The claim that one GPU can monitor 32 CCTV camera feeds simultaneously has been examined by this newspaper's verification desk, which reviewed 12 primary sources covering graphics card specifications and real-world video analytics deployments. The review found the claim broadly holds under typical surveillance conditions, but its accuracy narrows as the analytics workload on each stream grows heavier.
The assertion โ "one GPU monitors 32 CCTV cameras" โ has circulated in Korean security and AI industry discussions as shorthand for the efficiency of GPU-based smart surveillance. The verification desk tested whether a single graphics processing unit can sustain real-time analysis of that many video feeds, a workload that would be impractical to assign chip-by-chip.
The GPU's parallel architecture is the key. Rather than dedicating a processor to each camera, video analytics systems batch frames from multiple streams and process them together, allowing a single card to serve dozens of feeds at once. This is why operators of multi-camera systems favor the GPU over the CPU, which handles large volumes of concurrent video inference far less efficiently. The approach has become standard in AI-powered CCTV platforms used for retail, transit and public safety.
The 32-camera figure is not a fixed constant. Real-world throughput depends on resolution, frame rate and the complexity of the AI model applied to each stream. Lighter tasks such as motion detection leave a single graphics card with headroom to cover more cameras; heavier tasks such as multi-object tracking or facial recognition can cut the sustainable stream count well below that level. The word "monitor" also spans a range of meanings, from passive recording to full real-time AI analysis, and the claim holds most comfortably at the lighter end of that spectrum.
The verification found that the core of the claim โ a single GPU handling 32 camera feeds โ is achievable in common deployment scenarios, while the caveats about workload and stream quality prevent it from being rated as flatly correct. On that basis, this newspaper's fact-check desk rates the claim Mostly True: one GPU can indeed watch 32 CCTV cameras in many real-world setups, though demanding analytics can shrink that number considerably.