Computer vision and Artificial Intelligence – the driving forces in the Automotive Industry!
Christian Dale
Product Marketing Manager at Anyline
Computer vision and artificial intelligence (AI) are two technologies that are driving a wide range of new innovations in the automotive industry. From self-driving cars to mobile data capture, these technologies are helping to make our roads safer and more efficient.
In this blog post, we will cover the following three primary areas of AI development:
- Self Driving Cars
- Vehicle Navigation Systems
- Mobile Data Capture
Jump to key topics
Jump to key topics
Self-Driving Cars
One of the most exciting areas where computer vision and AI are being applied in the automotive industry is the development of self-driving cars. Self-driving cars rely heavily on computer vision to understand and navigate the road ahead. They use cameras and other sensors to detect and interpret the environment around them, and then use this information to make decisions about where to go and how to avoid obstacles.
One of the key challenges in developing self-driving cars is ensuring that the car can “see” the road ahead with a high degree of accuracy. This is where computer vision comes in. A car’s ability to quickly and precisely detect and identify objects on the road is made possible by computer vision algorithms that can process and analyze data from cameras and sensors in real time.
Vehicle Navigation systems
One of the main ways AI is being used within the automotive industry is to improve the accuracy and reliability of GPS-based navigation systems. To give drivers more precise and current information, AI algorithms can analyze data from a variety of sources, including maps, traffic data, and sensor data from the vehicle itself. In order to provide more individualized and effective routes, AI-powered navigation systems can also learn from a driver’s behavior and preferences over time.
Mobile Data Capture
In the automotive industry, particularly when it comes to vehicle servicing, technicians and mechanics are actively using mobile data capture to help them finish tasks that would previously have required a lot of time and repetition. This increased efficiency allows them to do more with less, giving service operators more manpower with fewer resources.
The main purpose of this AI-supported technology is to gather data that would otherwise be gathered manually. In the automotive industry, this can range from vehicle identification numbers (VIN) during registration to serial numbers on unique parts and even embossed letters on the sidewall of the tire, including both DOT/TIN and tire size numbers. More recently, computer vision has made it possible for mechanics to measure the depth of tire tread accurately using only a smartphone with a camera.
These solutions can be integrated into a matter of hours using any current application the operator may already have in place, be it for their workforce or customers since mobile data capture only needs a camera-enabled mobile device. The Anyline Mobile SDK is made to work with a variety of cross-platform frameworks, including React Native, Flutter, Cordova, Xamarin, and.NET MAUI, as well as native platforms like iOS, Android, and the Universal Windows Platform (UWP). Furthermore, Anyline Mobile SDK is designed to handle all data processing on the user’s device, enabling data capture without an internet connection.
In general, computer vision and artificial intelligence (AI) are crucial for the creation of new innovations in the automotive industry. These innovations—which range from self-driving cars to portable data collection devices—help to improve road safety and efficiency while enabling service providers to interact with customers more skillfully. And as these technologies continue to improve, we can expect to see even more exciting developments in the years to come.
