A 15-year-old Florida teen has engineered a low-cost, AI-powered CubeSat that detects flooding in real time — a breakthrough that could transform disaster response and save lives.
High school sophomore Abigail Merchant has turned her passion for technology into a life-saving innovation: a small, AI-powered CubeSat designed to detect floods in real time. Living in Orlando, Florida — a state prone to frequent flooding due to its low elevation — Merchant recognized the urgent need for faster, more accurate disaster response. Her solution, developed with a team of peers and now refined through internships at MIT and Accenture, could redefine how communities respond to catastrophic flooding.
Climate change is exacerbating the problem. Warmer air holds more moisture, leading to heavier rainfall and more frequent flooding, according to the U.S. Environmental Protection Agency. Existing satellite systems, while powerful, suffer from slow data transmission and delays in response — often taking hours to deliver critical information to emergency responders. Merchant’s CubeSat, built for under $310 and weighing just 495 grams, captures high-resolution images every two minutes and uses a convolutional neural network to detect flooding, assess infrastructure damage, and track survivors.
Why This Matters for the Future of Disaster Response
Traditional flood monitoring relies on large, expensive satellites that transmit data slowly. Merchant’s device, by contrast, operates on a constellation of small, standardized CubeSats — each a 10-by-10-by-10-centimeter unit — that can be manufactured using off-the-shelf components. This scalability means the technology can be deployed rapidly and affordably, even in regions lacking infrastructure. The CubeSat transmits up to 1,500 images daily and alerts emergency responders via SMS or email when flooding is detected — a speed that could mean the difference between life and death.
“While many existing systems operate on multihour cycles, the CubeSat captures high-resolution images every 2 minutes,” Merchant says. “The system can then trigger alerts that are delivered to first responders via SMS or email.”
From Science Fair to Satellite
Merchant’s journey began in 2023, when she presented a robotic arm project at an IEEE Orlando Section meeting. Inspired by her grandmother’s mobility challenges, she used an electroencephalogram and Bluetooth to control the device — a project that introduced her to IEEE’s global network of engineers and researchers. “IEEE quickly became a community that has shaped my understanding of what engineering can accomplish,” she says.
Her breakthrough came during MIT’s Beaver Works Build a CubeSat Challenge, where she and her team — the Satellite Sentinels — developed a CubeSat powered by a convolutional neural network (CNN) to identify heavily impacted flood zones. Merchant led the mission’s design and simulation efforts, configuring hardware and developing autonomous software. The device, housed in a clear plastic cube, used a Raspberry Pi, multiple sensors, and a camera to collect images. During ground testing, it transmitted images via Bluetooth to a laptop — a method that proved effective in a bathroom but not in orbit.
Out of 30 teams, the Satellite Sentinels placed third. But Merchant’s ambition didn’t stop there. She now works remotely for Accenture’s CubeSat launch team, refining her design for real-world deployment. One of her key challenges was training the CNN to recognize flooding under variable conditions — a problem she solved by teaching the algorithm to identify colors in individual pixels. Another was replacing Bluetooth with SubMiniature Version A (SMA) antennas, which can handle the long-range, high-bandwidth communication needed for satellites orbiting 700 kilometers above Earth.
Scaling Up: From Prototype to Product
Merchant’s work is now being supported by Accenture, where she serves as a payload owner and designer. Her team is working to transition from prototype to functional product, addressing the limitations of her MIT project. “The development process has been one of the most formative experiences of my career so far,” she says. “Working through the payload design and validation has given me so much experience, especially for my age.”
Her payload is expected to be launched early next year. “I’m really excited to learn from engineers and researchers who are working at the cutting edge of the field,” she says. “Being one of the youngest people in the lab is daunting, but I’m determined to contribute.”
Engineering for the Future: MIT and Beyond
Merchant is also an intern at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the school’s largest interdisciplinary lab. Led by IEEE Fellow Daniela Rus, recipient of the 2025 IEEE Edison Medal, CSAIL is at the forefront of AI and robotics research. Merchant’s work there focuses on cognitive cartography — a method for structuring complex information into semantic maps that reveal how ideas and concepts relate to one another. She uses embedding models, a type of machine learning that converts information into numerical representations, to help AI products understand how ideas connect — not just as isolated data points.
“I’m hoping to attend MIT or Stanford,” she says. “The goal is to build systems that don’t just respond to disasters, but predict them — and that’s what this CubeSat is designed to do.”
The Vision: IEEE and a Future as President
Merchant’s journey is deeply tied to IEEE, the global professional organization for engineers and technologists. Introduced to IEEE by Joe Jusai, former finance chair of the IEEE Orlando Section, she credits the organization with turning engineering from a dream into reality. “IEEE is a foundational part of my growth as a young researcher,” she says. “It turned engineering from my dream to reality.”
She was inspired by Kathleen Kramer, IEEE’s president-elect, whom she met at a local IEEE event before Kramer’s election. “After she was elected, I realized that I would love to become the president of IEEE someday,” Merchant says. “I hope one day that I can step into the same shoes as her and continue to help IEEE the same way it helped me.”
Her vision is not just to build better technology — but to build a more equitable, responsive, and intelligent future for disaster response. “I want to make sure that when people are in danger, they’re not left waiting for help,” she says. “I want to make sure that when a flood hits, the response is faster, smarter, and more effective — because lives depend on it.”
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