Ingeniería en Sistemas, Electrónica e Industrial

URI permanente para esta comunidadhttp://repositorio.uta.edu.ec/handle/123456789/1

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Autor/a: search.filters.author.Granda Jimenez Erik AlexanderTema: search.filters.subject.APLICATIVO WEB

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    Item type:Ítem,
    Aplicativo web con asistente de voz para automatizar procesos de ventas e inventarios en el restaurante Shawarma La Estacion
    (2025-08)
    Granda Jimenez Erik Alexander
    ;
    Jara Moya Santiago David
    ;
    Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Software
    Digital transformation represents a key opportunity to optimize operations in traditional businesses. In this context, Shawarma La Estación restaurant faced limitations derived from a management model based on manual tasks, making inventory control, sales supervision and operational efficiency difficult. This project proposed the development of a web application to automate the sales and inventory processes. Its functionalities included sales registration, management of products with expiration dates, administration of product transformations, registration of purchases and validation of daily closings, which allowed complete traceability. As an added value, a voice assistant was incorporated to execute actions by means of spoken commands, reducing the operational burden on personnel. The RAD (Rapid Application Development) methodology was applied for the development, which allowed an agile approach through prototypes and continuous iterations. Technologically, Next.js was implemented for the frontend, NestJS for the backend, MySQL as database and Azure Speech SDK for speech recognition. The results were significant, allowing a 98,95% reduction in the average execution time with the web application and a 98,02% reduction when using the voice assistant. The inventory control process showed the greatest savings, with a 100,00% reduction. In addition, an average rating of 4,95/5 was obtained when using the voice assistant, compared to 3,0 for the manual methods. These results demonstrated the effectiveness of the system in optimizing operational management and improving staff experience.