aiData Use Cases
Query and manage real-word data
Manage data recorded by external loggers or the aiData Recorder, all utilizing the auto tagging of the aiData Versioning System. With our system, explore the details of the whole journey such as time-of-day, domain and special environment, and search for interesting events, based on object class, traffic sign types, traffic light states, among many others. By this, curating diverse datasets for a variety of use-cases can be achieved smoothly and efficiently.
Collect your data Synchronized and well-calibrated
Record data with the aiData Recorder with built in tools to ensure synchronization and calibration between sensor streams. It also enables real-time sensor diagnostics and sensor calibration to ensure that potential errors can be identified and corrected during anytime in the data collection campaign.
Auto annotate real-world data
Annotate data automatically with the aiData Auto Annotator, including dynamic traffic participants and static objects, utilizing AI algorithms and a GPU cluster. Collect and annotate continuously, while receiving real-time feedback on the accumulated dataset for efficient adjustments.
Create your own metrics
Measure development progress against requirements and dive into real-time insights and data gap analysis. aiData Metrics support environment detection benchmarks, such as object tracking and confusion matrix, and vehicle function benchmarks, such as Autonomous Emergency Braking, to monitor the performance of your algorithms.
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 high-precision maps from raw sensor data
Generate customized HD map providing a solid basis from entry level ADAS to complex automated driving systems without the need for third-party map source. Map complex roads, with lane level precision and enrich them with traffic sign and light information to prepare vehicles for the upcoming scenarios.
Create 3D environments with neural reconstruction
Create high-fidelity reconstruction of 3D assets in a highly scalable way with neural rendering, all without relying on manual labor.
