Strong motion data recorded by strong-motion networks are essential for preventing and mitigating earthquake disasters, such as earthquake early warning and earthquake emergency responses, and the type of accelerometer can significantly influence the quality of recorded ground motions (GMs) and the subsequent usage. Different types of accelerometers vary significantly in both the price and the quality of collected data, because cheap accelerometers generate non-negligible self-noise and reduce the quality of the collected GMs. However, the effects of the accelerometer type and spatial density on the accuracy of GM-based seismic damage assessment are still unknown. The present study attempts to quantify these effects comprehensively at a regional scale. First, a method to simulate recorded data from different quality sensors is devised, using characteristics of existing low-, medium-, and high-quality accelerometers. These simulations use input data from either the Pacific Earthquake Engineering GM database or from a high-fidelity fault rupture and regional wave propagation simulation. Subsequently, the simulated sensor data are used to assess the seismic damage to typical buildings at a city scale. The results indicate that low-quality sensors found in most smartphones are currently insufficient for assessing seismic damage. Medium-quality accelerometers (MEMS-based instruments), on the other hand, can provide feasible solutions for cost-effective city-scale deployment and may offer deployment options that are superior to sensor networks with high-quality accelerometers.