Fishing is a fundamental economic activity for the livelihood of thousands of families in the Amazon region. However, it is a challenging activity due to the rapid degradation of fish, caused by biological and logistical factors, which makes it difficult to store without an adequate conservation system. For this purpose, the main preservation method used by fishing professionals in the North of Brazil consists of systems based on EPS (Expanded Polystyrene) boxes partially filled with ice blocks. In order to extend the shelf life of fish, methodologies provided by Industry 4.0 can be used, among which simulation-based Digital Twins stand out. These can be described as a virtual copy that uses mathematical models to replicate physical phenomena, with the aim of controlling and predicting adverse conditions of the analyzed process. In this sense, the objective of this work is to propose a Digital Twin model that can be used to monitor temperatures in containers used for fish storage in the Amazon region. The proposed model showed a maximum error of 3.5ºC in temperature measurements, proving to be viable in monitoring fish.
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