Alessandro Chiotti
Industrial Data Analytics from IoT sensors: an explorative study on coffee machines.
Rel. Elena Maria Baralis, Daniele Apiletti. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2019
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Abstract
The ability of collecting data from any kind of device is becoming more and more important every day. Many companies have realised that data acquisition and analysis provide a way to find new and more efficient solutions to their problems and to open up new perspectives. In order to optimize costs and maximize results, an initial exploratory analysis is necessary: in this phase, the interaction and exchange between domain experts and data analysts is fundamental to guide the analysis towards the company's objectives and to correctly interpret the results obtained from the data. For this reason, the thesis, conducted in collaboration with Lavazza, explores the data obtained from the telemetry sensors installed by the company inside their bar coffee machines.
The study is focused on analysing the feasibility of predicting coffee quality, predictive maintenance and identifying the variables mostly related to the two previous objectives
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