Risk reduction system and method for one or more work machines at a worksite

A method of risk reduction of a work machine at a worksite, the method comprising:

• receiving a location information data from a location sensor, indicating a geographic position of the work machine on the worksite;
• receiving a series of alert event information data generated by the monitoring subsystems on the work machine when deployed at the worksite;
• employing machine learning algorithms or predefined rules to classify each alert event into one more predetermined alert categories of information associated with a different operational risk levels;
• assigning a unique indicator to each classified alert event based on the classification of the alert event information data;
• aggregating the unique indicators over a defined time interval and based on the geographic position to generate a risk representation of the worksite;
• generating a report displaying the unique indicators on a user interface on a count basis, the unique indicators weighted based on a level of risk;
• and
• generating a control signal to automatically modify a work machine parameter when the count of the alert event exceeds a defined number.

A system for risk reduction during operation of a work machine at a worksite, comprising:

• at least one electronic data processor;
• at least one non-transitory computer readable medium with machine executable code which, when executed by the at least one electronic data processor, causes the at least one electronic data processor to perform operations including:
• receiving, from a location sensor, a location information indicating a geographic position of the work machine on a worksite;
• receiving, from a monitoring subsystem of the work machine, a series of alert event information data generated by the monitoring system on the work machine when deployed at the worksite;
• employing machine learning algorithms or predefined rules to classify each alert event into one or more predetermined alert categories of information associated with different operation risk levels;
• assigning a unique indicator to each classified alert event based on the classification of the alert event information in the series;
• aggregating the unique indicators over a defined time interval and based on the geographic position to generate a risk representation of the worksite;
• generate a control signal to modify a work machine parameter based on the alert event information;
• generate a set of clusters based on the classified alert event information correlated with one of a location information and a time information;
• and
• display the set of clusters on a report.