Artificial Intelligence, a revolution that has taken the world by storm. Spanning various industries and an extensive spectrum of applications, we live and breathe AI. An industry greatly influenced and benefited by this massive phenomenon is the Automobile Industry. From self-driving cars, electric vehicles to driver and vehicle health monitoring systems, AI and ML have sunk their roots deep into the mobility ecosystem. Let’s see what role AI and ML will play in transforming the automobile industry in 2022.
Electric Vehicles (EVs)
With Artificial Intelligence and Machine Language taking center stage across numerous arenas in the automobile industry, the EV sector is the most prominent. In stark contrast to the traditional IC engines that are a product of 100+ years of research and development, the EV is still at an evolutionary stage and is yet to be fully embraced across mainstream vehicle platforms. However, as concerns for planet-friendly and emission-free transportation grow more profound, the focus on EVs as the next automotive frontier is poised to increase.
Electric Vehicles have provoked an immense stir in the market with attributes like sustainability and efficiency at the forefront. As an added advantage, automobile manufacturers are constantly amplifying their efforts to introduce a vast set of AI-driven features. Machine and deep learning algorithms are being used to build complex driver monitoring systems that analyze driving patterns and cognitive behavioral functions like drowsiness and alcohol-induced inebriation detection and security facets like biometric authentication.
Another crucial aspect constantly being worked on is range prediction in EVs. In addition to driving behavior attributes like acceleration, braking, and average speeds, battery management systems are influenced by ambient variables like temperature and humidity. Automotive researchers are conducting comprehensive research and are engaged in developing complex algorithms that analyze all these conditions and increase the accuracy of the range prediction models.
Charging infrastructure is crucial to the mass adoption of EVs. Harnessing the power of Artificial Intelligence, efforts are being made to develop systems that reference geospatial data to recommend proximate charging stations with cognizance of rapid or slow charging facilities according to the requirement of the vehicle at a given juncture.
Autonomous Vehicles (AVs)
Edging a step closer to the vision of flying cars, we have assembled ones that can self-drive. The A in AVs can be indubitably ascribed to Artificial Intelligence. Cognitive intelligent systems employ neural networks to offer radical features such as blind-spot monitoring, traffic analysis, and driver-assist steering to prevent accidents and maintain safety standards. Other added advantages introduced through AI, including adaptive cruise control and autonomous parking, further contribute to driving convenience. From Robo-Taxis and Autonomous Delivery Solutions to Advertising Vehicles, the AV market continues to grow at an extraordinary pace.
Motorsports
The world of Motorsports has caught the AI bug as well. Artificial Intelligence is influencing auto racing in various ways. Features like surrogate modeling to speed up simulation turnarounds, revamping traditional engineering and design solutions, and even segmenting the fan base for improved advertising are all boons of AI. Another splendid use case of AI in racecars is the ameliorated safety brought about by assessing massive datasets of historical and real-time data. Driverless racing is another arena that is steadily being reared into existence by the upsurge of AI.
Vehicle health diagnostics
Advanced health monitoring platforms are leveraging the power of AI to deliver highly efficacious remote diagnostics. Digital Twins of drivetrain components are being used to generate predictive insights for use cases such as overheating, battery charging, and fuel-air charge composition. Furthermore, comprehensive reports on fuel efficiency-pilferage, driving performance, routes-schedules, and performance of emissions control systems are made available with minimal manual intervention. Utilizing AI to predict possible malfunctions reduces downtime and curtails the risk of mission-critical breakdowns. This leads to elevated toplines and reduced costs incurred on maintenance and repairs.
Enhancing manufacturing
The future is demand-specific, and applying AI to Supply Chain Management and Manufacturing will ascertain smarter and swifter production methods. Designers and product developers can generate roadmaps using the abundant data on usage and preferences procured over time and construct models that will be well-received. Robotic assembly lines can expedite cost-saving and productivity by damage and accident reduction.
Boosting sales
Apart from the technical advantages, AI can also positively impact the financial numbers by carrying out customer profiling. Modernistic automobile recommendation systems offer a seamless customer experience for purchase and auction. With the launch of numerous automobile recommendation platforms, the sales numbers achieved via digital customers in recent times are staggering.
AI and ML have the potential to redefine every aspect of our life. In the case of the automobile industry, these technologies are proving invaluable in both mitigating and resolving several challenges, especially with regard to EV adoption and developing planet-friendly automotive technologies. The universe of AI and ML is full of endless possibilities; an amalgam of these is an era of stupendous digital transformation.
Disclaimer
Views expressed above are the author’s own.
