Visually impaired people face urban mobility hazards such as vehicles, pedestrians, curbs, and steps. Wearable electronic travel aids can support obstacle avoidance only when these hazards fall within sensing coverage. Existing studies have focused mainly on algorithms and human–computer interaction, while the sensing coverage required by real-world hazards remains less examined. We collected 1486 min of street-scene video, built urban mobility hazard samples, and used simulation to compare target pixel counts over time for cameras with different horizontal fields of view. Among 81,353 valid samples, hazards showed concentrated high-frequency categories and a rich long tail, mainly including vehicles, scooters, pedestrians, curbs, bollards, poles, trees, and steps. Simulation showed that a horizontal field of view of approximately $120°$ balanced pixel coverage and sustained observation. We then built a chest-mounted four-camera prototype and conducted a feasibility demonstration at a real intersection. Camera configuration should therefore be guided by real-world hazard visibility, and coordinated multi-camera coverage is a promising design choice for wearable ETAs in urban environments.