Had chosen the SDGs and COVID-19 challenge, we choose to focus on the 11th SDGs goal, which is to make cities inclusive, safe, resilient and sustainable. Our project, Uspot, aims to impact the way people are dealing with coronavirus crisis around the world, by turning the necessity of leaving their houses more smartly and safely with data information about how crowded are the places they wanna go and determining contamination rates. We though about creating a system that crosses Flowminder's* mobile phone network data with NASA's data related to high-density urban areas (such as urban population distribution, country slum data, land consumption).
By matching these information, we can create a visually accessible map that informs which areas and places are more crowded at the moment. Thinking further, we can make cities more inclusive by recommending users to give preference for small commerce and local entrepreneurs, impacting positively in the local economy.
Besides that, health institutions could use this platform as a tool for preventing and controlling new epidemies.
The UN 2030 Agenda SDGs are not only milestones set by and for world leaders but they do are goals everyone can do something about it, what makes them all quite inspirational, especially for us in team Arquitetonautas. The terrible effects that COVID-19 pandemic had over urban areas across the world motivated us to work with the SDG 11. Following an adapted design method - with design sprint, double diamond and Panic Lobster process elements, we started studying and classifying pandemic-related urban problems, then we choosed to deal with how social isolation is difficult to observe in high-density urban areas. We brainstormed up to 28 possible solutions, analyzed and narrowed them down to the after developed one. At first, we thought about developing a hardware device to collect data, but then we realized the essential information is already powered by NASA Earth Observation data (such as population distribution, land consumption and slum country data), mobile network data provided by NGO Flowminder and contamination risk data complied by Juntos contra o COVID initiative. As a result, our application challenge is to data crossing all this information, in real-time, to provide a clear and accessible level of crowedness in a heat map format over an map-searching engine like,Google Maps API . Finally instructing every user where it's more or less crowed, more or less likely to get contaminated. In order to prototype Uspot, we first defined personas, analyzed their costumer journeys and designed a storyboard, Secondly, we developed smartphone mockups, with a basic but good-to-test user interface. We then improved some features and attributions over feedbacks received.
NASA/UN:
- Urban population distribution.
- Country Slum data.
- Land consumption.
- Datasets in Support of United Nations Sustainable Development Goals
Flowminder:
- Mobile phone network data.
- Illness's spreed velocity.