Automatização dos serviços de coleta domiciliar com o QGIS e Python

Abstract

This work describes the development of an innovative tool for monitoring household waste collection services in the city of Recife, Brazil, using QGIS and Python. The main objective is to optimize the management of the Operational Control Center (CCO) of TPF, which operates within Emlurb, allowing for better monitoring of collection operations and analysis of vehicle routes. The developed platform collects and processes geospatial data, providing accurate and timely information about the trucks’ paths and generating reports that assist in service management. By integrating these technologies, the tool offers features such as identifying unserviced areas, analyzing response times by sector, and evaluating vehicle productivity. The generated reports provide a comprehensive view of operational efficiency, facilitating strategic decision-making, including route adjustments and the reallocation of more productive vehicles. Additionally, the tool allows filtering data by speed and distance tolerance, helping to verify whether the trucks adhered to their planned routes. Implementing this solution yields significant benefits for public management, including enhanced operational control, data accuracy, and transparency in waste collection activities. By generating real-time information and rapid results, the tool contributes to the efficiency of operations and the continuous improvement of services, fostering a more effective and data-driven administration. Thus, the developed system helps streamline the waste collection process, making it more agile and sustainable.