Tecnologia utilizada em auditorias com foco no controle de qualidade das obras públicas rodoviárias do Estado do Ceará
Abstract
This article presents a proposal for technological innovation to support audits of public road projects in the state of Ceará, aiming to increase the efficiency and reliability of quality control. The work arises from the Chief Scientist for Road Infrastructure program and describes the creation of GRiR (Rationalized Road Infrastructure Manager), a platform that uses computer vision, optical character recognition (OCR), and data analysis to transform digitized reports into structured, integrated information visualized on interactive dashboards.
The research highlights the importance of intelligent solutions to overcome the limitations of the traditional inspection model, which relies on reports, often derived from images, making analysis difficult and creating room for human error. The system developed allows for the creation of templates for data extraction, application of machine learning algorithms, and integration with databases, resulting in greater traceability, standardization, and agility in the audit process.
The results demonstrate that the platform helps reduce analysis time, optimize resources, and increase accuracy in identifying nonconformities. In addition to offering gains in transparency and reliability, GRiR strengthens the work of the Ceará State Audit Court (TCE-CE), enabling a more modern and dynamic oversight model aligned with contemporary demands for innovation and efficiency in public management.
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