Multi-Agent AI Framework for Objective Assessment of Excavator Operator Proficiency Through Temporal Behavior Analysis
Research summary
Multi-agent assessment across 119 operators and three skill levels.
Research record
This record preserves the title and author order of the supplied manuscript. Its research stage remains separate from the existence of a PDF or conference-formatted layout.
Evaluation results, cohort definitions, limitations, and source locators are maintained in the related project. This record does not duplicate the project metrics.
The supplied PDF prints abbreviated author names. Full names must be confirmed before a final scholarly citation is released.
Evaluation Scope & Methodology
Samples, denominators, uncertainty, sources and limits
Approach
Compare reported control-coordination aggregates across skill groups, preserving the telemetry/video/report branches.
Results and scope belong to the related case study, Temporal assessment of excavator proficiency.
Cohorts and samples
| Cohort | Sample | Definition |
|---|---|---|
| Temporal assessment sample | 119 operators | Three skill levels; separate assessment/reporting study. |
Reported measures
| Measure | Unit | Cohort | Denominator | Uncertainty | Evidence |
|---|---|---|---|---|---|
| Arm–Boom Pairwise Simultaneity Index | Score from 0 to 1 | Temporal assessment sample | Expert and novice group aggregates in the 119-operator study | None reported | Reported in source |
| Bimanual Coordination Score | Score from 0 to 1 | Temporal assessment sample | Expert and novice group aggregates in the 119-operator study | None reported | Reported in source |
Limitations
- This 119-operator study is separate from the N=36 classifier and N=40 gaze analysis.
- Generated assessment reports do not establish coaching efficacy.
- Three-control versus three-or-more wording requires reconciliation.
- Control-usage categories must not be stacked without resolving overlap definitions.
Sources
- Multi-Agent AI Framework for Objective Assessment of Excavator Operator Proficiency Through Temporal Behavior Analysis, Abstract; Tables 4.1–4.2; Figures 3-1/3-2 (Supplied manuscript reviewed November 2026). Open approved PDF
Cite this record
Sueed W., Muhammad K., Asif C., Chao W. Multi-Agent AI Framework for Objective Assessment of Excavator Operator Proficiency Through Temporal Behavior Analysis. Manuscript.
Formatted from the supplied manuscript. Publisher metadata has not been verified, so no BibTeX is offered yet.