In the automotive industry, artificial intelligence is being used more and more to lessen human intervention and error. Artificial intelligence improves speech recognition, decision-making, and visual perception on its own. Technologies used for Artificial Intelligence in Automotive-
The automotive sector is about to undergo an incredible transformation. Modern automobiles with Advanced Driver Assistance Systems (ADAS) powered by Artificial Intelligence in Automotive are capable of autonomous manoeuvring and parking. In order to keep drivers alert and safe, cars can even recognise when they are getting tired and send them alerts. These features would only have been imaginable in science fiction movies or books about ten or twenty years ago. But today, things are different. To stay one step ahead of rivals in the market, automakers have begun incorporating cutting-edge technologies in their goods and processes. As a result, IoT technologies like:
Use Cases of Artificial Intelligence in Automotive- 1.Maintenance Planning- One of the best examples of how data science can be used to benefit the automotive industry is perhaps predictive maintenance. 2.Behavior Analytics for Drivers- One of the leading causes of traffic accidents worldwide is driver distraction. Automotive applications powered by AI and Deep Learning can provide a wealth of useful in-car analytics. In order to prevent accidents, cameras and IR sensors can accurately identify the driver's behaviour. 3.Road Conditions Evaluation- Real-time road conditions can be determined by AI-powered automotive applications, allowing drivers to be informed of roadwork, accidents, speed limits, and closures before they set out on their journey. An IoT-based smartphone app was created by the AI/ML engineers at Embitel to analyse road conditions and give drivers the best navigational assistance possible based on those conditions. Based on potholes, speed bumps, and road closures, this app chooses the route that will be the most efficient for the journey. Around 100 metres before the driver reaches the hump or pothole, another warning is given. Tech Trends for Autonomous Vehicles In a matter of milliseconds, autonomous vehicles view, perceive, and decide. Computer vision, machine learning, and AI technologies make it easier to evaluate the outside world. Additionally, edge and cloud computing applications collaborate to transform enormous amounts of vehicle data into timely, useful insights.
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