AI-Based Analysis - Fuel

 This insight displays the actions required to refuel the generator's fuel tank based on the following parameters:

• Current fuel level

• The average fuel consumption rate per hour over the past week

• The average number of hours that an engine runs each day

• Travel duration to the site

This insight describes the fuel data quality score and possible reasons for that issue based on the following parameters:

• Data availability

• Fuel sensor availability

• Fuel configurations in the system

• Differences between measured operational consumption and estimated load-based consumption

• Differences between measured operational consumption and average consumption

• Number of drops and refuel events

 Based on the system's knowledge of the average fuel consumption at the site, the fields calculate the number of days until the fuel in the tank runs out (for tanks 1 and 2 separately).

The data quality fields help to:

• Filtering out sites with low data quality from the analysis so they will not affect organizational indicators (fuel consumption rates, total consumption, total refueling, etc.).

• Making it easier to identify "problematic" sites. It will be possible to determine which sites require a visit and what the issue is by using the new fields.

Logics and calculations performed internally by Galooli that result in a score (0 to 100) that is impacted by the following situations.

The field will return the value “-9999” if there are less then 0.25 engine hours

Comment explaining why a site received any data quality score. It would also serve as a guide for the technician who is sent to the site to resolve the problem.

The fields will present a brief description that enables filtering the field results.

For a more detailed and accurate description, refer to the “Low Fuel Data Quality Active/Description/Activation Date” field.