Cloud-Based Architecture Development to Share Vehicle and Traffic Information for Industry 4.0

Abstract

The automotive and technology sectors have developed very rapidly over the past decade. In addition to this growth, it also introduced the term Industry 4.0, which is used to represent the current Industrial Revolution. This revolution encompasses many sectors from manufacturing to health care. With Industry 4.0, digital transformation can create value throughout the entire product lifecycle, support customer feedback, and provide advanced solutions to the problems to be experienced. Automatic communication between the vehicle and the management office will facilitate our lives by enabling different analysis of vehicles such as the driver’s vehicle usage history, fuel consumption, maintenance indicators, determination of a behavioral model with data like temperature. This provides analysis of the car, the driver’s experience, and the road, preventing critical problems and unwanted behavior, and increasing safety on the roads. For example, during the winter season, municipal employees will not have to wait at night to intervene in road freezing. Employees will instantly monitor which roads are at risk of icing through the data collected from the vehicles on the road and municipal workers will salinize them in no time. This article aims to implement a platform that collects and analyzes vehicle sensor data and provides individual and corporate feedback. Using the OBD-II scanner, it is intended to help prevent problems, reduce accident rates and manage different types of vehicles. A ready OBD-II (On Board Diagnostic) reader device, supported by a Bluetooth connection, is used to collect data directly from the ECU (Engine Control Unit) in real-time, using an android-based smartphone as a cloud network connection. The architectural structure in the cloud is capable of collecting and analyzing raw data to detect the occurrence of errors in vehicles. While providing feedback to the user, a smart cloud-based architecture provides the necessary information to the relevant municipal, fire or ambulance units by foreseeing traffic accidents, the icing on roads in winter or asphalt melting in summer. Experiments and tests conducted in Istanbul’s traffic show that the proposed platform has applicability and potential to use.

H. Ilhan—Senior Member, IEEE.