Overview
In response to Hurricane Katrina, I led a fundraiser selling "fancy telescopes" (construction paper rolled up with stickers and glitter on them) at my first-grade parent-teacher conferences. We raised $108, which I was very proud of at the time.
Years later, despite an improved technological landscape and the $108, the Hurricane Response process is not significantly more efficient.
When hurricanes come, people who need evacuation struggle to be located and rescued, and those who need shelter find themselves being turned away due to poor communication.
From outside research, interviews with crisis management personnel, and discussions with engineers, we designed Hurri Safe to tackle the critical communication challenge.
Hurri Safe is a module that creates a local network to enable communication from officials to those left on the ground and maps heat created by people to allow officials to identify the locations of those left behind. Unlike the current system, this enables dynamic decisions and increases the rescue window to include the day's low-visibility times.
Because hurricane rescue is such a time-sensitive and pressing issue, we hypothesize that the increased communication enabled by Hurri Safe modules would lead to more efficient hurricane rescue.
This project yielded the consept video at the bottom!
Team
Ekta Verma (MHCI 2020)
Ketaki Rao (MHCI 2020)
Megan Parisi (MHCI 2020)
My Role
Designer — I edited video (including all audio work), wrote and found clips for the intro, designed all animations in the walkthrough, created the logo and served as narrator. Doing design work on this project enabled me to hone my storytelling abilities.
Researcher — I acquired an interview with a person who works with Hurricane Response to ensure that our suggestions were reasonable and to gather more information and led research on scanning types to discover the info-red sensor. This process was the first time I considered physical requirements for an IoT design, which opened my eyes to more design possibilities for the future. Moreover, the more extensive contextual and high-stakes nature of this problem challenged me to focus on accuracy and systems thinking as I moved into design.
Teammate — I used my knowledge of video production to set accurate achievable timelines and delegate work.
Challenge
Hurricane rescue is currently dangerously inefficient, with many left behind and left confused about where their appropriate shelter was. This mismanagement of rescue resources has been devastating to communities and will continue until the system is changed.
With this project, we tried to answer the question of:
How might we make hurricane rescue more efficient with technology?
Findings
Our research uncovered that this pain's primary root is the inability to communicate to those who need help and are providing it, as hurricanes take out natural power lines. In addition to the initial wind, strong storm surges, dictate that any feasible solution be able to withstand strong winds.
There are 2 types of systems with communications failures, ones that address stuck people, and ones that address active shelter seekers.
Stuck people struggle to contact those who can rescue them and vice versa.
"We can't look for anyone at night because there is no light. We can only hope they are there in the morning"
So a solution must provide significant visibility
Meaning: Communication is the key issue in the mismanagement of hurricane evacuation
Anything intended to serve those post-hurricane must be strong enough to handle storm surges.
Process
Tactics Used
Interview, Storyboarding (Both Design & Film Style), Technical Research, Critique
We first narrowed our project scope down to solutions for hurricane rescue.
The process of solving this hurricane problem began with defining what problem we wanted to solve. This product was designed in response to a prompt for a society-focused solution that utilized IoT.
To discover our problem space, each group member storyboarded ideas of different problems and solutions, using a context problem solution effect structure.
I presented went from small, a retainer with sensors that could detect cavities and decay, which could potentially speed up dental work, to large, a flexible waste management system for refugee camps.
We tested these ideas among our peers. To get a sense of direction. This critique encouraged us to do focus on the solutions that were for much larger problems like the refugee crisis.
The problem with this as we would soon discover was that we were too uneducated on these subjects to create an effective solution.
In an attempt to solve this problem our group then began a heavy research phase in which we all read articles and papers about how refugee camps worked. We found the results of this search left us with a very incomplete picture of what was going on because there was no standard protocol or problems, which led us to look for a natural disaster with a standard protocol response that could have an IoT solution.
As I hope you guessed, we choose hurricanes. Specifically hurricane protocol in the US.
Second we analyzed the situation to identify relevant personas and common problems to build empathy for users.
Now, only half of my group was from the US, and none of us were from a state typically hit by hurricanes, to better understand how we could best help in a hurricane situation we began by defining personals set of key players, to identify their motives and pain points.
From our research we first noticed that there were two distinct types of victims, with needs defined by their mobility levels.
The stuck person — this person cannot leave their house due to water levels they are relying on rescue persons to find them. Their major pain points are an inability to contact rescue persons to get help, and a lack of awareness of when they are being rescued. These people are typically low-income.
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The active shelter seeker — this person has more agency, they are often able to move and drive to different shelters for help. The main problem that they face is being able to understand how to access resources available, as information about changes or capacity is usually relayed in a delayed manner to them. These people are typically low-income.
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These victim types are supported by two different support systems that have a common route: Communication
However, these have different outcomes aligned with their missions.
Stuck People Rely upon:
The official state/national rescue person — this person is trained in this area and has to access too much info. They attempt to rescue every person as quickly as possible. Their main issue is an inability to locate persons. They often have their hours reduced due to not being able to see at night.
The unofficial rescue person — recognizing prior inefficiencies in the system this person goes out of their way to rescue others. Often using jet-ski’s and relying upon word of mouth. This person is able to rescue stuck individuals one at a time. Their challenges are a lack of access to official information, an inability to see well in the dark, and lower rescue capacity compared to official personnel.
Active shelter seekers Rely upon:
The on-site shelter communications coordinators — These persons attempt to ensure that shelters are open and run smoothly. They compare attendance and capacity. Communicating to news and officials, to schedule any necessary adjustments. They struggle to communicate changes and feel guilty about providing incorrect information.
From this work, we found that the route of most problems was communication and began to consolidate our findings into requirements for a successful solution.
This communication failure after a storm seemed to be caused by power lines getting taken out, and people being physically difficult to spot, and therefore rescue when in their homes or at night.
Given this, we figured that an ideal solution should:
Give officials a map of person locations in areas that they could not see.
Create a network for communication between respondents and the stranded.
Be able to work immediately after the storm.
With these requirements we first tested to see if this would be possible, reading articles about different types of sensors, and modules to determine what could work.
We decided upon an IR camera sensor to locate persons & a beacon to build a network. These tools were chosen for their efficacy. We figure that creating a smaller lightweight body for our product would allow our product to float and be more affordable.
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With this design. we created a storyboard of a solution to test with classmates to see if it made sense.
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Response to our storyboard was overwhelmingly positive. However, the people who we were testing on did not have familiarity with this topic or experience so I reached out to someone who was more familiar with the topic.
Fourth, interviews with a subject matter expert, encouraged us to ensure the design could service true disaster conditions.
I reached out to my friend whose sister had studied emergency planning and she put us in contact with someone who deals directly with this scenario.
The key insight from this interview was that we needed to think more about deployment and the ability to not be destroyed by storm surges, a factor that we had not considered.
Given this information, we updated our criteria for an ideal solution to include a third item: heavy enough to not be disturbed by storm surges.
We then updated our design to be better equipped for storm surges.
We imagined that this would allow the Infrared Camera Sensor to work. These ideas were cross checked by a group of engineers.
For deployment, we imagined that these could be deployed using weather proof drones from helicopters, as they are storm resistant and helicopters are already being used, and have been purchased for post-hurricane recovery.
Solution
Our solution, Hurri Safe, is a tiny module dropped from planes on drones planes and will dig into the ground using its claws, which will help keep the module steady during storm surges.
Once it lands, it creates a local area network that will allow those within the area to receive alerts on their phones from officials about evacuation times, shelter directions, & capacity updates. Additionally, the infrared sensor on the module scans the area for heat, a reasonably good representation of people enabling officials to optimize their rescue routes better and increase the time when they can carry out rescues to include dark hours.
In summary, creating a local area network and scanning for heat Hurri Safe can improve the efficiency and effectiveness of all important hurricane rescue missions.