“The most vital AI trends of the Automotive Industry”.

Evolutions in technology have been bringing new inventions, discoveries and new insights to make life simpler and safer, in every field. Be it home appliances, automobile, healthcare and many more, there is no dearth for options now, and the advancements seem to reach unimaginable heights. It is not an exaggeration if we say that the technology is taking over the common lives of common people.

When it comes to automobile industry, it is in commotion with innumerable technical advancements and strategic shifts promising a world which is very close to our fantasy days of flying or driverless cars. Not only this, but AI is making long distance driving safer, convenient and less taxing, and is the best example of displaying the fact how innovation is shaping the future of automobile industry.

A focus on automation

Over the past few decades, automotive hardware has become intricately linked with software due to which the ‘driver assists’ have been connected to various computers which help in monitoring the car performance. Today, driver assistive technologies such as lane departure warning, emergency braking, collision avoidance and blind spot warning are available even in mass-market cars.

A future where we tap out our destination into a smart-phone, step into a vehicle, and are driven there by ‘a computer’, is not far, bringing the best of artificial intelligence and machine learning to function. Let us look at a few of the artificial intelligence trends which are sure to make a mark and are surely here to stay:

Machine Learning

Machine learning, a branch of artificial intelligence, excellently attempts to replicate the way in which humans learn (i.e. by repetition of tasks using historical data).  Using AI, the machine is not only autonomous, but they are made capable to communicate with other vehicles/drivers in the vicinity

Toyota has gone a step ahead and has brought together Big data, Machine Learning and Artificial Intelligence to generate highly sensitive autonomous systems that support in the movement for those to help an ageing population mobile and ensure they can still use their cars.

Deep Learning

Deep Learning is the process by which machine learning is implemented, and it enables carrying out many AI-related tasks without any setbacks. In automobile industry, DL enables breaking a huge task into multiple smaller tasks, making the advanced driving assistance systems and autonomous driving possible.

Lately, Nvidia and Bosch’s partnership came into the picture, they are working together to enhance the quality and characteristics of autonomous vehicles. Bosch is in a process to develop a supercomputer that will be installed in such vehicles, and Nvidia is working on to produce the Deep Learning technology to power it.

Internet of Things (IoT)

IoT in automobile intelligence is slated to bring in revolutionary changes in the way vehicles will be equipped with myriad of sensors, connectivity platforms, geo-analytical capabilities and analysis methods for Big Data. IoT is set to become a fundamental link in integrating these different systems into a single unified platform, and allow manufacturers with additional features such as:

• Smart, integrated way of monitoring the vehicle performance to analyse when repairs or replacements of component parts are needed.
• Data from sensors and other input methods sent directly to manufacturers so adjustments or tweaks to operational systems can be made in future production programs.
• Fleets of vehicles can be managed more efficiently and reports on fuel usage can be generated and shared in real-time.
• Dealers and manufacturing companies can diagnose issues and prescribe repair options without a customer physically visiting a repair shop.
• Smart sensors to detect potential health or impairment issues with drivers and summon essential personnel to protect the driver and other motorists.

Risk Identification and Emotion Detection

The possibilities of what Machine Learning can do are endless. Can you imagine a machine trying to identify what a human is expressing by uploading pictures through ML algorithms and calculate probabilities of your emotions such as joy, anger, sadness and so on. Looks like even the thinking of a human being will be controlled by ML now.

However, identifying such signals in human drivers coupled with AI-assisted cars will help reduce the risk of road accidents due to fatigue. Also, Automotive AI could be used to identify if a driver was under the influence of drugs or alcohol.

Robotics and Defect Detection

Undoubtedly, AI is pushing driverless car revolution and improving safety, it has also been embracing the new technologies which are making the functionality further better. One best example is the Robots are in function in automotive manufacturing plants for ages, but now they are being used to reduce the manufacturing downtime by leveraging sensors and complex algorithms to monitor manufacturing tasks round the clock.

Also, AI-based algorithms can digest masses of data from vibration sensors and other sources, detect anomalies, separate errors from background noise, diagnose the problem, and predict if a breakdown is likely or imminent.

Conclusion

Through Artificial Intelligence capabilities, you can witness a new kind of car driving – the “cloud to car” phenomenon. Thanks to tremendous computational power that’s available at their disposal developers have been able to create apps that have taken artificial Intelligence to a whole new level of excellence.

And it is not just about cars that drive on its own, and act as a real driver would in various circumstances, AI would also help in building cheaper cars that can sense the environment and navigate through all the hindrances that may come up during driving.

Author : Pushpalatha Kowlgi