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These errors can significantly degrade the quality of collected data and the event log extracted from raw sensor readings, impact data analysis and lead to inaccurate or distorted results. This article emphasizes the importance of evaluating data quality and errors before proceeding with analysis. The effectiveness of three error correction methods, a rule-based method and a Process Mining (PM)-based method which are adjusted for a smart home use case, and their combination was also investigated in resolving log errors. 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