Desarrollo de un sistema web y móvil que mejore la obtención de datos georreferenciados de delitos con el propósito de crear un modelo analítico de Business Intelligence (BI) orientado al seguimiento de las tendencias de siniestros en la ciudad de Ambato

Abstract

The city of Ambato faces significant challenges in the collection and analysis of crime and casualty data, which negatively impacts public safety decision-making. Traditional methods, based on manual records and fragmented systems, are inefficient and error-prone, affecting accuracy and timeliness in tracking crime trends. This research project proposes the development of a system that combines a mobile application and a web platform, with the objective of optimizing the collection and analysis of geo-referenced crime data and creating a Business Intelligence (BI) analytical model. The system seeks to improve operational efficiency, reduce human error and provide a tool that facilitates administration and access to information for both authorities and citizens. The project was developed using the XP (eXtreme Programming) agile development methodology, which allowed for greater flexibility and adaptability to changes during the development process. This approach facilitated rapid iterations and the incorporation of continuous feedback, ensuring that the final product met requirements as system development progressed. The project is divided into two main applications: web and mobile. Flutter was used for the development of the mobile application, due to its cross-platform performance. For the web application, NextJS and NestJS were used, technologies that allow the creation of robust and scalable web applications. Additionally, a PostgreSQL geospatial database was used to efficiently manage large volumes of georeferenced data and develop a BI analytical model to visualize and analyze crime trends.