Artificial Neural Networks as Artificial Intelligence Technique for Energy Saving in Refrigeration Systems—A Review

Mario Pérez-Gomariz (), Antonio López-Gómez and Fernando Cerdán-Cartagena
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Mario Pérez-Gomariz: Department of Information Technologies and Telecommunications, ETSIT—UPCT, Antiguo Cuartel de Antigones, Plaza del Hospital 1, 30202 Cartagena, Spain
Antonio López-Gómez: Department of Agricultural Engineering, ETSIA—UPCT, Paseo Alfonso XIII 48, 30203 Cartagena, Spain
Fernando Cerdán-Cartagena: Department of Information Technologies and Telecommunications, ETSIT—UPCT, Antiguo Cuartel de Antigones, Plaza del Hospital 1, 30202 Cartagena, Spain

Clean Technol., 2023, vol. 5, issue 1, 1-21

Abstract: The refrigeration industry is an energy-intensive sector. Increasing the efficiency of industrial refrigeration systems is crucial for reducing production costs and minimizing CO 2 emissions. Optimization of refrigeration systems is often a complex and time-consuming problem. This is where technologies such as big data and artificial intelligence play an important role. Nowadays, smart sensorization and the development of IoT (Internet of Things) make the massive connection of all kinds of devices possible, thereby enabling a new way of data acquisition. In this scenario, refrigeration systems can be measured comprehensively by acquiring large volumes of data in real-time. Then, artificial neural network (ANN) models can use the data to drive autonomous decision-making to build more efficient refrigeration systems.

Keywords: artificial intelligence; artificial neural networks; internet of things; energy saving; refrigeration systems; data-based models (search for similar items in EconPapers)
JEL-codes: Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2023
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