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How Far is AI going in the Transportation Industry?

By Logistics Tech Outlook | Thursday, May 30, 2019

Transportation FREMONT, CA: With the advent of industrial metamorphosis, the automotive industry has seen a remarkable transformation in appreciation to artificial intelligence (AI). The integration of AI and machine learning in the automobile industry has helped to reduce costs, optimize products, and accelerate development cycles. The inclusion of virtual reality, internet of things (IoT), and real-time simulations have crippled the traditional practices and cemented automotive industry as a leader of technological advancement. The 3D augmented virtualization and embedded AI platforms not only enable the manufacturers to undergo innovations but also entrusts workers with a statistical flowchart for placid workflow procedure. 

Presently, with over 1.2 billion vehicles on the road, which is likely to cross 2 billion by 2035, will exponentially increase the fatal accident rates. According to the World Health Organization, an unexpected 1.25 million accidents are encountered every year and with the increase of automobiles, the numbers are certain to escalate eventually. Automotive manufacturers along with regulatory bodies, are empowering AI to undermine the fatality of future roads and make the travels increasingly convenient. The vision of connected cars will reduce the probability of collision and make the avenues risk free.

The potential advantages obtained from the integration of blind stop monitoring, adaptive cruise control, lane-keeping technology, collision avoidance are practically limitless. The AI-powered virtual assistants embedded into the cars disclose an informative behavioral study that can anticipate and pre-determine errors. AI-powered geo-locators not only operate as a guiding tool for the driver, sailors, and pilots at any geography or terrains but also designs routes to exclude accidents and traffics. The transportation companies are utilizing machine learning to analyze previously recorded data to detect active automotive influx and minimize traveling time.

In recent times, AI and machine learning capabilities have far exceeded to become a crucial part of automobile machinery. The advancement is creating a great risk of overdependence on digital and autonomous systems. The autonomous approach is yet to attain the powers established through manual control but with the rise of AI, the industry leaders are positive to bring a change.

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