Preparing driving data is an essential step in training the artificial intelligence (AI) technology that powers autonomous vehicles. In fact, the quality and quantity of data will affect the AI model’s decision-making process. To save you cost and time, EC Innovations has put together key points on what to look out for when gathering training data based on our rich experience in collecting and processing driving data.
Data Collection Hardware
The performance of a car’s vision sensors (such as the front, surround, and rear view cameras) determines the light transmittance and fidelity of image acquisition. Thus, the precision of data collected by cameras, LIDAR sensors, gyroscopes, and other hardware will depend on how many are installed and where. To select the most suitable device and installation position, you should learn about the sensor specifications and functions.
Real-World Data Collection
Before data is collected in the real world, detailed research should be conducted on different driving conditions and data types for route planning. In addition, you should consider factors such as data resources, network centers, parking locations, costs, and driver safety.
Data Transmission and Security
Data security has always been the top priority in driving data collection. The parties involved in a project should sign an NDA that sets out the terms for the use, transmission, storage, and inspection of data collected. Data security should be ensured in all stages, from data collection and labeling to storage and transmission.
There’s certainly a lot that goes into data collection, but this hard work will pay off in the long run. EC Innovations is a leading one-stop data service provider, offering high-quality data collection and annotation expertise. Get in touch with us inquiry@ecinnovations.com to develop tailored solutions for your business needs.
