IVS is a solution for the benchmarking and validation of your ADAS and HAD software functions in a virtual driving context (including vision algorithms, data fusion, deep-learning, positioning, etc.)
IVS allows to centralize, store and share your recorded driving situations (sensors data), index them, search for particular situations, preview and post-process such huge amounts of driving data on parallel computing clusters.
IVS is made of several two main modules.
IDM is the core part of the IVS solution. It consists in a centralized big-data database to store, re-index, preview and search for particular driving scenarios among your large amounts of recorded data (up to PetaBytes, including video streams, lidars, radars, GPS, CAN and any other automotive sensors data).
Based on the search results in IDM, the Intempora Test Manager allows to inject your own algorithms and software features in the form of RTMaps applications (diagrams) in the cloud system, and automate post-processing tasks in a distributed manner on clusters of computing nodes in the Azure environment.
IVS is made for being middleware-agnostic, so it can work with various sensors datasets and operate jobs with different middlewares or simulators.
RTMaps and RTag are already nicely integrated with IVS for data recording, live tagging and optimized post-processing of multisensor datasets.
Based on RTMaps (Real Time Multisensor applications>, the Intempora flagship, users can develop high-end in car data recording systems on a variety of hardware platforms from the market.
RTMaps is also made for algorithms integration, excecution, testing and validation, and can be used in the IVS framework as a post-processing framework in ITM and for tags generation and previews generation.
With RTag, a tactile tablet connected to an RTMaps data recorder, it becomes easy to manually annotate data while driving, in conjunction with potential automatic annotation algorithms running in real-time in the recorder.