Application of bayesian deep learning for Smart City monitoring and chemical industry processes operation

• Grant number: 19/08280-9
• Support type: Scholarships in Brazil - Master
• Effective date (Start): June 01, 2019
• Effective date (End): May 31, 2021
• Field of knowledge: Interdisciplinary Subjects
• Principal researcher: Song Won Park
• Grantee: Gustavo Ryuji Taira
• Home Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 17/50343-2 - Institutional development plan in the area of digital transformation: advanced manufacturing and smart and sustainable cities (PDIp), AP.PDIP

Abstract

Project consists on the development of Bayesian Deep Learning based systems applicable for the Smart Cities monitoring and chemical industry process operations. The elaborate systems will be applied to databases obtained by air quality sensors and/or sound noise sensors, and, lastly, they will be applied to industrial chemical process data (FCC) (Fluid Catalytic Cracking). One of the goals of this work is the development of Big Data Analytics systems to be incorporated as applications of Machine Learning with methods that are easily applicable for different contexts, in order to create self-agent systems such as Smart City and Smart Factory. (AU)