The proposed work describes an architecture able to optimize production supporting wheat transformation processes, developed within the framework of an industry research project. The architecture is designed in order to integrate and enable different systems and technologies including big data systems and artificial intelligence algorithms. Preliminary results about detected field data and data flow implementation are discussed. A particular attention is focused on predictive maintenance of production machines by infrared thermography imaging and accelerometer signal processing.

Production Optimization Monitoring System Implementing Artificial Intelligence and Big Data

Massaro A;
2020-01-01

Abstract

The proposed work describes an architecture able to optimize production supporting wheat transformation processes, developed within the framework of an industry research project. The architecture is designed in order to integrate and enable different systems and technologies including big data systems and artificial intelligence algorithms. Preliminary results about detected field data and data flow implementation are discussed. A particular attention is focused on predictive maintenance of production machines by infrared thermography imaging and accelerometer signal processing.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12572/18370
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