. Some of the technologies that we've developed at Insight to help try to solve some of these technology problems are around the use of data spaces to make it easier to be able to share data in a more interoperable way and to kind of integrate data in a pay-as-you-go manner. We've also invested a lot of time looking at cognitive adaptability, trying to make these systems more self-sufficient. How can they self-configure themselves? How can they self-optimize themselves so that it doesn't require a human intervention? And those are really the kind of key technologies that we have. On the data side, this is quite straightforward. It allows us to bring together data from devices, from things, from different types of sensors within the environment and to connect it to that contextual data that's needed to be able to understand it. Once we have the data in place, we're able then to analyze it using data-driven and rule-based AI techniques to be able to optimize different models for decision support within the environment. So this is pretty straightforward. We've seen a few presentations on this. It's very nice. What about the user experience? Does anyone care about this? How do we actually engage that user into the process? So we have the data, it's in a good place. What do we do next? And this is the critical part to having sustainability. We started to look at this process, and we came across an area of design research that looked at the area of persuasive design. How do you actually make the design of something more intuitive so that it actually creates a positive behavior? And everyone's familiar with these two examples. So while I don't personally like speed bumps myself, they do make me drive slower. They do change my behavior when I'm driving around them. You get safer driving in those conditions. And everyone's also familiar with that notion of recycling. And by correctly designing the recycling techniques, we can all guess where does the paper go? Where does the can and bottle go? So by looking at the design, we can actually shape the behavior of users. This can be used within the design of actual technologies themselves. So the notion of persuasive technologies, we talked about by Fogg, who is one of the fathers of user experience design. What he looks at there is how we actually shape our technology to actually try to have a positive behavior or to change the attitudes of our users. So this was our starting point from a design point of view. What we wanted to do was to leverage all of this IoT and big data to be able to create a positive user experience for the people within our smart environments. Critically, we wanted to engage non-technical users. If you need a PhD in computer science to use this stuff, the game is already lost. So what we're looking at is your average office worker who can interact with data at a very, very simple and clear level. We wanted to ensure that we could inform users within our smart environments about their energy usage and water usage. And we wanted to be able to motivate their change to actually have positive effects on that. What we were inspired by is the psychological literature. This is the trans theoretical model that was come up in the 80s. And it's a collection of the different psychological models that were there at the time in order to look at behavioral change in humans. Typically, it's used to help people who have addiction. So if you're drug addiction, alcohol addiction, gambling addiction, hands up in the room. OK, no, no, thank you. Basically, this is the cornerstone of the psychological theory that actually helps people to recover from that. We looked at it from the point of view that energy and water usage are a form of addiction as well. So could we actually leverage this model to help us structure a user journey for the people in our environment? The model has a number of different steps from pre contemplation. The person is unaware of the problem to contemplation. Oh, I'm aware of a problem. There is a problem that I need to sort. Preparation. OK, I'm getting ready to take action. Action itself. OK, we're making positive changes. I'm doing the action that I want. And then we have maintenance. How do we keep that person in that positive step? And with this, what we've done is we've actually structured the second half of our model to actually identify where those different stages a user could be at on their journey within the trans theoretical model. So pre contemplation, contemplation and preparation is all about user awareness. And then you've got action and maintenance is very much around that user engagement side. With this user journey mapped out, what we then did is looked at all the data and tried to devise a set of applications that could actually help the users understand where the on that journey, what information do you need at that stage of the journey to help you understand where you're at and to maybe guide you towards what's the next step that you would take. So it's very much trying to structure that user journey across that psychological behavioral model that we identified to give you a couple of examples of that. What we did is we actually had a number of pilots across a number of different organizations in the world. So we have a pilot that was running the Nati Airport in Milan. We've run it in a couple of different buildings in the university down in Galway. We had a group of 12 houses in a thermi in Greece. And we also run it in a primary school as well. So what that gave us was a wide range of different users that we could interact with everything from the business traveler to the family traveling to the family traveling on holidays, school teachers to school kids, software engineers and data scientists to coffee engineers and pastry scientists. Our user experience design principles was very simple. We wanted to have different levels of engagement for the users that we had. We use the TT model, the TT model to do that. And we leveraged the notion of progressive disclosure, the idea that we didn't want to overload all of the users with the information that was there, but that we would slowly reveal more and more information as the user interacted with the system to give them a feeling of what was taking place. We also used gamification. So some of these kind of social influencing aspects to help people to be encouraged to engage in energy saving behavior. And by looking at the behavior of their colleagues, their friends, their family members, that can be very positive in reinforcing their own belief to do it very much like going for a run with your friend. Half the time you wouldn't run if your friend wasn't going out, but the two of you go together. And then finally, we wanted to be able to provide proximal and actionable feedback. So when a person is making a decision about using water or using energy, we wanted to be able to get the feedback into that moment as quickly as possible to guide them, to inform them of their actions. Here are some examples of some of the interactive apps that we created. One is at the building here in Galway. The other one is actually in the airport in Milan. And these were about the contemplation stage. A person kind of walking around the space, maybe might be wondering what kind of energy or water usage is taking place here. By having interactive public displays, people could engage there and start finding out about how the building is using the water, how the occupants in the building are using water. This goes right down to the idea of personalized dashboards where people in a home setting or in an office setting can actually get detailed information about how they're actually using water and energy within that context. And this can help them to understand what kind of actions can they do and can they take to actually reduce water and energy usage that's there. And then finally, the notion of alerts and notifications. This is very much about giving specific targeted information to people at points of energy consumption or water consumption, telling people if there was an alternative available to them or at least reminding them of the actual embodied energy or usage that was used there. And obviously, things like smartwatches and a range of mobile devices were very important to connecting to the person in that context. The impacts that we had in our pilots were very positive. The rent for a three month period and we managed to reduce 65,000 kilograms of CO2 emissions. We had 62,500 meters squared of water savings. We reduced energy consumption in the pilot areas by about 23 percent, which would also include the energy needed to pump water within the environments. And we also were able to clearly identify cost savings of 45,000 euro. Interestingly, as well, the cognitive techniques that we developed to be able to identify optimization opportunities identified five leaks in buildings that were less than 18 months old. So even in new buildings that were creating today's, there's actually leaks from day one in those systems. And even though those systems had building management systems in place, there was no clear way for the actual operators to actually see those. So really data is one thing, but analyzing the data and extracting actual actual knowledge is the critical part. From a user experience point of view, the things that we learned is that it's critical not to overload users because quickly people turn off if they see too many figures. It's really important to understand your user's journey, where they're coming from, where they want to go to and designing an experience that matches up with that. Social influence is critical within this context in terms of encouraging people and creating a team-like environment or a supportive constructive atmosphere to be able to encourage positive behaviors. And it becomes very important as well to carefully target these notifications that we talked about because there's nothing worse than waking up and getting 17 notifications about things that you don't care about anymore. So you have to use those in a very targeted and limited way. And with that, that's the end of my presentation. There's some more details on our website and we're just releasing an open access book later on this month, which kind of details some of the technologies that we used here and also some of the use cases and pilots in further detail. And just to give credit to the Waternomics project, which was funded by the European Commission and the Sense project that was funded by Enterprise Ireland and also the Insight Centre is funded by Science Foundation Ireland as well. And with that, thank you very much. Thank you, Edward. It was a fascinating talk and I always love when speakers interact with the crowd, especially in a kind of name and shaming. I didn't do that, did I? I definitely feel guilty about driving here now. Yeah, that's fascinating. Just a quick question. Just you mentioned these are all these were pilot studies and I'm just wondering what is the vision for the future? Rolling this out into kind of an out. So we see it in our everyday interactions, I suppose, in life. Yeah, absolutely. So one of the really positive outcomes that we had from the Waternomics project is that the company that runs the airport in Milan also has a second airport that was newly built in Alpenza. So they're currently deploying the system in their second airport. And what we've had then is a number of local authorities in Ireland interested in deploying the system on a pilot stage here as well. So there's interest in trying to push it forward and to get more people involved. Great. OK, well, we'll thank Edward again. Cheers, thank you.