Road Quality Analysis Based on Cognitive Internet of Vehicles (CIoV)
This addresses road quality analysis for autonomous vehicle companies and users, but appears incremental as it applies existing cognitive methods to a new domain.
This research proposes using Cognitive Internet of Vehicles (CIoV) to analyze road quality from autonomous vehicle data, aiming to reduce energy consumption and improve quality of service for self-driving applications.
This research proposal aims to use cognitive methods to analyze the quality of roads based on the new proposed technology called Cognitive Internet of Vehicles (CIoV). By using Big Data corresponding to the collected data of autonomous vehicles, we can apply cognitive analytics to a huge amount of transportation data. This process can help us to create valuable information such as road quality from an immense volume of meaningless data. In this proposal, we are going to focus on the quality of roads for various business and commercial purposes. The proposed system can be used as an additional service of autonomous car companies or as a mobile application for ordinary usages. As a result, this system can reduce the usage of resources such as energy consumption of autonomous vehicles. Moreover, this technology benefits the next-generation of self-driving applications to improve their QoS.