New cars are in short supply, with delivery times stretching up to a year due to ongoing shortages of semiconductors and other supply chain issues.
This is affecting customers of all kinds, but none more so than fleet buyers. The shortage means that many fleets, from car rental companies to police departments, are unable to replace vehicles as frequently, leading to a growing reliance on older vehicles and increased resources devoted to keep them.
Instead of simply replacing vehicles, which was often the previous strategy because it was more cost effective than making repairs or keeping up with ongoing maintenance, fleet managers need to invest more in inspections, monitoring and repairs.
One way they can ensure the vehicles they deploy remain safe and in the best possible condition is by using artificial intelligence solutions that increase driver responsibility, examine a vehicle’s performance and determine ways to ensure it meets standards needed to ensure safety and efficiency, as well as recommend ways to bring vehicles up to code or identify problems before they cause problems.
For many people, the term “fleet” brings to mind rental cars and taxis. But the fleets include police and rescue vehicles, transportation for government safety screeners and regulators carrying specialized equipment, vans and delivery trucks to bring much-needed supplies to consumers and institutions like schools and hospitals, and much more.
Operators of these fleets need vehicles they can really trust; and if they fail, that could put lives in danger.
Until the backlog is removed from the supply chain — and that could take years, experts say — fleets of all kinds will have to make do with what they have. To do that, they will have to go beyond the usual inspection and repair procedures that they have relied on in the past.
Artificial intelligence can help with these deep dive inspections, using easy-to-operate mobile apps alongside standard vehicle equipment like security cameras to routinely document the status of fleet vehicles.
This creates an objective and up-to-date record. Apps can remind drivers to file an inspection report when they start and end a shift, and cameras can record vehicles and details about their condition as they enter and exit services. All of this data can be uploaded to a central server, where advanced data analysis tools can process the images, cataloging them in an easy-to-use format for review by fleet managers, body shops, inspectors and other vendors.
Meanwhile, sensors can track data on driving habits, brake usage, wear and tear, and other internal vehicle data. Based on the analysis of all this data, the AI tools can make recommendations about the necessary services or the expected problems and repairs.
Tracking driving habits and current vehicle conditions also makes drivers more accountable, ensuring the vehicle is treated better, aware of its condition, and picked up and returned on time. This can also help extend the life of a vehicle, or at least keep it in better shape.
The widespread use of AI in these inspections will not only make driving and vehicles safer, it will also reduce the labor required to ensure vehicles are roadworthy.
Most of these inspections are now still carried out manually, which means they are labor intensive and subject to human error. Automating the inspection process through advanced data analytics will help ensure inspections are performed regularly, without the risk of fatigue-induced errors.
Advanced AI analytics systems could make the difference between poor and ideal performance, perhaps even between life and death.