That’s a cool idea. I’d start by mounting a shotgun mic on a tripod near a traffic intersection, maybe a binaural mic on a head set so you get that true 3‑D feel of the road. Use a 24‑bit field recorder at 48 kHz to keep all the high‑frequency detail. Then step around the corner to capture the streetlight hum with a close‑mic or a passive contact mic on the pole—those low‑frequency whines are easier to isolate that way. When you have the files, load them into a spectral editor like Sonic Visualizer or MATLAB. You can plot a time‑frequency spectrogram and tag the peaks that match the traffic cadence. Then overlay those timestamps onto a GIS map or even a simple spreadsheet that maps latitude, longitude, and sound level. If you want to really quantify it, run a Fourier transform on each segment to extract the fundamental frequency of the hum, and use that as a “city noise index.” Finally, export the data and create a visual waveform that looks like a city map—high‑volume streets in red, low‑volume corners in blue, with the traffic pulse overlaid as a rhythmic contour. That should give you a neat acoustic blueprint of the city’s heartbeat.