The invention discloses a sampling GPR method of continuous 
anomaly detection in a collecting data flow of an environment sensor, and belongs to the technical field of 
data monitoring of environment sensors. The sampling GPR method of the continuous 
anomaly detection in the collecting data flow of the environment sensor is used for solving the problem that 
anomaly detection can not be conducted in real time, wherein the problem is caused by the fact that data calculation amount is large in data flow anomaly detection of a traditional environment sensor. The sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor is based on a prediction-
model method, a prediction model is built through historical data, the mean value and the 
confidence interval of current data are obtained, a current 
data value is compared with the 
confidence interval, and the current 
data value is regarded as exceptional data if the current 
data value exceeds the 
confidence interval. According to the sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor, less historical data are needed, 
algorithm operation efficiency is improved, and input training data are not required to be provided with category tags. The sampling GPR method of the continuous anomaly detection in the collecting data flow of the environment sensor can detect an exceptional situation in a self-adaptive mode according to real-time arrival data, and is applied to continuous exceptional 
data detection in collecting data flow of the environment sensor.