The well-designed and proven ASAM ODS Semantics and Data Models will play an indispensable and essential role in Distributed Processing, Artificial Intelligence and Machine Learning in the Measurement and Simulation domain. Distributed Brix platform is based on international standards ASAM ODS which offers well defined semantics to the heterogeneous disconnected data in a standard form.
BRIX is based on an architecture which is a fusion of technologies. iASYS uses Spark for distributing the analytics and make it semantically rich data by using Graph databases. This data also needs to be accessible to different programming languages & platforms. The target is achievable with BRIX in a short span of time.
Additionally, the BRIX PVM helps in setting up a foundation for model-based development (MBD) system where a seamless exchange of engineering data across validation process is possible. It holds the capability to be extended for enterprise and multi-locations globally.
The automotive industry is entering a wave of transformation with innovation like emission regulations for Gasoline & diesel engine Electric/Hybrid mobility, Automated Driver Assistance Systems (ADAS), Autonomous Driving (AD). Thus the IT teams of organizations in this domain are placing their bets on big data technologies (cloud & cluster computing). To assure competitiveness, firms in the automotive industry are forced to respond to market demands quickly and to develop and manufacture their products efficiently. One such initiative called Digital twin (where simulation and physical test result meet)strategy is being realized in the product validation area, as the need of an hour to fulfil high-quality standards, and meet customer needs & legal requirements in the shortest possible time to market . However, there are some challenges which need to be overcome to realize the strategy.
Simulation data is already in digital form. Bringing the physical test & validation data in digital form is challenging, given the scattered existence of the data in different function groups, departments, formats and increased volume. Apart from IT technology challenge, the lack of engineering domain knowhow is an equal drawback against the successful implementation of such solutions. iASYS addresses this challenge Distributed Brix – Big Data. This is a scalable platform based on distributed and parallel computing architecture coupled with the knowledge of complex engineering data in automotive domain for the past two decades.
Unlike Social Network, in automotive, the nature of data is complex. It is high volume binary structured data. To process high volume of engineering data, concurrent computing resources are required which can effectively process algorithms in parallel. Distributed Brix offers High performance parallel computing architecture coupled with well defined semantics meta model for domain know-how and is specifically designed to offer high performance in Automotive development area. Once Digital twin is realized in product validation area, OEMs will have the foundation for Artificial Intelligence (AI) and Machine learning (ML). In fact, specifically in the R&D environment, data sources like test beds & development fleet can become IOT device. Data from different validation testing equipment or development vehicle fleet (IoT Devices) will flow into the development area.