June 30, 2026
Wall-E, but make it asbestos
I built a mmWave material classification radar
Student tries to build a wall-sniffing asbestos detector and the comments go wild
TLDR: An engineering grad built a prototype radar to identify dangerous wall materials like asbestos, hoping to make testing cheaper and easier. In the comments, readers were equal parts impressed, nostalgic, and obsessed with the honest failure story, with many saying the hard-won lessons were the real treasure.
A recent engineering grad dropped a wild build story about spending six brutal months making a small radar that could help spot dangerous wall materials like asbestos without tearing buildings apart, and the comment section instantly turned into a support group slash geek reunion. The big mood? Respect. People were deeply impressed that this wasn’t just another app or AI wrapper, but a real physical device aimed at a very real health problem. One commenter basically saluted the pain, saying they’d built something similar for a school project and knew exactly how hard it is to even get started. Another piled on with an even more cinematic flex: they’d worked on radar that could see pipes in walls and even spot concealed weapons from far away, which gave the whole thread a delicious “okay, now we’re all in a spy movie” energy.
The strongest opinion in the room was that the project’s failure to fully launch because of funding actually made the post more valuable, not less. A commenter flat-out said we learn more from failure than success, and called the lessons at the end “gold,” which is basically Hacker News poetry. There wasn’t much fighting, but there was one tiny drama beat: the project got so much attention that someone complained it was “hugged to death,” internet-speak for “everyone clicked at once and broke it.” Even that felt affectionate. So while the inventor brought the science, the community delivered the real plot twist: people are starving for honest, messy, ambitious hardware stories.
Key Points
- •The article documents a six-month project to build a mmWave radar prototype for classifying materials, with asbestos detection as the motivating use case.
- •The author used off-the-shelf development hardware, specifically a Texas Instruments IWRL6432 BOOST board and an ESP32 dev kit, to accelerate prototyping.
- •A custom test bench was built to measure the electromagnetic response of different material samples during development.
- •The final classification approach combined Capon beamforming with a neural network to identify material surfaces under stated layer assumptions.
- •The article explains an FMCW radar DSP chain including chirp characterization, mixing to form a beat signal, range FFT for depth estimation, and MVDR/Capon beamforming for angle-of-arrival resolution.