An Wang

Remote Calibrating a National-Wide Dense Low-Cost Sensor Network for Hyperlocal Air Surveillance.

This study proposes a scalable remote calibration framework that eliminates physical colocation by integrating metropolis-specific monthly updates with a spatiotemporal pairing algorithm for representative training data selection and serves as a cornerstone in advancing the use of large-scale LCS networks.