File:Channel-Estimation-Channel-estimation-data-gathered-during-c4fc3c25.jpg

Channel estimation data gathered during routine beamforming contains enough environmental detail to passively profile human presence and biological rhythms.

AI-generated illustration for Channel Estimation, made with fal.ai (fal-ai/flux-2-pro).

Prompt: A cutaway view of a domestic room showing a Wi-Fi access point emitting beamformed signals toward a human figure, with the reflected signals returning to the access point and being processed into a silhouette or biological profile of the person, suggesting the extraction of presence, movement, and respiratory data from the channel feedback. Style: Detailed digital illustration blending technical schematic linework with painterly atmospheric rendering, as if a scientific textbook were reimagined by a noir graphic novelist. Colour palette of deep midnight blue, charcoal black, and slate grey as foundations, accented with electric teal, bioluminescent green, and cold amber. Lighting is dramatic and directional, suggesting surveillance or laboratory environments — pools of cold light against deep shadow, with occasional glowing circuit-trace highlights. Compositions favour tight framing with layered depth: foreground technical detail dissolving into abstracted background geometry. Detail level is high but purposeful, prioritising legible structure over decorative complexity. Mood is clinical yet ominous, precise yet unsettling. No text, lettering, captions, logos, watermarks or borders unless it is a technical drawing.