Automated Record Keeping for Maintenance Operations via Tracking of Maintenance Vehicles Using Telematics Tracks [Summary]

Krogmeier, James V.; Zhang, Yaguang · 2025 · ROSA P / Purdue University. Joint Transportation Research Program

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Summary

This study addresses the inefficiencies and inaccuracies inherent in manual record-keeping for maintenance vehicle operations within transportation agencies, specifically focusing on the Indiana Department of Transportation (INDOT). Current methods rely on manual work orders that lack precise spatial and temporal accuracy, hindering resource optimization and data-driven decision-making. To resolve these issues, the researchers developed an automated system leveraging GPS-based telematics data to enhance work order verification, streamline record-keeping, and improve fleet management efficiency, particularly for winter highway operations. The methodology involved integrating GPS data from INDOT’s Data Warehouse with automated data processing and visualization tools. The system was designed to track vehicle movements and verify maintenance activities by matching GPS tracks with recorded work orders. Key technical challenges addressed included data standardization, GPS accuracy, and time resolution. The researchers developed a robust converter between INDOT’s Reference Post System and GPS coordinates to standardize road naming conventions. Additionally, a scalable, privacy-focused web application was created to allow managers to access, visualize, and validate work orders using GPS records. The study examined the system's performance in automating work order generation and identified operational constraints, such as connectivity issues in rural areas. The findings indicate that the system successfully automated the verification of work orders for winter highway operations, significantly reducing manual effort and improving accuracy. However, full automation of work order generation was not achieved; the system could infer work activity based on GPS tracks but required additional data, such as driver information and precise activity start and end timestamps, to fully automate the process. The study found that minute-level GPS tracking was insufficient for accurate automation, recommending a shift to second-level tracking to capture precise vehicle activity. Operational challenges included the "digital divide," which affects real-time GPS data transmission in rural areas, and the necessity of integrating precise start and end times into work orders. The significance of this research lies in providing a foundation for expanding automated record-keeping to other maintenance operations, such as asphalt patching and roadside mowing. The study recommends that INDOT enhance GPS data collection frequency to second-level tracking, implement a standardized data processing framework, and expand work order recording methods to include precise timing data. Future research is suggested to refine algorithms for multi-vehicle operations and optimize data transmission strategies to mitigate rural connectivity issues. Ultimately, the developed web-based application and standardized frameworks offer a pathway to improved efficiency and accountability in transportation management.

Key finding

Minute-level GPS tracking proved insufficient for accurate work order automation, with second-level GPS resolution required to reliably capture maintenance vehicle activity.

Methodology

modeling

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (7 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

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