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However, most existing machine learning\u2010based charts assume that in\u2010control process observations are independent and identically distributed, a condition rarely met in practice, which limits their real\u2010world applicability. This paper suggests a framework that integrates a sequential spatio\u2010temporal decorrelation procedure with representative machine learning charting schemes, enabling effective monitoring of spatio\u2010temporal data streams. 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