The Viridis platform is extensively based on the concepts of the Internet of Things, Big Data, and Industry 4.0, as it is capable of capturing, storing and processing large volumes of data on the consumption of energy and utilities of any operational unit, whether a specific machine or a production process as a whole. These data, combined with information about the context in which they were recorded (production plans, process variables, operational parameters, among others), makes possible, using the techniques of Machine Learning, the construction of predictive models that are combined to create a digital representation of that asset – a digital twin. The large integration capacity of the platform facilitates the capture of relevant data, while its modeling and visualization capabilities make the use, interpretation, and evolution of digital twins easy, resulting in significant value creation for our clients.
Data Analyst for Viridis, degree in electrical engineering from UFMG. He has a solid understanding of computational intelligence and statistics, acquired during his time at the Computational Intelligence Laboratory of the School of Engineering of UFMG.
Publications by Victor de Souza