Over the last few years, Artificial Intelligence has become a pivotal role in our lives and the business landscape. Irrespective of the industry, AI has simplified processes and empowered business decisions with prediction. When it comes to the transportation and logistics industry, this technology has started impacting the businesses at a greater level.
What challenges does AI solve in transportation?
Be it passenger or goods transportation, the industry has been constantly faced with major challenges. Fleet owners, especially those who operate and manage long-haul trucks face these common problems, such as,
i) Knowing the exact location of their fleet
ii) Educating their drivers about safety protocols and proper handling of trucks
iii) Periodic maintenance and fleet health management.
With the growing intervention of technology in the transportation and logistics industry, businesses have been leveraging innovative solutions to address these obstacles. The GPS-based fleet management system has already been successful in solving the first two challenges to an extent through driver behavior monitoring and analyzing metrics like acceleration, braking and speeding. These metrics are being used by the fleet owners as a prescriptive data points to make corrective actions.
But, what the fleet owners actually require is that all this information to be used as collective and integrated data points that, in turn, automates the entire maintenance life cycle of the fleet and predicts the maintenance cycle and vehicle health.
Artificial Intelligence has been the frontrunner in this aspect with its ability to identify patterns and provide prediction. And that’s where AI can make an enormous difference for the fleet owners.
With all the possible data obtained from GPS and IoT devices, and based on the maintenance records of the fleet, AI can predict the vehicle health based on its utilization and how it is being handled by the operators.
Currently, most of the fleet owners find it very tedious to manage and maintain the maintenance schedule of their fleet. Creating scheduled reminders and keeping a track of them by designating resources is even more complicated. When telematics data come into place, it becomes easy to solve this business problem. Telematics data, generally obtained from the devices and other sources, can be processed to provide appropriate schedule suggestions. This will play a major role in drastically cutting down the operational cost.
With such intelligence at their disposal, the logistics and transportation industry now have the ability to broaden their opportunities and gain increased cost-efficiency and bottom-line results.