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Role of Artificial Intelligence in Future Vehicles

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Role of Artificial Intelligence in Future Vehicles

The integration of IoT devices and AI capabilities enable vehicle manufacturers to update their items with new features like predictive maintenance and smart sensors.

· AI Zone ·
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Films like The Fifth Element and Total Recall introduced the concept of autonomous vehicles to our collective subconscious and, in a way, inspired tech firms and car manufacturers to develop driverless technology. The idea of AI-powered vehicles (such as self-driving cars, unmanned public transportation buses, and pilot-less areal vehicles) however, has now been around for some time. Are we any closer, though, to realizing the potential of AI in automobiles of the future than we were a decade back? Let’s explore.

The Current State of the AI Automobile Truth

2022 is all set to be the year when global automobile makers will move majorly to the autonomous vehicle manufacturer. Nissan and Delphi, for instance, have released official press statements claiming the same. Small-scale autonomous public transportation experiment has already been carried out in China. The truth is, we are on the cusp of an AI-powered vehicle revolution, and things are only going to change further as technology improves.

Role of the Internet of Things (IoT)

Thousands of smart devices are connected to the Internet on a daily basis, from smartphones to health monitors. According to Gartner, more than 250 million vehicles are expected have online connectivity by 2020.

As vehicles rely increasingly on electrical parts, software, and technology, manufacturers must collaborate with software development and other teams in the tech sector to successfully develop IoT-enabled vehicles. And, if that’s not all, the integration of IoT devices and AI capabilities will enable vehicle manufacturers to update their items with new features, such as:

  • Repair scheduling
  • Automatic toll collection
  • Performance issue identification
  • Predictive maintenance
  • Smart sensors for medical emergencies.

How Emotion Detection and Risk Identification Can Help

Microsoft, IBM, and Social Opinion have developed sentiment analysis APIs capable of detecting emotion in streams of text. But it’s one thing to gauge the mood in a document and another to detect how a person is feeling. Thanks to the advancement of technology, however:

  • Uploading and processing pictures via machine learning algorithms enables us to calculate key emotions, like sadness, joy, anger, and so on.
  • Identifying such signals in human drivers can allow AI vehicles to reduce the chances of road accidents from fatigue.
  • Emotion detection software in vehicles can also help identify if the driver is under the influence of alcohol or drugs.
  • Users can still rely on AI-savvy insurance companies to bail them out as far as claims and collision are concerned.

Greater Fuel Efficiency

Tesla is leading the fuel-efficiency movement, launching various hybrid and electric models that require only a single charge to traverse hundreds of miles. According to The Financial Post, over two million electric vehicles were sold around the world in 2016. And this figure will only increase as more automobile firms adopt electric vehicle technology.

For example, companies such as General Motors and VW have recently added electric vehicles to their product lineup, and Volvo has mentioned how all their engines will feature an electric motor by next year. The increasing affordability of electric vehicles might also have something to do with it, as companies such as Toyota, Hyundai, and Kia are releasing hybrid cars worth less than $30,000.

Robotics and Detection of Automobile Defects

There is little doubt that AI is helping us move toward a driverless vehicle revolution that is sure to improve road safety in the long run. But implementing AI in automobile manufacturing plants also has its share of advantages.

Robots may have been a staple of automotive manufacturing plants for years, but according to a McKinsey report, the addition of AI can:

  • Significantly decrease downtime by leveraging complex algorithms and sensors to monitor the manufacturing equipment around the clock.
  • Increase equipment availability by over 20 percent, lowering inspection costs by almost 25 percent.
  • Reduce the total annual maintenance expenses by a maximum of 10 percent.
  • Detecting anomalies more precisely than humans, and hence vehicles being produced will boast better quality.
  • Forecast orders, thereby decreasing excess stock by nearly 50 percent.

Concluding Remarks

AI is changing and improving various aspects of the mobility industry, and as time goes by, manufacturers and customers alike will understand how they are driving business efficiencies as far as cost is concerned through multiple steps of the distribution and manufacturing process.

ai ,autonomous vehicles ,iot ,emotion detection ,risk identification ,robotics

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