A data-driven methodology based on unsupervised learning for vehicular feedback in the context of Industry 4.0
Industry 4.0, Intelligent Vehicle, OBD, Evolutionary Systems.
The new industrial revolution, known as industry 4.0, aims to create value throughout the product lifecycle and customer feedback. Emerging, the automotive market has grown with the help of technologies, which enables automatic communication between vehicles and factories. For this, an On-Board Diagnostic (OBD) scanner is used to capture the data and send it to a server in the cloud, allowing different analyzes of these vehicles to be performed in real time. Thus, the purpose of this work is to provide customized feedback based on vehicle information for industry 4.0 customers in the automotive industry through a data streaming and unsupervised learning methodology. In order to provide this feedback, an explanatory study will be adopted by means of an experimental procedure for validation of the proposed methodology. Preliminary results regarding an exploratory analysis of the Platforms / App and OBD Edge are explained, which provides benefits to research and developments in this area.