Automatização parcial do processo de solicitação de laudos de bens inservíveis

Abstract

Efficient asset management is crucial for institutions, ensuring proper use and preservation of their resources. Within the university context, identifying and evaluating unserviceable assets are fundamental stages of this process. However, the current method of requesting assessments on such assets within the university presents complexities, making it less user-friendly. To address this, this work proposes the creation of an application that automates the most time-consuming parts of this process. The solution allows users to log in using their previously registered credentials or a Google account and then capture at least three images of the asset to automatically generate the required file for the report request. Using image processing techniques and Optical Character Recognition (OCR), the application will extract the asset tag number and query a database to retrieve detailed information about the asset. This data, along with the images, will be compiled and made available to the user in PDF format, ready for the report request. The application also includes authentication via Keycloak and infrastructure on AWS, ensuring the security of the user’s credentials and the availability of the application. This approach aims to make the user experience more intuitive and accessible, reducing process complexity and minimizing errors. Furthermore, it is expected to optimize the time of both requesters and the Committee for Equipment and Furniture Report Issuance, making the report request process faster and more efficient.