When thinking about artificial intelligence in the automotive industry, the first thing that comes to our minds is self-driving cars. But AI can do much more than just drive vehicles.

AI is increasing its foothold and importance in the automotive industry. Its value is expected to reach almost $16 billion by 2027.

Let’s take a deeper look in on artificial intelligence and its subset machine learning to see how applications of AI are impacting automotive manufacturers, vehicle owners, and service providers.

Self-Driving and Autonomous Vehicles

This is probably the most popular application of AI. However we should know that cars equipped with this technology offer two levels of autonomy: a self-driving system or a fully autonomous mode.

Self-Driving Systems and Driver Assistance

These solutions allow the AI to take the co-pilot’s seat in the vehicle. Such applications help everyone from customers and manufacturers to regulators in becoming comfortable with AI as a driver before turning to fully autonomous vehicles.

AI can identify dangerous situations by monitoring data coming from many different sensors and take emergency control of the vehicle to avoid an accident. Blind-spot monitoring, emergency braking, or cross-traffic alert monitors are just a few examples of how AI improves driving.

Autonomous Vehicles

The combination of AI, machine learning algorithms, and cloud technologies is the key to fully autonomous vehicles. We’ve already had the mechanical systems required to control the vehicle braking, steering, and acceleration for many years. What was lacking was the brain to control all of it.

AI promises to fulfil this goal. First of all, the amount of processing power required to drive the vehicle is gigantic and conventional computers aren’t up to the task. This is where cloud computing comes in. Together with sophisticated machine learning algorithms, cloud technologies allow machines not only to perform tasks but also to learn from them.

Smart Manufacturing

AI impacts the end product that actually interacts with the consumer, but it also plays a critical role in revamping the entire manufacturing process of automotive companies.

For example, assembly-line robots that have been part of vehicle production for more than half a century now are now transformed into smart robots that work together with humans. Kia Motors is already using robotics technology via the development of the Hyundai Vest Exoskeleton (H-VEX) wearable industrial robots. These robots enhance the manufacturing process and help the overall production.

Another example is automated guided vehicles able to move materials around factories without human intervention. They can identify objects on their path and then adjust the route easily. You can also find painting robots on manufacturing floors that follow the pre-programmed standards and instantly alert quality control personnel of any identified defects. All of these features are powered by AI to shorten production time without affecting its quality.

Predictive Maintenance

The application of artificial intelligence and cloud platforms ensures that relevant data is available whenever needed. This powers systems like predictive maintenance, which relies on connected devices sending alerts via sensors.

Conventional vehicles can alert us about maintenance requirements by low battery indicators, check engine light, or oil light. This differs entirely from the possibilities offered by innovative connected vehicles equipped with AI software that monitors hundreds of sensors located all around the vehicle, capable of detecting problems before they affect the vehicle’s operation and the driving experience.

Manufacturers can offer predictive maintenance and over the air software updates for the entire brand of vehicles to help to enhance the customer experience and lower the cost of maintaining their products.

Marketing Personalization

Many industries are experiencing increased competition and struggle to keep customers engaged with their offers. This opens the door to personalized marketing delivered via intelligent vehicles. Companies can use AI to target an audience of qualified prospects with the most relevant messages at the right time.

AI connected with Big Data and vehicle infotainment systems can suggest products and services to drivers on the basis of their personalization profiles.

For example, a driver who announced a wedding on social media can be alerted for sale at the bridal store just around the corner when driving. If the vehicle experiences low fuel, the system can automatically suggest the nearest gas station that is included in the system. AI will learn its drivers’ needs and notify them when they’re close to a business that might serve them.

AI-Powered Automotive Insurance

The insurance industry and artificial intelligence are both about predicting the future. No wonder that insurance has embraced the use of AI automotive insurance solutions to help make more accurate risk assessments in real time.

For starters, AI accelerates the process of filing claims when accidents occur. But it can do many more things. AI can recreate risk profiles based on drivers’ individual risk factors found in the data and look for many less obvious factors that predict how safe the driver is likely (considering anything from their health issues to personal matters and diet).

Another interesting use of AI is for Do-it-Yourself auto damage assessment. Art Financial published an application to the Chinese auto market powered by AI that enables drivers to carry out their own auto damage assessment for insurance companies. The on-screen instructions show users how to video their vehicle damage for insurance claims and suggest what will be covered by insurance.

Driver Monitoring

AI doesn’t only drive but also helps to keep an eye on the driver. For example, the automotive computer vision start-up eyeSight uses artificial intelligence and deep learning to offer a broad range of automotive solutions:

  • It uses advanced Time-of-Flight (TOF) cameras and IR sensors to detect driver behaviour in four key areas of driver identification, checking whether or not the driver is in the vehicle.
  • It can even implement driver recognition using advanced AI algorithms that detect when the driver is operating the vehicle. For example, every member of a family might have their own preferences and the system can automatically adjust the seats, temperature, and other factors to match the individual.
  • Another solution is driver monitoring. For example, by observing the driver’s gaze, head position, and eye openness, the software can detect distracted driving and alert the driver to keep their eyes open on the road. Drowsiness can be detected by eye openness and head position as well.
  • Moreover, contextual controls allow AI to tailor the content of the heads-up display according to where the driver’s eyes are focused. In case of a crash, the system will release airbags in a way based on how the driver was sitting, thanks to body detection features.

Conclusion

Innovations based on AI and ML are empowering the Automotive industry significantly. As a result, the sector has now started offering better products and services to customers with excellence.

We at AppleTech have the experience, expertise and the knowhow to leverage the most innovative approaches in building portals, mobile and web applications for the automotive industry as well as many other domains. Come to us with your idea and watch it develop into a solution.

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