By improving existing services and adding new services without interrupting existing functionality, it becomes possible to support new services like hazard prediction for connected cars and driving assistance, which must operate non-stop. ![]() ![]() ![]() By analyzing and predicting current, past, and future states while processing the data flowing in continuously and saving several instances worth of the results of data processing in memory, the technology offers services like driving diagnostics and failure prevention for car batteries, etc.By analyzing the driving conditions of each vehicle on a road to road basis in real time, the technology creates a virtual simulation of road conditions that delivers users almost instantaneous traffic information about traffic jams and driving hazards.After initial availability in Japan, the solution will subsequently be rolled out in North America and Europe. Parallel processing, as well as data processing content can be added and modified in an agile manner while the system is running, offering service providers the ability to flexibly respond to data analysis and prediction services in various use cases, while providing safe, secure, and comfortable mobility services to drivers and carriers on the road. Data and data processing programs (referred to below as plugins) are managed as objects in an in-memory system ( 3) in stream processing for pedestrians, vehicles, roads, buildings, and other objects from the real-world. About the Technologyįujitsu is offering a data processing platform powered by its Dracena technology. In order to create a digital twin for use in a mobility context, Fujitsu has launched its new stream data processing platform to support the development of various services that leverage automotive big data to contribute to the realization of a safe, secure, and comfortable mobile society. Simultaneously, these systems for analyzing automotive big data are siloed for each service and overlap in development functions and system resources, creating a need for a system that can flexibly and efficiently implement various services concurrently.Īgainst this backdrop, Fujitsu is advocating and promoting the digital twin technology for the mobility space, based on the idea of digitally reproducing information about vehicles and roads in real-time. Big data from connected vehicles, including images collected from car sensors, and CAN ( 2) data, will play an important role in realizing mobility services like traffic monitoring, maps, and insurance, as well as vehicle design. The mobility industry is presently undergoing a once in a century period of change, and from 2020 onward, the number of connected cars will increase exponentially. Going forward, Fujitsu plans to roll out the service in overseas regions including North America and Europe. Continuous data processing additionally offers users the flexibility to add and change services that must operate without disruption, such as real-time hazard prediction for connected cars. This makes it possible to digitally reproduce the surrounding situation, including other vehicles. The new platform allows for the management and processing of data in discreet units of people and objects including pedestrians, vehicles, roads, and buildings, which are constantly changing in the real world. The new platform facilitates simple and efficient automotive big data analysis by leveraging Fujitsu's data processing technology, Dracena ( 1), a stream processing architecture that can add or change content while processing large volumes of IoT data, without stopping. Fujitsu Limited today announced that it will launch a new stream data processing platform for service providers to maximize the use of big data collected from connected cars.
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