Artificial intelligence has become an integral part of many spheres of activities. It is no surprise that the automotive industry is no exception. AI is making significant progress in many areas, including image analysis. Thus, the latest technologies have enabled the automotive industry to automatically assess the condition of a car. And this is done on the basis of images. This opens up new opportunities for creating comprehensive car reports. These include reducing the time for damage assessment, increasing accuracy, and reducing the cost of expertise. So, what role will AI play in the future of this industry?
The role of AI in image analysis
AI technologies are revolutionizing image analysis in many industries. Modern algorithms are capable of not only processing a large amount of visual information but also providing conclusions. Previously, this was only possible with the help of human experts. One of the most impressive examples is AI damage detection. By analysing car images, AI accurately identifies even the smallest injuries. Moreover, it categorizes them by severity.
The role of quality for accuracy
Although the main topic is damage assessment using AI, it is worth remembering that image quality plays a major role in the accuracy of the analysis. And one of the important tasks that may be required before using an image for analysis is to remove image background so that the AI can focus on the main object, the car, and increase the accuracy of the analysis. Apple users can use built-in tools to do this. For example, Apple photos cut out background allows you to quickly remove the background from an image without having to install additional programs. So, we have iPhone remove background capabilities that allow us to remove the background of images directly on the mobile device. Mac users can also use Mac remove background from image to edit photos before using them in damage analysis.
Remote damage assessment and AI. Benefits and challenges
Previously, it was necessary to contact a specialist and conduct a physical examination, but today, thanks to AI, it can be done remotely. Users can upload photos of a car through a special app, where AI damage detection will automatically identify existing defects and estimate their cost. This allows users to quickly get information about the condition of the car without the need for a physical inspection.
Advantages
Speed and convenience
AI can process hundreds of images in a matter of seconds, whereas a human would need much more time to do so.
Reduced human factor
Algorithms work emotionlessly, not making mistakes due to fatigue or inattention.
Accuracy
Modern machine learning systems constantly improve skills and achieve high accuracy in damage assessment.
- Such systems can analyse different types of damage. From minor scratches to serious car body deformations.
- They can compare images of a car before and after an accident. This allows determining the exact location and nature of the damage.
Challenges
The need for high quality images
Even the most intelligent algorithm will not be able to provide an accurate result if the image is of poor quality or contains many third-party objects.
AI is still under development
Sometimes it may be necessary to check the results additionally. In complicated cases, when the damage is not obvious, AI may need support from an expert.
Integrating AI into the automotive reporting process
With image-based car damage assessment, you can automatically generate certain reports. They will contain information about:
- all the damage detected,
- their extent,
- possible cost of repair.
Such reports can be used for both internal and external purposes. For example, to assess the value of a car for resale, as well as for insurance companies.
To confirm the vehicle’s complete history from verified sources you can also avail a free vehicle check to know if it has been stolen, written-off or has any mileage issues.
Automating damage assessment and report generation processes with AI has great potential. Namely, the potential to influence the market. This can lead to the following significant processes.
- Reducing the cost of expertise
- Speeding up insurance processes
- Reducing fraud risks
At the same time, it may also create new challenges for traditional appraisers and insurance companies. They will be forced to adapt to new technologies.
Conclusions
The use of AI in image analysis and automotive reports is an innovative approach. This approach has a huge potential for development. AI damage detection and car damage assessment are examples of how technology can simplify processes and make them more efficient and less costly. However, despite all the advantages, there are also challenges. They also need to be considered. Only then will further development be obvious. Specifically, the development of AI technologies will continue to open new opportunities for the automotive industry. And we have to be ready for the changes they will bring.
