{"id":281,"date":"2018-04-12T21:38:27","date_gmt":"2018-04-12T20:38:27","guid":{"rendered":"http:\/\/www.alkit.se\/?page_id=281"},"modified":"2018-04-12T21:47:32","modified_gmt":"2018-04-12T20:47:32","slug":"baud-ii-big-automotive-data","status":"publish","type":"page","link":"https:\/\/www.alkit.se\/index.php\/projects\/baud-ii-big-automotive-data\/","title":{"rendered":"BAuD II – Big Automotive Data"},"content":{"rendered":"

The landscape of the automotive industry is currently being dramatically redefined by connectivity, smart embedded systems, cloud services and Big Data analytics. To stay competitive and to meet the challenges of climate change, safety and sustainability, vehicle manufacturers must provide new added value product features and services, while reducing the time to market. The key to realize this is to fully exploit the opportunities of leveraging data collected from vehicles for knowledge-driven product development.
\nThe aim of the BAuD II project is to explore how a technological platform for telematics, cloud computing, Big Data analytics and decision making support can be implemented and deployed in operational environments to improve product quality, while simultaneously reducing the time to market.<\/p>\n

The project is a continuation of the\u00a0BAuD<\/a> FFI project, wherein a prototype Big Data telematics and analytics platform has been developed and tested. The next step is to take this prototype to a higher technological readiness level, to further improve the scalability of the platform, and to extend it in several ways to increase the benefits. The scalability requirements will initially target a test vehicle fleet of one thousand vehicles, with the expressed aim of the technology developed to be scalable to customer vehicle fleets of millions of connected vehicles. The extensions will include the addition of user generated data through a multi-purpose smartphone app to be developed in the project. By complementing the objective data measured in test vehicles with subjective data from customers, a quicker and more accurate response to customer needs and expectations will be possible. This will require improvements to the analytics framework, to also be able to analyze and cross reference subjective data. The intention is furthermore to design the smartphone app not only to serve as a subjective data collection tool, but also as a means to present information to the users for novel applications, improving the customer experience based on the information resources generated by the Big Data analytics services.<\/p>\n

Finally, the project will also study how tools for collaboration and decision making based on the collected data can be designed and integrated into the telematics and analytics framework. This includes the development of a knowledge management system, capturing the results and experiences generated from the telematics and analytics framework.<\/p>\n

The project partners are:<\/p>\n