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Ever since mid-2022, news has been surfacing about a terrible mold contamination issue at U.S. Army barracks locations around the United States, with one of the highest-profile areas being at Fort Liberty (F.K.A. Fort Bragg). This issue is so severe that numerous soldiers have been hospitalized as a result of mold contamination, making it the subject of widespread media scrutiny and congressional investigations.
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In early November 2022, I was approached by SPC. Salem Ezz with the U.S. Army 3rd Infantry Division to work with him and his team on developing a software-based solution to the mold contamination crisis plaguing the U.S. Army. SPC. Ezz’s team would consist of him as the lead engineer, myself as the lead interface designer, Lieutenant Christopher Aliperti as the lead researcher, as well as the project’s non-profit collaborator, CMi2—which would provide essential circuitry for the sensors and 3D print the housings for real-world use.
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Though initially, we called this project the “Marne Mold Tracker,” over time, its official name within the U.S. Army has evolved to becoming the Marne Mold Contamination Administration Tool, or MCAT—because you know how much the military loves its acronyms.
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This tool was conceived to fulfill a specific use case and address both a primary and secondary problem that the U.S. Army wanted to tackle. The primary problem had to do with not knowing which building locations were already contaminated, making it difficult to distribute safety resources to those locations promptly. Additionally, the secondary problem had to do with not knowing which building locations were at risk of being contaminated, necessitating preventative measures.
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As a result, the Marne Mold Tracker is primarily a reporting solution, followed by a tracking solution. The tracking solution relies on a series of proprietary sensors connected and contained in a 3D printed housing, relaying real-time temperature and humidity information back to a software suite managed by a noncommissioned officer or internal safety staff. The reporting solution is designed to work in concert with the tracking solution and relies on a human operator to click a button on the scanner hub to report if they have seen mold contamination inside their room.
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On the other end, the non-commissioned officer operating the app and monitoring virtual hub nodes can see that a sensor hub in a particular area has a user-submitted report of contamination on corresponding sensors. Additionally, he or she will be able to see rooms that are at risk of contamination as a result of their temperature profile.
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As the UI designer, my work was fairly straightforward but gradually evolved over time. Initially, it started as merely translating the team’s low-fidelity wireframe into a high-fidelity prototype. However, it eventually grew into suggesting new feature sets and proposing usability improvements. Consequently, what began as a fairly basic “stoplight-style” design ethos evolved into a more detailed, nuanced piece of software that could accommodate multiple users and scale infinitely to meet the volumetric requirements for the amount of sensors needed by a particular end-user.
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Addressing volume and finding visually efficient ways of accommodating it was the primary challenge of the project. A soldier may be able to monitor their room with only five sensors, but an NCO would need to manage an entire barracks, which could have 500 sensors. Simultaneously, an internal health and safety officer may need to manage the entire installation, which has 50,000 sensors.
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For this reason, each design change revolved around realizing more efficient ways of addressing volume and intelligently utilizing space. This story is largely told through the gradual evolution of our sensor design.
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Initially, my V1 design of the MCAT sensor readout was simple—supporting basic temperature, an undetailed line chart, and a color-coordinated backer in a single-readout format. These single-readout displays would be stacked in 5 or 6 and laid out as consecutive columns next to one another within a white box. A top-level sensor for the entire building would sit next to the box, providing a readout of the temperature averages across each room inside it.
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Due to volume issues in the V1 design, the V2 design of the MCAT sensor readout built on this philosophy. Instead of a readout corresponding to a sensor in the room, the readout corresponded to the room temperature average. Underneath the room temperature average are color-coordinated “lights” that illuminate based on the status of the sensor they correspond to, along with a steel “tile” area listing each sensor in the room, its corresponding “light,” and the temperature and humidity profile for the sensors in that room. Additionally, to increase the readout’s volume potential, I allowed each hub to support “pages” of sensors instead of just five.
We also added in a formalized wizard-style menu to help users onboard new hardware into the system. .
The V2.5 and V3 iterations of the MCAT sensor readout involved making our design more compact while maximizing its volume potential. For the V2.5 design–which is the closest thing to the “current” design that the team is working towards–I made the sensor readout more compact by making the tile area retractable.
To address complexities regarding the “lights” that appear on the hub readout, I added another box to support a number if there are more than six sensors attached to a hub. The number tells the user how many more sensors there are on the hub, beyond what can be displayed by top-level stoplights on the hub view.
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At the same time, important changes were made to the app itself to help create software that people could actually use. Firstly, we removed the listing of buildings on the main page and replaced it with a building search. Additionally, to bring more order to the design, we allowed for the ability to have “pages” of hubs to accommodate infinite volumes of hubs without appearing cluttered. Finally, we added user functionality to the top bar.
Compared to version 2 and 2.5, version 3 takes many of the improvements from earlier iterations of the design and re-positions the building sensor so that it is above the hub readouts. While this may seem like fewer sensors due to the removal of a sensor row, these sensors are made up for with the added hub columns.
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Despite being a very young project, MCAT has rapidly become one of the darling initiatives within the U.S. Army 3rd Infantry Division, as well as the broader organization as a whole. Thanks to SPC. Ezz’ development talents, LT Aliperti’s research, and my creative expertise, MCAT has quickly caught the eye of the military’s top brass, including the General of the 82nd Airborne Division, the General of the 3rd Infantry Division, as well as the Secretary of the U.S. Army.
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Consequently, the Marne MCAT is an award-winning project, being the 2023 winner of U.S. Special Operations Command’s (SOCOM) Dragons Lair innovation award, earned by taking part in SOCOM’s Dragon’s Lair innovation competition. This 80-project competition takes place in March and involves various special operations branches within the U.S. Military. Notably, the 3rd Infantry Division is NOT special operations, which reflects the regard the U.S. Army has for this particular project.
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As a result of winning Dragons Lair 2023, SPC. Ezz and LT. Aliperti were also awarded the U.S. Army’s Meritorious Service Commendation, the highest peacetime honor a soldier can receive while enlisted.
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Finally, MCAT’s success within the U.S. Military has led to the subsequent creation of the Marne Innovation Center in May 2023. This center serves as the U.S. Army 3rd Infantry Division’s incubator for future hardware and software projects, as well as the development of enlisted coders and engineers. Though the innovation center starts primarily as a hardware location, future expansions of the Marne Innovation Center will include a software factory.
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The Marne MCAT is still actively in production, with the current phase focusing primarily on developing and testing the necessary hardware components that the final product relies on to be fully realized. The Marne Innovation Center’s broader focus on hardware has led to a pause in software development, keeping the broader app and all its iterations unreleased to the public. Nevertheless, I have decided to include this project in my portfolio because it represents some of my most significant work—not just in scope, but in terms of application and the potential impact on many people.
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Although this project was done mostly in my spare time, I believe it is not the end of my foray into design work for the U.S. Military. Looking forward, members of the Marne Innovation Center have expressed an interest in continuing to work with me on other projects in the future. This includes not only UI/UX work directly related to MCAT but also bringing my UI/UX talents to other application projects and potentially even some online properties.
United States Army, 3rd Infantry Division (MARNE)
Cliff Brett, SPC. Salem Ezz., LT1 Chris Aliperti
UI Design for Applications
Adobe XD
Dragons Lair Innovation Award (2023), Meritorious Service Commendation (2023 - SPC. Ezz & LT1 Aliperti)
August 7, 2023
UI/UX design
Application Design, Apps, Army, UI/UX
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