AI Patent Trends In The Automobile Sector

AI finds application in the entire value chain of the automotive segment. Below we explore its prospects in each: 

1. Manufacturing  
   The manufacturing circuit consists of four stages namely, Design, Supply Chain, Production, and Post Production. This is the segment that AI has touched most deeply due to its wide applicability here. AI robots are already being used by companies like Hyundai and OTTO Motors to work alongside humans on the assembly line. Hyundai has successfully tested robotic exoskeletons or wearable robots that reduce human fatigue by lowering the impact on the lower body. This may result in increased productivity. Similarly, OTTO launched an intelligent material transport vehicle for their plant, based on AI. This self-driven vehicle can autonomously navigate through the manufacturing unit.  
   AI also finds use in the automotive supply chain. With complex supply chains spread across countries and continents, ensuring smooth operation is vital to productivity. Implementing AI in the supply chain helps regulate logistics, tracking, and management easily.  
2.  Transportation 
   Autonomously driven passenger vehicles are the ultimate goal for AI applications in this segment. Tesla currently leads the pack with its level 2 autonomous cars with its ‘Autopilot Driver Assistance System’ in the Model S car. Besides, the above there are several other use cases in transportation. AI-powered software for driver risk assessment, cloud computing, and driver monitoring too are being developed to offer more safety in cars and improve drive quality. The driver monitoring systems, for example, will be able to communicate and create maps, raise an alarm if the driver is falling asleep, detect tiredness, forecast weather, and offer other useful information that will assist the driver. 
3.  Services 
   The post-purchase services can also benefit immensely from the use of AI. The current AI software can already predict things like engine & battery performance to pre-warn the driver. This kind of predictive maintenance utilizes historical data like manuals, IOT data, service orders, etc., to make an assessment independently. In-car assistance too is becoming more mainstream as AI becomes accessible and cost-friendly.  
   AI is also being used in automotive insurance to digitalize and expedite the insurance process. Allowing customers to click and upload damaged vehicle photos using AI apps, allows makes the process smoother and quicker than traditional insurance.