For years, fleet monitoring consisted of knowing a vehicle’s location and reacting when an incident occurred. Today, the challenge is different: interpreting large volumes of information in real time to anticipate risks before they affect operations.
For María de los Ángeles Useche, Commercial Director of Total Protect , artificial intelligence (AI) is beginning to accelerate this transition. More than just automating tasks, it allows for the simultaneous analysis of variables that were previously isolated, such as speed, routes, weather conditions, driver behavior, and road history, transforming them into preventative alerts that help in making decisions before an accident or attempted robbery occurs.
Useche told T21 that the main challenge currently facing transport companies is not the lack of information, but the ability to process it quickly.
“I would sum it up in one word: immediacy,” he stated.
He explained that AI allows processing large volumes of data virtually in real time , making it possible to handle a greater number of events without losing personalization in the service and reducing the margin of error that can exist in completely manual processes.
From reactive to predictive monitoring
The real change occurs when data stops being used solely to analyze what has already happened and starts being used to anticipate what might happen.
Predictive models allow for combining historical information with data generated during a vehicle’s journey. If the system identifies a tractor-trailer speeding on a road with a history of high-risk conditions and also detects adverse weather conditions, such as rain, the platform can generate a preventative alert and even communicate with the driver to request a reduction in speed before an incident occurs.
“Predictive data, along with additional layers of information, allows us to protect, care for, and prevent,” he noted.
Although many companies still associate monitoring with visualizing a vehicle on a map , the current operation incorporates much more complex elements.
From a monitoring center it is possible to interpret behavioral patterns, identify areas where robberies have historically occurred, recognize recurring signal losses and activate preventive protocols before an event escalates.
This accumulated knowledge allows analysts to understand the operational context of each trip and make decisions more quickly to protect both the operator and the cargo.
The integration of technologies such as geolocation , telemetry , video surveillance and data analysis significantly expands visibility over a fleet.
While geolocation allows you to know the location of a unit, video surveillance provides visual evidence and telemetry offers information on the vehicle’s condition, driving habits, possible maintenance needs and operational performance.
“If we combine geolocation, video surveillance, and telemetry, we can better understand how the vehicle is working and provide information that makes each trip safer, more efficient, and more profitable,” the executive explained.
Anticipating risks also improves competitiveness
Prevention not only reduces losses; it also strengthens operations.
Useche pointed out that anticipating risks allows for protecting the lives of operators, extending the useful life of vehicles, and offering greater certainty to customers regarding the delivery of their goods.
In a market where thousands of companies compete to offer a more reliable service, the ability to prevent incidents is beginning to become a competitive differentiator.
Currently, Total Protect monitors more than eight thousand cargo transport units and maintains a recovery rate of 95% , a figure that recently increased from 94 to 95%, according to the company.
Furthermore, it is already conducting tests to incorporate artificial intelligence in different areas of its operation with the aim of strengthening its monitoring capabilities and moving towards a model where the information not only allows knowing what is happening during a trip, but also anticipating what could happen.
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