Application of artificial intelligence in the automotive industry
Application of artificial intelligence in the automotive industry
Mohammadreza Moradi1 Sam Ghobadi2 Kourosh Ali Akbarian3 Yasin Haji Abed4
1) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
2) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
3) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
4) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
Publication :
3rd International Conference on Recent Advances in Engineering, Innovation and Technology - Belgium(eitconf.com/3rd)
Abstract :
Application of Artificial Intelligence in the Automotive Industry Abstract Artificial intelligence (AI) has had a wide impact on the automotive industry in recent years, causing significant changes in the fields of production, safety, productivity and user experience. This technology has optimized production processes and made driving safer and smarter through machine learning, computer vision, natural language processing and big data analysis. One of the most important applications of AI in this industry is the development of self-driving cars, which enable automated driving using advanced algorithms and smart sensors. Also, advanced driver assistance systems (ADAS) play an important role in reducing accidents by providing capabilities such as automatic braking, lane departure warning and blind spot detection. In addition, AI helps optimize the supply chain, predictive maintenance and improve user experience through entertainment systems and smart assistants. Despite the many benefits, challenges such as high costs, security issues, the need for extensive data, and regulatory regulations still exist. This article examines the main applications of AI in the automotive industry, the benefits, challenges, and the future of this technology.
Keywords :
artificial intelligence
self
driving cars
driver assistance systems
supply chain
predictive maintenance
automotive industry
machine learning
computer vision