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chosun.com · picked by Petr Mišák · 33d ago

KAIST develops hidden camera detector using inexpensive LED and artificial intelligence

Source preview: KAIST develops hidden camera detector using inexpensive LED and artificial intelligence
AI summary

Researchers from South Korea's KAIST, in collaboration with partners from Singapore, developed a technique called SweepLED that enables detecting hidden cameras using a smartphone with an attached LED device costing roughly $7. The system uses artificial intelligence to analyze changes in light reflection and achieves 94% accuracy in detection within 5 seconds, unlike traditional methods that rely on users visually searching for reflective spots.

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Tip author’s note

You know camera detectors and other spy devices from movies. But now all it should take is a couple of LEDs and a smartphone, and you'll be able to check the place yourself.

AI questions & answers
How does SweepLED technology work and how does it differ from traditional camera detectors?

SweepLED uses an LED diode that continuously changes the direction of light around a suspected object. Artificial intelligence then analyzes how light changes over time—ordinary glossy surfaces show reflections that move or disappear, while cameras produce a characteristic pattern due to their internal lens structure. Traditional detectors rely on users manually searching for bright spots.

What are the accuracy and cost of this technology?

The system achieves 94% accuracy and examines each object in approximately 5 seconds. The LED device costs around $7, making it affordable for mass adoption as a smartphone accessory.

Where was this technology developed and how was it published?

The research was led by scientists at KAIST (Korea Advanced Institute of Science and Technology) in collaboration with colleagues from Singapore's NUS (Nanyang Technological University) and SMU (Singapore Management University). Results were presented in June 2026 at the international academic conference ACM MobiSys 2026.

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Mentions
  • KAIST
  • SweepLED
  • NUS
  • SMU
  • Han Jun
  • ACM MobiSys 2026