How AI Technologies Can Impact Car Inspections? Use Cases Explained
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Artificial intelligence is revolutionizing every area of our lives, and the automotive industry is no exception. CHI Software, as a generative AI development company that has been growing since 2006, knows this better than anyone. Today, one of the most significant advances in the automotive industry is AI vehicle inspection.
AI integration is changing how cars are assessed, making the process faster, more accurate, and more efficient. CHI Software’s developments in this new field include AI-based machine condition monitoring software, which is already helping to monitor the state of a car in real-time, while the vehicle hail scanning system can detect even the slightest external defects in about a minute.
In this article, we will explain how cutting-edge technology is changing traditional practices, covering the benefits of artificial intelligence in inspection, key innovations, and CHI Software’s experience in this field. So, let’s start with the most interesting — how AI transforms vehicle inspections.
Benefits of AI in Car Inspections
Artificial intelligence technology offers advantages that traditional methods cannot match. Thanks to the introduction of smart algorithms, inspections can become more thorough, efficient, and reliable. Below, you can find a detailed answer to the question of how AI transforms vehicle inspections.
Faster and More Accurate Inspections
Artificial intelligence minimizes the human factor in vehicle inspection. Human inspectors may not notice small defects, for example, due to fatigue. In this case, machine learning models and advanced algorithms will do the painstaking work with extreme accuracy to the smallest detail.
AI has many capabilities that are beyond human inspectors. For example, by implementing AI, a company can check the alignment of key components such as wheels, axles, and body panels to ensure they meet manufacturer specifications.
Reduced Costs
Another advantage of AI in vehicle inspections is significant cost savings for both businesses and customers.
- The time needed for labor is reduced due to the automation of many processes, resulting in lower costs for inspectors. The changes enable the company to cut the number of inspectors or redirect them to other, more important tasks.
- Equipment and maintenance costs are comparatively lower, as AI systems require less supervision and upgrades than tools and equipment used for manual inspections.
Predictive Maintenance
Predictive maintenance ensures that potential malfunctions are identified early. What does this mean? First and foremost, it is a significant safety improvement. Preventive maintenance saves time, and could even save the car. This approach could reduce the number of unexpected failures during the driving process.
AI vehicle inspections allow you to keep records and quickly analyze past data to provide a complete picture of the vehicle’s condition. Such innovations reduce the number of unnecessary interventions, and maintenance can be performed only when it is needed.
Improved Vehicle Safety and Reliability
- In addition to detecting damage faster, AI can also use machine learning algorithms which continuously learn and adapt after each inspection to create a more reliable inspection process.
- Monitoring systems can detect the most minor problems using image recognition and computer vision algorithms. AI can detect damage that is usually missed during a manual inspection.
- AI inspects all cars to the same exacting standards. And, of course, the inspection staff and car owners have access to a history of all inspections with in-depth details. Reports and other types of feedback are also provided in the shortest possible time, minimizing downtime.
Real-Time Data Processing
AI can process vast amounts of data in real time. Processing includes various readings: sensors, vehicle diagnostics, and image recognition. It’s hard to describe how massive this work is and how much time and effort it would take without AI. The implementation of AI algorithms allows professionals to take immediate action if any problems are detected.
Improved Documentation
AI systems can automatically record and document inspection results. Algorithms can create digital records that can be stored or shared. Improvements to documentation can include:
- Automated data recording: every step of the inspection can be documented in real-time.
- Comprehensive reports: AI systems generate detailed inspection reports. They include diagnostic data, images of defects, accurate sensor readings, and a summary of the overall condition of the vehicle.
- Easy sharing: inspection reports can be shared between departments, teams or other stakeholders.
- Visual documentation: documents are supplemented with high-resolution images or videos.
- Historical data analysis: improved documentation allows professionals to analyze trends over time.
AI-Driven Innovations in Vehicle Inspection
It’s incredible what AI-based car inspections can achieve, isn’t it? Well, we’re not going to stop here. We have prepared up-to-date information on using all of these technologies, so let’s get down to it.
Comprehensive Vehicle Health Monitoring
To completely understand the vehicle’s condition, sensor fusion needs to be used, combining data from multiple sensors. Then, health index algorithms can calculate the overall state of the car. If necessary, professionals can customize the monitoring areas depending on the car’s type. Such a comprehensive approach will provide a complete picture of the car’s condition, from the engine’s operation to the appearance.
Inspection Report Automation
NLP is actively used to generate detailed yet human-readable reports without manual control. Of course, this saves both the client’s and the company’s time.
At one of the first stages, NLP models process large amounts of structured and unstructured data from images and sensors to extract the most crucial information from the entire review. Then, NLP automatically summarizes the findings and identifies key issues. Algorithms ensure the integrity and completeness of all reports. Natural language is used to format well-structured reports, making them even more accessible.
Post-Collision Analysis
In post-collision analysis, machine learning is widely used to estimate repair costs based on existing damage. Algorithms are used to predict the cost of repair solutions. ML also simplifies the decision-making process during the repair process by helping to understand the consequences comprehensively.
Automated Pre-Delivery Inspections
Defect detection models and quality control algorithms ensure vehicles meet standards.
Automated pre-sale inspection (ASI) is a critical process in the automotive industry. It ensures that vehicles meet quality and safety standards. For these inspections advanced technologies are applied to finer points.
Defect detection models use artificial intelligence and machine learning to scan vehicles. The automated ASI process detects a massive number of defects: from mechanical problems and system malfunctions to cosmetic imperfections.
Used Car Certification
3D images and sensors help algorithms assess the degree of wear and tear, and machine learning algorithms estimate the value of the vehicle based on its condition and market requirements.
The process of AI-based vehicle damage detection was described in detail earlier. We described a successful combination of algorithms on the example of a vehicle hail scanning system application we developed. Check it out!
How about learning more about the technologies behind these use cases? Our original article will explain them to you in detail, adding some real-market case studies and future AI implementations.
