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AI: The Future of Fleet Management


As technology continues to evolve, more and more data is created, making it nearly impossible for humans to see and process every bit. But artificial intelligence (AI) can help us meet the challenge. As the demand on national transportation infrastructures grows exponentially, fleet managers will have to turn to AI to stay competitive.

Artificial Intelligence: What is it and How it works

Artificial intelligence, or machine learning, looks at the large volumes of data your telematics system produces and analyses and reports on that data in a clear and concise way. AI spots patterns and behaviours and can make recommendations based on the data.

AI develops expertise and offers not only the usual alarms and status alerts but also observations about the future. It recognises patterns that are hidden in the data and helps you to answer the questions that you don’t know to ask. This is the biggest difference between artificial intelligence and business intelligence, where business intelligence relies on you knowing what questions to ask, artificial intelligence uses data to identify the biggest influencing factors on outcomes and provide recommended adjustments.    

The role of AI is to simplify data management and help fleet managers identify problem areas before they become an issue and help create real-time coaching and training programs.   

So, What Can AI Do?

AI factors in prediction with cause and effect and anticipation to streamline fleet operations. The three things AI will likely be able to do based on the data available in your telematics system are:

  • This seems familiar (Prediction): We have seen “X” scenario before and “Y” was the result. In other similar cases, these situations tended to emerge. For example, in engines of this model vehicle, rising temperatures tend to indicate a gasket repair is needed. Or, when we serviced this type of customer in the past, we experienced delays due to backups at the loading bay.
  • I’ve noticed when this then that (Cause and Effect): More frequent oil changes on this type of engine seem to make a big difference in fuel economy. Or, when we send 10-minute ETA notifications to customers, on-site wait times drop by 25 %.
  • Based on historical data, this is likely to occur (Anticipation): Driver A has more than 50 harsh-driving incidents each day. At this rate, the total vehicle ownership cost will increase by 15%. AI has noticed that reducing harsh driving generally increases vehicle lifespans and reduces fuel consumption.

AI Growth & Value

AI technology is already disrupting the way we move people and goods. From observing traffic patterns to reducing fuel cost and optimising driving routes to reducing traffic incidents. AI is creating opportunities to make transport safer, more reliable more efficient and cleaner.

AI Growth in Transport

While decision-makers recognise the value of AI, many aren’t as familiar with the tech and its huge day-to-day benefits. Business leader will need to clearly demonstrate how AI will positively impact drivers and staff across the organisation.

Understanding the Value of AI

AI automatically transforms big data into digestible reports, visual dashboards and actionable insights that help businesses to make decisions. It is this power that helps businesses make more data-based decisions that are proving to help with cost reduction and revenue increases.

AI Businesses Uses


AI and Onboard Cameras

There are two powerful benefits of AI-equipped onboard cameras. One is incident reduction through driver assistance where drivers can be alerted to potentially dangerous actions. The second is the capability to measure driver behaviour including fatigue, distracted driving tailgating and a wide range of road violations, enabling fleet managers to easily build a picture of fleet wide and individual driver safety.  

With an integrated AI dashcam from Teletrac Navman, businesses can:

  • Measure driver behaviour that standard vehicle telematics cannot
  • Build fleet wide and driver safety scorecards
  • Gameify driver safety with incentive programs
  • Be proactive in driving training and one-on-one coaching

What Data Can AI Interpret?

AI relies on data, and lots of it, to learn about operations and provide insights and predictions. Telematics systems capture an ever increasing volume of data from a wide range of data points which can be pulled into an AI processor. These include but are not limited to:

  • Engine diagnostics ODB2 and J1939 / CAN bus data
  • Runtime data
  • Maintenance data
  • Fuel usage data
  • Idle times and location data
  • Driver hours data
  • Dangerous driving event data
  • Distracted driving event data
  • Fatigue data
  • Vehicle/asset utilisation data

AI’s Future as Seen in Other Industries

Many industries have embraced AI technology already. Factories and hospitals have benefited significantly from AI that optimises maintenance processes and looks for signs of potential downtime before the incident occurs. Here’s a look at how other industries use AI:

Healthcare: Healthcare is one of the most active users of AI technology, incorporating AI into virtual doctor visits and using robotics in surgery. Hospitals all around the country are using AI to make more accurate diagnosis and creating individualised treatment paths for patients.

Manufacturing: Manufacturing process disruptions can cost tens of thousands of dollars per hour for downtime. Machines equipped with cameras can make real-time quality checks, detecting even the smallest defects, and predictive maintenance keeps machines running at maximum capacity.

E-Commerce: E-Commerce sites such as are using AI technology to increase sales, reduce shopping cart abandonment and predicting inventory needs. AI-based tools help companies forecast sales and manage inventory.