Episode 18: Dr. Fabio Duarte and Dr. Simone Mora, from MIT Senseable City Lab, talks about his research projects on data gathering in informal settlements

Welcome everybody to the 18th episode of the Humanitarian Engineering Podcast. I'm Alberto Martinetti today with you. For this episode we have a special guest from MIT, Dr. Fabio Duarte, Associate Director of the Sensible City Lab and Dr. Simone Mora, a research scientist at the Sensible City Lab as well. Welcome Fabio. Welcome Simone. Thank you for having us. Thank you. Pleasure to be here. Well, let's start with with a personal introduction. Can you tell us something about yourself, please? So my name is Fabio Duarte. I'm from Brazil. My background is urban planning and I have been working with technology and cities for many years since I joined the Sensible City Lab. Thank you very much Fabio. And Simone? I'm Simone Mora, I'm originally from Italy. I did study and worked in Italy, Norway and the U.S. and have a background in computer science. Okay. Thank you very much. Let's talk about a bit your current job. Let's maybe start with you Fabio. So at the lab we have more or less 50 people distributed in four labs. So the lab is based in Boston at MIT. And as part of MIT we have this combination of computer scientists, mathematicians, but also designers, urban planners, all working together in the same lab. And more recently we start to have some smaller labs around the world. We have one in Dubai, another one in Rio, in Brazil, and the biggest one here in the Netherlands in Amsterdam with the AMS Institute. So what I do in my daily life is mainly to coordinate all these researchers working in different parts of the world in particular projects. Very interesting, thanks. As you know, as a humanitarian engineering group we work a lot with communities. And it seems that definitely your work that you're doing in a sensible city lab is also very oriented to the community at the moment. Yes. And you Simone. Yes, I work in projects that deal with sensors or sensing tools and also supervise younger researchers. And in general we try to come up with a low-cost solution to capture data about cities. A lot of this data usually refers to the physical environment, especially for example air quality, heat and noise. And that's what I do. Okay, thank you very much. I would like to maybe discuss with you Fabio and Simone if you have some concrete example about a solution that the students are working on, maybe link it to your project and if there is also a specific link more to the, let's say, to the humanitarian engineering part. So with the community and the SOF community specifically. Yeah. One thing that I like of what the lab has been doing for 15 years more or less now is that every spring we teach a class called the "sensible class" we call. And then we select two cities that partner with the lab and we develop a project for the city with some professionals from the city but also with MIT students. It's a semester long class. We go to the city and some cities, look, my problem is about how technology is influencing mobility. Other times it's about air pollution. So what I like about this engagement that I think is closer to communities is that we don't do only research projects at the lab with researchers but also we try to engage students because eventually when they graduate they will be out in the world and knowing which projects and problems the cities actually have will be very beneficial to them. Yeah, indeed. It seems that the community becomes the playground for your research and your students and how to improve their well-being. Yeah, exactly. And Simone, for you. Yes, alongside what Fabi just said, a lot of the activity of the lab including the class we teach revolves around the use of tools and making some cases data collection tools and tools that we develop at the lab for our self, for our project, but in many cases eventually we release the tool as open source. I can give you an example of a project we recently launched called the Octopus. In this case, the tool that we've developed is a maker-friendly platform so we look at the maker communities and the tool allows basically to collect a variety of environmental parameters. But the cool thing is that all devices can be 3D printed in a maker space and we also looked at the usability and sustainability of the project by allowing makers to bring their own electronics, in particular Arduino boards, so they can customize the platform we're using components that MITA really have around. Can you give us maybe an example of a product that they are developing? Yes, we are soon doing a pilot project in a favela in Rio de Janeiro and in this case we're going to work with the local community to deploy a sensor to measure heat and we're particularly interested in looking at how the informal environment and the informal settings compares to the formal city in terms of exposure to heat. Can I ask you one question about this project? How is the involvement of the communities exactly that will be organized? As Fabio mentioned, we have labs around the world and one of our recently established lab is in Rio de Janeiro so we're lucky that we have local researchers there that allow us to interact with the community that are in charge of today's collaboration with the local community. Obviously, this is done within a network of different organizations in Rio de Janeiro including a maker space that will physically fabricate the device and community member from favela, which is Marge, that will help us deploying and collecting data. So it's a tight network that involves the lab in Boston but also our satellite lab in our global lab in Rio as well as local collaborators. I see, I ask you that because one of the, let's say, usual question is how the community will benefit of the work of Azen academia and the researcher as well. But I think in this case what is also interesting is that we are engaging, we are hiring local researchers from the community to work for two months in building the devices, learning how to calibrate the device, collecting the data and then eventually they will release their own report. So I think for us it's also interesting that we're not only having community members collecting data but they will be working with us through the whole project and they have the completely freedom to do whatever they want with the data. So I think this is also for us quite important in this project because it's a very sensitive topic when we go to informal settlements and there is a long history of colonization and exploitation etc. So how to make sure that the project is their project as is ours. So it's not only okay, oh this is our project and then we have some help from the community. No. This is equal, equally important MIT and MARE project. Yeah, because one of, of course, of the recurrent question is how can we make sure that also they own the project, right? So how it will be the ownership after the, for example, the project ends, as we usually happen in academia, right, after some years, some months, the project ends and then what? I have a question regarding this topic that might be interesting in specifically related to the work that you do at your lab. How do you see the difference between project with underserved communities and project with, let's say, they don't have scarce resources or limited access to normal resources? Do you see any difference when you, when you work with them? I think I see two ways of, of dealing with that. Some of them, for instance, we did a very interesting project with some colleagues from Brown University about water, water contamination in one part of Mississippi in the United States. And then we did all the analysis of the, the, the, the alerts when okay, you cannot drink this water, how this has impact children at school. In this case, after we finished the project, it more or less was abandoned. We could not see any follow-up. On the other hand, this project in here, in this particular favela, the communities so well organized that actually even the project started from there. It was not us trying to do something with them, but we were there talking to the community by, I don't know, I don't even remember the topic. It was something else. And then some guy from the community said, Oh, I heard that you have the sensor that measure our quality. We are doing a deployment here with only two devices. And this trigger already. Okay. Oh, in this case, we can do something together. So I think the difference is not also, we cannot, I think, generalize underserved communities, et cetera. Because some of them, they are not well organized, but some of them, they are so well organized that we see a follow-up happening very quickly. Yeah. I think what you mentioned, it's, it's extremely important. So the starting point actually of a project with a underserved community engineering, humanitarian engineering has to be the community. We cannot come there and discuss, Oh, this is the problem you have. Let's find a solution. That is, we already see that happening so many times in the past, right? So that definitely what you said is absolutely true. From your side, Simone, do you see any, any, maybe any difference in your daily work? Yeah. I totally agree. On one side, from a technological point of view, the challenge is a challenge to develop something in Boston where you have kind of huge infrastructure and that thing also needs to work in a place that we assume has no infrastructure. And also I think what is important and maybe sometimes a little bit underestimated, especially in academia in talking, for example, in the research field of citizen science, if many of those projects, citizen are actually not scientists, are more data collector or more, they do tasks, but sometimes they don't know why they're doing those tasks. So I think what we strive to do is, as Fabio says, to involve the community to allow them to give tools that will allow them some freedom of exploration and also to teach them the basics that they need in order to operate the tools and also to understand the data. And this is what we do, for example, with the processes that allow them to calibrate the data. Because, again, another area that we want to address is also the quality of the data and the robustness of the data that we capture, which is important for actually doing science and writing papers and doing research. Yeah, absolutely. Now, I think I'm curious about one topic that is not on the script, actually. So you will be surprised, but it's just been triggered by our conversation, but in our university at the moment we are talking, especially in the Netherlands, about open science and how to make sure that projects are carried out within the studio with communities. They somehow fall into the box of open science that we can share most as we can in terms of paper and data. I was wondering to see if you have any idea about how to reuse maybe some experience, some data that you have collected in some project or with some communities, and transfer the results in other settings. But was not on the script, so I can imagine we can skip it. So when we talk about open science, I think one thing that we have to take into account is that different communities in different countries, but also within the same country, different people, they value data differently. So it's not a matter of, okay, oh, this is open science, all data should be distributed because data is very sensitive and also is culturally sensitive. And we have a project that we focus specifically on that. It's called Dataslots, and in this project we look at, try to understand what are the forces that drive acceptance of certain solutions, and with solutions we think about an application, a service, or a device, solutions that are very heavy on the data they collect and the data they process. And this project, we develop the tools that allow communities, allow citizens to understand what type of data is used and is processed, either sometimes also without them to know, and how this data is used to give them some benefits. And by allowing them playing a car game, which somehow resemble a slot machine, that's why Dataslot is the name, we empower them to make informed decisions on the acceptance, or their willingness to accept or reject certain solutions. And we've done, we've played the game across more than 50 countries, both in a physical and digital form. We've released the results of this study a few weeks ago. What was very, very interesting looking into the data is how different communities and different also geographical areas core differently when it comes to their perceived privacy risks and perceived values of the data collected. Yeah, thanks, because that is quite a recurrent discussion and talk that usually we have, what to do with the privacy data of the communities, also because in some case, for example, this might be in danger, the community even, if, for example, a political situation is not stable, or if we are talking about refugees or migrants are moving in different geographical regions. And another aspect that, for instance, the data itself, it's only part of the problem if you don't have the technology to process the data, or give an example, if we get lots of laser scanning data, it's very heavy, so we can go to a community and say, look, we are here collecting all these images from the community, laser scanning our community, and I'm giving you all this data, what for, they don't have any resources to do anything to use them. So I think the open science idea should not, needs to be beyond open data, right? Yeah, absolutely. Okay, look, it's open science. So everybody needs to have access to the same technology, to the same knowledge to process the data, the same skills to analyze the data, but also to know what the benefit you can have out of that, for instance, a company can have all this data and launch a product that will sell to ourselves. This is good for them, but not necessarily good for me, who is a scientist, a government can design a policy that might actually hinder my own well-being. So I think there is the open science needs to have this, all these components, data is important, technology is important, knowledge, and finally, what power do you have to use this data for? Absolutely. Thank you very much both for this reflection on the open science part. Let's move now to the next part of our episode, and the first questions. Okay, we have now prepared four first questions, which you can answer hopefully in one or two short sentences. I would like to start maybe with you Fabian. What do you think that humanitarian engineering is relevant? Because more than half of the world live in sub-ideal situation, and engineering should not be focusing only on Dubai-like cities. Bold statement. Thanks. And Simone. Yes, because we live in a world that changes very fast, and sometimes formal institution and organization, they're not fast enough to react to these changes. So I think our role is in tools, methods that can be adopted by local communities. Second question. What is the most urgent topic to be addressed by humanitarian engineering students and professionals in your experience? Fabio. I would go for informal settlements, and the reason is the same. We are dangering the future of billions of people, if we focus, if our city model is Singapore. There is only one Singapore. Absolutely. Yeah. I think addressing the climate crisis, in general climate change, and developing solutions that allow especially vulnerable relations to be able to mitigate these effects. Yeah, because it's also important to underline the usually climate change impacts most the communities, such as underserved communities and communities that are not access to basic needs. Third question. How can a humanitarian engineer make the most impact in your experience? Sometimes I think it's focusing on old technologies that have worked in developed countries long time ago, and then simply the engineering domain forgets about that. One very simple example is the nets to protect against malaria. So we put so much money, billions of dollars in whatever new technology. And look, if we get a fraction of that and bring nets to Africa, we would be saving so many million lives. With sometimes with simple and for good solutions as well. Yeah. Simone. I totally agree and to compliment that I think especially design practices have done a lot of steps moving toward user-centered design. And this idea of trying to use technology to augment existing solutions rather than trying to fully replace them is key to achieve kind of large scale adoption of those solutions. Last question for both of you. I think one aspect that makes humanitarian engineering different from other engineering disciplines, for example, mechanical engineer or civil engineer. I think my question is very simple. All the other engineering, they ask the question what? What I'm doing here. And humanitarian study why I'm doing that. So I think bringing the why back to the engineering domain is critical. So the why is the driven factor for a humanitarian engineer. Yeah. I fully agree with that. Thank you Simone. Yeah. I would totally agree. And I think also because the difference in the methodologies because in many traditional disciplines you can run lab settings. You can have you control for many different variables. You come up with your report as you can repeat tests as many times as you want. When it comes to humanitarian engineering, the city or the communities are indeed your lab. And that's usually a very messy lab. There are a lot of things you cannot control. There are a lot of things that aren't expected. A lot of things that are tightly related with the culture, with the people, the way you approach with community. And this makes things or engineering way harder than many of the traditional disciplines. At least when it comes to arranging experiment and collecting data. Okay. Thank you very much Fabio and Simone. We can also close the first question section. Today we had the pleasure to talk with Fabio and Simone from the Sensible City Lab at MIT. We discussed some of the relevant project with underserved communities. They also gave us a very interesting vision on how a humanitarian engineer can contribute to help underserved communities. Fabio and Simone, I really would like to thank you very much to come to the University of Twente and also to our podcast. It's been a real pleasure to host you. Thank you. Fabio. Thank you very much. It was a pleasure. The Humanitarian Engineering Podcast.