GoGriffith
Helping users regain confidence in their safety during the Covid-19 pandemic by allowing them to determine risk prior to visiting Griffith Park.
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The Covid-19 Pandemic hit the world without warning; We all had to change our daily routines, we all had our mental health challenged, and feeling safe became the most important thing to all of us. During this design sprint, our team noticed that going outside played a major role in our users new routines. Now users feared for their safety and need stronger tools to make more informed choices. This is why we chose Griffith Park to design a solution that allows user to determine crowd risk factors prior to visiting.
In this 3 month collaboration with Jennifer Morehead, Joey Fonacier, and Ruben Montanez I conducted user research in the form of survey creation, data interpretation, and user testing. Additionally, I identified our user pain points via user journeys and competative analysis, and further proved our concept by prototyping an example in Google Teachable Machine. Finally, I collaborated with my team on prototyping, by following our style guide to develop wireframes and a high fidelity mock up.
While Griffith Park provides a much needed outlet for Los Angeles locals during the Covid-19 pandemic, there are gaps in the parks pandemic preparations.
Based on our users needs, we determined that users want the power to choose their own level of Covid-19 risk when deciding to enter public spaces.
We saw that users who are working from home or continue to care for family still have busy schedules and would like to be able to plan visits to Griffith Park and know details about the crowd density in order to better plan.
Our users would like to know if the crowd at Griffith Park is mask compliant prior to their visit in order to determine how comfortable they are before they begin their trip.
In a follow up conversation with our users we determined that the power of choice is what they appreciated most with this concept. While high risk visitors or those visiting the park with family tend to be the most cautious, younger audiences are willing to risk a higher crowd density. The power of choice and the ability to plan is what speaks most to our local visitors.
Before we began designing, we took a better look at the types of users that would want crowd density data, and looked into their existing behaviors. We conducted user interviews, and defined two major archetypes by focusing on identifying their feelings about safety during the pandemic as well as their need for outdoor activity.
Age: 42
Location: Burbank
Family: Married, with children
During quarantine Monica noticed the importance of going outside with her children. If they don't get their play time in, her kids become restless and nap time becomes non- existent. Monika cares for her family safety and refuses to take them into large crowds of unmasked people.
Age: 26
Location: West Hollywood
Family: Single
Brock used to have a consistent routine, he would go to work, go to the gym, and go home. However, the pandemic had a different plan, and now he typically finds himself stuck at home in front of his laptop for at least 8 hours a day. His need for outdoor activity comes from his need to get out of the house and maintain positive mental clarity. He is not as nervous about crowds since it is typically easy for him to avoid them, but he would like to know that the people near him are taking the mask mandate seriously.
In looking at existing crowd density technologies, we found that most of these applications only provide information for businesses, and typically they do not provide exact current information. Due to this turned to emerging technology to find a way to collect crowd density and mask wearing data.
Upon determining the type of data our users wanted from this application, we began to test different data visualization types to learn which one our users responded best to. We tested live video data, a point density map, and a heat map format.
Our design continued to go through several iterations in order to find the most user friendly layout, and show data in the most concise way, this early iteration was an attempt to get all relevant data implemented into one prototype.
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Our final low fidelity iteration combined the point density map with color coordination to communicate crowd density to users. The user is able to see how busy select areas of the park are, and learn information about mask wearing in the area as well as view the parks camera view. Users are also able to pin a location to be able to get notified when areas of the park are too crowded for their comfort.
Users can see select areas in the park and their crowd density communicated via color
Clicking on a specific location allows users a stronger overview of covid conditions in that area
Users can watch a specific area and get up to date alerts about that areas crowd density trends
Once an area is pinned users can share that pin with friends
Sharing pins allows users to make Covid safe plans with friends and family
Here a new icon represents the Griffith Park Observatory as a pinned area
Users get a push notification on their phone when relevant crowd density changes happen
Users can see a visual change when a pinned area becomes high density
Pinned high density areas show up and options are provided for users to quickly update plans
Users can easily remove pins they no longer need
Users don't want to be bombarded with notifications about density changes, so they need to be in change of how notifications are set.
Users need to be aware of where the density information is gathered when they visit the park, and need to know that their privacy is safe.
Users plan their trip to Griffith park differently, some need a long term plan and some need a short term.
A mobile application the provides crowd density data and monitors crowd density at Griffith Park.
This is where user choice becomes extremely important, not all users need the same thing so a variety of choices better allows us to impact a greater variety of lifestyles. However, too much choice can overwhelm users so it is important for designers to strike a perfect balence.
Most of us were not ready to be so heavily impacted by Covid-19 when world wide shut downs began. As designers we had to quickly pivot to being able to design for such impactful lifestyle changes and that is a skill we will be able to use for the rest of our careers.
Interested in checking out more of my case studies? Go ahead:
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