How AI Fleet Management Will Shape The Future Of Transportation
How will AI Fleet Management shape the future of transportation? And which are the best fleet management software solutions? Find out in this article!
Artificial intelligence (AI) is gradually becoming a constant presence in many technological applications. From apps and websites that show accurate user recommendations to gaming predictions, it is changing the user experience in many fields.
Fleet management is one of the areas that AI is disrupting. The growing need to put driver safety first without compromising cost or efficiency has led to the adoption of smart fleet management systems.
For the average driver, the presence of AI can be felt heavily in the use of smartphones and telematics devices that recommend the best routes to take in traffic. This used to be a herculean task marked by paper maps and listening to radio broadcasts of traffic routes; today, we have complex traffic apps that combine GPS and artificial intelligence to make drivers’ lives easier. Fleets benefit from powerful AI-based applications that handle anything from route recommendations to road risk data analysis and even driver coaching. It provides the accuracy, efficiency, convenience, and ease that earlier technology failed to provide. As a result, it is becoming safer to transport goods and services.
What Is AI Fleet Management?
AI fleet management is the use of artificial intelligence-based technology to manage fleet operations. In a constantly changing world, it streamlines the work of any fleet manager by gradually eliminating human error from the transport process.
AI-based recommendations ensure that fleet drivers, managers, and mechanics can make better decisions that improve the long-term performance of the fleet. It also serves as assistive technology, ensuring that drivers retain autonomy during each transport cycle. Here are some key aspects of fleet management that AI can optimize:
#1 Real-Time Fleet Analytics
Collecting data is a key element of any operational process because without analyzing past data, you cannot make informed decisions. With historical insights to inform millions of data points analyzed in real-time, the result is the prioritization opportunities and risks so that fleet managers and drivers can determine the best course of action to take in potentially problematic situations.