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Most existing algorithms for fault-tolerant event region detection only assume that events are spatially correlated, but we argue that events are usually both spatially and temporally correlated. By examining the temporal correlation of sensor measurements, we propose a detection algorithm by applying statistical hypothesis test (SHT). SHT-based algorithm is more accurate in detecting event regions, and is more energy efficient since it avoids measurement exchanges. To improve the capability of fault recognition, we extend SHT-based algorithm by examining both spatial and temporal correlations of sensor measurements. The extended SHT-based algorithm can recognize almost all faults when sensor network is densely deployed.