AI System for Classifying Fleet Events into Operations Queues

The problem

Authorised telematics events, vehicle records and assignment records arrive from different systems and event logs, preventing the team from viewing each case on a single timeline.

As a result, source links may be lost while the event class and review priority are prepared, the case may be referred to the wrong team and the basis for a technical decision may remain unclear.

An incomplete workflow may overlook conflicting sensor data or an emergency, while an unsuitable workflow could lead to an incorrect judgement about driver behaviour.

What we set out to improve

• Time taken for the draft event class and review priority to be ready for specialist review
• Correct referral of records involving conflicting sensor data or an emergency to the appropriate specialist queue
• Record of suggestions corrected or rejected by the fleet operations specialist

How the system works

1. 01 Retrieve authorised telematics event, vehicle and assignment record data from authorised sources
2. 02 Verify the source, timestamp and record identifier
3. 03 Add the context of the relevant asset, user, store, vehicle or content
4. 04 Prepare a draft event class and review priority
5. 05 Compare the draft with technical rules and authority limits
6. 06 Check for exceptions: conflicting sensor data or an emergency
7. 07 Obtain the fleet operations specialist's approval, correction or rejection
8. 08 Write the input, suggestion, change and final decision to the audit log

Methods we used

• Source- and time-traceable data extraction for authorised telematics events, vehicle records and assignment records
• Structured output that constrains event class and review priority fields according to technical rules
• An exception gate that separates conflicting sensor data or an emergency from workflow processing
• An authorised queue that presents evidence and suggestions together for the fleet operations specialist
• Duplicate transaction checks and a rollback record to address the risk of making an incorrect judgement about driver behaviour

Where people stay involved

Data and security

Only fields required for the task are processed from authorised telematics events, vehicle records and assignment records. Source-system permissions are preserved, and personal, technical and security-sensitive data is minimised before being provided to the model. Every read, suggestion, human change and target-system action is written to the audit log.

Who this suits

Frequently asked questions