Machine learning is the way of the future for fleets. It can be used in all aspects of fleet management, from safety to efficiency. Manual procedures made fleet management challenging and tedious, but machine learning streamlines processes and makes them simple and straightforward. So what can machine learning do for fleet managers, and how can businesses take advantage?
Analytics
Gathering and analyzing data is one essential part of a fleet manager’s job. It helps determine issues and make decisions about what is best for the fleet. Analytics helps with everyday tasks such as route planning. It considers historical traffic data, job information, GPS location, and more to create the most cost-effective route to complete everything necessary for the day. It is also an excellent way to keep vehicles in good condition. Analytics offers ways to track vehicle status, maintenance history, and other details that help maintain vehicles’ good working order.
Maintenance
Maintenance is an integral part of fleet management. Vehicle breakdowns cause significant delays and cost money to the business. Therefore, avoiding them is a necessity in keeping the fleet productive and effective. If vehicles are not adequately maintained, vehicle problems can cause accidents that threaten the safety and reputation of your fleet. Luckily, machine learning can pinpoint issues in your vehicle before they cause breakdowns and let fleet managers know when it’s time to schedule maintenance. This saves on high repair costs later down the line and promotes safety for the fleet.
Safety
Artificial intelligence is one of the most revolutionary technologies to come about for fleets. One primary use is in detecting unsafe behaviors on the road. AI technology such as in Azuga’s SafetyCam dash cam can detect behaviors associated with drowsy, aggressive, and distracted driving and alert the fleet manager so they can take corrective action. The AI can see drivers using their phones, yawning, or losing focus. These behaviors can all be incredibly dangerous and lead to accidents, which damage a fleet’s productivity and reputation. Of course, the top priority is keeping employees and other drivers on the road safe, and eliminating dangerous driving behaviors is the way to do so. The National Highway Traffic Safety Administration found that distracted driving killed 3,142 people in 2019, and drowsy driving killed 1,550. Curtailing these behaviors means that fleets can minimize these accidents, leading to safer roads for everyone.
Efficiency
Machine learning is integral to the day-to-day functions of an effective fleet. Fleet managers can no longer track processes on pen and paper. Simple and even complex tasks can be automated so that managers can focus on making decisions that improve the fleet. As mentioned previously, important tasks such as route planning can be taken over by machine learning, but what about scheduling, dispatching, and managing jobs? Machine learning can bring in data to analyze technician skills and proficiencies and assign them automatically to jobs that are best suited for them. There are many ways that machine learning can help with the assigning and dispatching process.
Conclusion
Machine learning will continue to evolve as time goes on and new uses become available all the time. Soon, fleet management will be more streamlined and straightforward than ever. Azuga is at the forefront of fleet technology and can lead fleets into this new frontier. Find out what options are available to you today by reaching out to the experts at Azuga.
