Diagnostic Sensor Performance Bench: 3D

This simulation renders a genuine 3D sensor field — not a flat dashboard — distributed evenly across a sphere around a central diagnostic device core using a Fibonacci-sphere layout, which you can freely orbit and zoom around. Each sensor node independently computes its own signal-to-noise ratio from a fixed signal power against a noise floor set by the efficiency slider (SNR = 20·log₁₀(Signal_Power / Noise_Power)), coloring itself from red through yellow to green as its reading improves. Meanwhile the whole bench's reliability decays over simulated time following Reliability = e^-λt, where the failure rate λ depends on both the chosen device type (diagnostic, therapeutic or monitoring hardware fails at different baseline rates) and the efficiency setting — low efficiency accelerates failures, and a sensor that fails visibly dims to gray and drops out of the live detection-accuracy count. Detection accuracy itself follows the useful-output-over-total-input relationship from the source instrument model, weighted by the live reliability curve, so you can watch a bench's real-world diagnostic confidence erode in three dimensions as sensors age and noise rises.