Artificial intelligence is one of the most important parts of the human future. Artificial Intelligence (AI) allows machines to learn from experience, adapt to new inputs, and perform human tasks. Most of the artificial intelligence examples you hear about today - from chess computers to self-propelled cars - rely heavily on deep learning and natural language processing.
And how does AI affect the automotive industry?
Experts still consider AI transformation in the automotive industry to be slow, despite 80% of all industrial players naming AI as their core strategy. So there is a great missed opportunity from which your company can take advantage. However, the benefits it offers for the automotive industry are currently a trend. Car manufacturers and technology companies strive to develop the best technology of artificial intelligence and automating.
The application of artificial intelligence in the automotive industry is not limited to autonomous driving. AI and machine learning also help to keep us safe and connected. Moreover, it is the emerging technologies that are now used in the production process. The automotive industry uses evolving technology to emulate and support human action. Today's connected vehicles and future cars will rely on AI systems. To determine the place of machine learning and artificial intelligence in the automotive industry, we can give some examples of use.
AI and autonomous control are inseparable. Autonomous driving brings news in the automotive industry, driver assistance powered by artificial intelligence has become quite a widespread function that drivers now expect in their cars. The AI monitors dozens of sensors and can instantly respond to hazardous situations by alerting the driver, emergency braking or emergency vehicle control. Artificial intelligence and machine learning are also successfully used in navigation software, blind-spot monitor, and easily facilitate drivers, for example by adjusting the seat and mirrors and designing entertainment.
AI recently introduced the term “predictive maintenance” in the automotive industry. This makes AI a real player in this domain the ability to aggregate and analyze large data from multiple sources: vehicle sensor data, historical maintenance records, and weather data. In this way, AI makes it possible to detect problems before they affect the operation of the vehicle and to prevent sudden failures when the assets are operated at the highest performance.
In recent years, the insurance industry has adopted the use of artificial intelligence in connected vehicles to help gain access to risk in real-time mode and speed up the complaint process in the event of an accident. AI takes into account individual driver factors and recent events, not just driving history, to create accurate risk profiles. Also, technology such as Dingsunbao 2.0., A popular application in the Chinese automotive market, has allowed drivers with management and tools to make their assessments of car damage by insurance companies.
The dissemination of AI has had a major impact on the production of cars. One notable change in recent years has been the emergence of intelligent and wearable robots that now work with their human assembly line counterparts, not their counterparts. Such collaborative robots understand what people are doing and adjust their movements to avoid injuries. Besides, AI-powered painting and welding robots can now identify material defects and alert quality control personnel. Automated Guided Vehicle (AGV) is another technology driven by artificial intelligence that has been used in automobile manufacturing. AGVs rely on artificial intelligence and no human assistance, identify loaded objects, modify their routes, and deliver materials to various parts of an automobile race.
Artificial intelligence allows you to automate not only predictive maintenance but also other supply chain processes such as demand forecasting and production planning. For example, FPT-Software has developed AI-powered solutions that can automatically calculate the remaining storage space and recommend the best loading options for a particular product type in a particular warehouse semi-automatic inspection and loading of packages into the truck, using cognitive visual recognition to assist in product inspection before acceptance into the warehouse automatically count the number of interchangeable lifting cranes in ports, etc. AI chatbots have also been successfully used to accelerate the process of filing your documents and order queries.
While some manufacturers have focused on helping drivers track the road, new AI applications have been launched to track drivers. AI software can detect if the driver is in his vehicle and also automatically adjusts the seat, mirrors and even temperature when one of the regular car users reaches the driver's seat. Head position and eye openness allow the software to detect drowsiness and wake the driver, while gesture recognition has become a useful way to manage infotainment as you type. AI software can even analyze the position of the upper body during an accident and adapt the deployment of airbags accordingly.
Connected vehicles generate a considerable amount of data. Autonomous cars are expected to earn 4,000 GB per day. AI cloud platforms ensure that all this data is available whenever it is needed. To target qualified leads in personalized marketing, you need to go through unclassified data, which is very impractical. But AI-based cloud platforms are the perfect solution. Their interconnection with large vehicle data and information systems can be used to provide drivers with personalized suggestions. The power of AI, in this case, is that it knows the driver and can make relevant offers based on its location.
And what do you envision the future of the automotive industry within AI?