Mexico City's Atlas of Prevention
Through a partnership between Sarah Williams and Lorena Bello Gomez of MIT and the Mexico City government, we developed an interactive web-based platform for residents of Mexico City to learn how to protect themselves from a range of risks.
Users first drag Ólin, the mascot for civil protection, to a locations of interest such as their home or workplace. Within a second, the app retrieves nearby incidents and risk assessments from three different APIs maintained by the City. Icons representing a range of incidents, from COVID-19 cases to gas leaks, appear where they occurred. Clicking on Ólin opens a pop-up with a graph showing the assessed risk levels. On the bottom right is a deck of cards representing each risk that automatically sorts according to the number of nearby incidents.
After learning about the most imminent threats, users navigate to a second page to discover the most relevant preventive measures. The menus on the left allow the user to set filters according to their budget, situation and preferences. The cards on the right automatically filter and sort accordingly.
The front of each card consists of an image, which could be a graphic that the City uses on other social media platforms, a title and tags indicating the cost, type and scale at which the solution applies. Clicking on a card flips it to reveal a description and a link to further information.
In the gif, the user selects the risk of gas leaks and indicates the she has a large stationary tank in her house. She then filters for the most affordable, ‘$’, solutions in the “Best Practices” category. One of the cards that shows Ólin holding a candle near the tank. Clicking on the card reveals text explaining the importance of keeping flames atleast 3 meters away from gas tanks to avoid explosions, which occur frequently in Mexico City.
While we demonstrated the platform with risks related to flooding, gas leaks and COVID-19, non-technical professionals can easily expand the platform to include other risks or preventive measures.
Supervised by Loreno Bello Gomez and Sarah Williams.
Initially developed in collaboration with Lenna Johnsen.