Innovative Artificial Intelligence Integration in Automotive

[vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column][vc_column_text]While today’s market conditions are being reshaped by technology, an important way for companies to create a competitive advantage in tough competitive conditions is to invest in innovation. Compared to other sectors, the automotive industry focuses more on technological innovation. In the field of innovation investments, companies have turned to autonomous driverless vehicles, vehicles operating with different fuel alternatives and futuristic designs equipped with artificial intelligence technology.[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column]

Automotive and Artificial Intelligence

[vc_column_text]The introduction of artificial intelligence technology to the automotive industry has ushered in a new era in the sector. It is stated that OEMs (Original Equipment Manufacturers) are investing billions of dollars to design vehicles for connected, autonomous, shared and electric (CASE in industry parlance) mobility. According to experts, the global market integrated with AI is expected to witness a compound annual growth rate (CAGR) of 39.4 per cent during the forecast period of up to USD 20.76 billion from 2022 to 2030.

With the integration of artificial intelligence, viewing the vehicle from a mobile phone or computer, IoT and other technological elements into vehicles, there has been a revolution in the automotive industry. Artificial intelligence technology is now on the stage at every stage, not only in design, but also in sales, after-sales support, training, complex processes in the supply chain and planned efforts for customer satisfaction. Artificial intelligence is reshaping the automotive industry.[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column]

Major Artificial Intelligence Integration Models

[vc_column_text]Artificial intelligence technologies such as machine learning, deep learning and computer vision take place in the automotive industry in the field of robotic automation. It contributes to faster, more error-free and less costly production. Artificial intelligence is used to create advantages in the provision of different types of services such as fleet management, driver safety measures, insurance and traffic inspection, driver alerting, facilitating automotive production, testing or preparation processes. The main usage models are as follows:

Autonomous vehicles: The autonomous vehicle (AV) is a concept that originated at the 1939 New York World’s Fair. This dream dates back to the autonomous vehicle project of industrial designer Norman Bel Geddes. It is stated that autonomous vehicles, which are the subject of investments by many automotive and technology giants, still need decades to be realized.

Collaborative Robots: Cobots, also known as collaborative robots, are translated into our language as collaborative robots, and are defined as robots that enable safe working by interacting side by side with humans in a common working area. By working together with employees; It provides intelligent and functional services in areas such as assembly and inspection without human errors.

3D Printers: 3D printers make a difference in the production and supply of parts for the automotive industry. The use of 3D printers to create prototypes in the industry; It is preferred with its advantages such as fast production times, low cost and the ability to produce complex geometries and the possibility of control during the preparation phase.

Smart Helmets: Equipping helmets with artificial intelligence technology for driver safety gave birth to smart helmet technology. Smart helmet technology, which connects to the phone with applications running via Bluetooth, provides the use of the features required for comfortable driving. Smart helmets offer various possibilities such as noise reduction, volume control, access to map information, automatic search after an accident, and the driver can talk to multiple people at the same time.

Machine Vision: Machine vision is generally defined as the technology and methods used in industry to provide imaging-based automated inspection and analysis to optimize different processes, such as automated inspection, process control and robot guidance. In automotive, it is used to minimize potential errors and risks.

Automated Guided Vehicles: Automated Guided Vehicles (AGVs) are driverless mobile vehicles that are programmed to transport materials in a facility. They are used in the automotive industry because they prevent injuries to employees and are more efficient than manpower. It also provides maximum savings in warehouse utilization.

Driver Monitoring System: The driver monitoring system is used to make the necessary warnings for driving safety and thus provide warnings in some problems that will cause accidents. By following the driver’s eye movements, it detects situations such as sleep or dizziness.

ARTIFICIAL INTELLIGENCE Cameras: Designed to ensure driving safety, this technology continues to be developed with methods such as image processing, pattern recognition and deep learning through artificial intelligence.

Vehicle Tracking Software: It provides detailed information on fuel, speed, engine, etc., as well as being used for route determination with its advanced map feature and vehicle location detection in cases such as accidents or disappearances.

Automotive Insurance: Artificial intelligence display instructions on how to video the damage and then submit it for an automotive insurance claim, as well as reports such as repair recommendations, total cost covered by insurance, etc. Allows the driver to make their own auto damage assessments, if necessary, to be reported to insurance.[/vc_column_text][/vc_column][/vc_row]