Temperature behavior is considered in the industrial environment as a challenge for analysis and inspection. The use of smart technologies is essential in different industrial environments when exists multi-stages. It is a challenge when the goal is the prediction of events through time. In this paper, we present a process for environment partition by clustering that uses analysis of historical measures of temperature to obtain at first, the best statistical value for making partitions. The experimental results demonstrate that our approach has good results.
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