aiData Use Cases | Data Solutions for ADAS & AD
Query and manage real-word data
Explore the details of the whole journey such as time-of-day, road types traveled, and search for interesting events based on object class, traffic sign types or traffic scenario, among many others. The aiData Versioning System is powered by AI-based capabilities to ease data curation, including text-, image-, scenario-, and similarity-based searching. Automate the curation of diverse datasets to allow your engineers to focus on more valuable tasks.
Collect your data synchronized and well-calibrated
aiMotive has vast experience calibrating complex, multi-modal sensor setups and providing tools and engineering services if requested. Record data using the aiData Recorder to ensure synchronization and calibration between sensor streams while enabling real-time diagnostics to ensure that any issues can be identified and corrected during the data collection campaign.
Auto annotate real-world data
Annotate data automatically with the aiData Auto Annotator, including dynamic traffic participants and static objects, outperforming human annotators in accuracy. Teams will have annotations available just hours after data collection, enabling a 400x efficiency gain and more than 95% cost reduction, only after 500 hours of annotated data - compared to manual labelling.
Create your own metrics
aiData provides a flexible metrics framework to track your software development progress against any arbitrary KPIs. The tool comes with 150+ built-in metrics, such as calculating NCAP scores and AEB FP rate, among many others, in simulation and readback. Easily set up your completely automatic V&V for new software releases, with engineer- and manager-level visual reports.
Generate synthetic data to address data gaps
Create great volumes of diverse synthetic data, with the variability needed to replicate real-world conditions for training and testing your AD software. Generate synthetic sensor data with plausible scenarios and event sequences, and vary environmental and road conditions.
Create 3D environments with neural reconstruction
Automatically generate static 3D worlds with neural reconstruction in a highly scalable way with neural reconstruction, all without relying on 3D artists. Then, simulate complex sensor setups and augment the scenes with dynamic agents, all while closing the real-to-sim gap compared to traditional simulation.
