Automated Record Keeping for Maintenance Operations via Tracking of Maintenance Vehicles Using Telematics Tracks
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2025-06-24
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Edition:Final Report
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Abstract:Efficient and accurate record-keeping for maintenance vehicle operations is essential for optimizing resources, improving accountability, and enhancing decision-making for transportation agencies. The Indiana Department of Transportation (INDOT) sought an automated system to verify and improve work order records using telematics-based vehicle tracking. This study developed and evaluated a system that leverages GPS data from INDOT’s Data Warehouse to automate work order verification, track vehicle movements, and enhance data accuracy for winter highway maintenance operations. The system integrates GPS tracking, automated data processing, and visualization tools to address key challenges such as data standardization, GPS accuracy, and time resolution. Results indicate that minute-level GPS sampling is insufficient for work order automation, and higher-resolution second-level tracking is recommended. A web-based application was developed to provide managers with scalable, privacy-focused tools for visualizing and validating maintenance activities. Key findings include the successful automation of work order verification, the development of a standardized GPS-to-road location conversion methodology, and the identification of operational challenges such as data transmission gaps in rural areas. The study recommends increasing GPS data resolution, implementing standardized data processing frameworks, enhancing work order recording methods with precise start and end times, and expanding the system to other maintenance operations such as asphalt patching and roadside mowing. This research provides a scalable framework for automating maintenance record-keeping, emphasizing the importance of data accuracy, standardization, and enhanced GPS tracking to improve operational efficiency in transportation management.
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Main Document Checksum:urn:sha-512:f4a7af0416fe9a393a608894f3e2ae05f6963f20d9a54d50514ea24633a14187a2aa558c2de0e1fda16bbe2751eab00857117e7984b00e45d675d1e2636f5f46
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