Diseño e implementación de una WEB APP para el monitoreo y predicción de variables en cultivos agrícolas en el municipio de La Calera mediante datos de una WSN con tecnología LPWAN e IA, utilizando la metodología SCRUM

Abstract

The Colombian agricultural sector currently faces significant challenges and limitations resulting from persistent government neglect and the difficulty of keeping pace with technological innovation. One of its primary needs is the real-time monitoring of crops to predict adverse conditions caused by climatic events, thereby reducing economic losses and improving competitiveness. To address this need, this project proposes the development of a web application (Web App) for monitoring and predicting agricultural variables in crops located in the municipality of La Calera. The proposed solution is supported by a Wireless Sensor Network (WSN) based on Low Power Wide Area Network (LPWAN) technology. The application employs Artificial Intelligence (AI) techniques to analyze data collected by the sensors and provide accurate, real-time predictions using time-series models. This initiative is led by the LIDER Research Group (Research and Development Laboratory in Electronics and Networks) at Universidad Distrital. The proposed web application is designed to monitor and predict agricultural variables in crops located in the municipality of La Calera. The system relies on an LPWAN-based Wireless Sensor Network (WSN) to collect field data, which are analyzed using Artificial Intelligence (AI) techniques to generate accurate real-time predictions through time-series models.