Avances tecnológicos en alta montaña: desarrollo de una aplicación de realidad aumentada e Lot para el monitoreo de la capa de nieve en el nevado Huascarán, Perú

• Autor: Zapata Paulini, Joselyn Esther
• Formato: tesis de maestría
• Fecha de Publicación: 2025
• Institución: Universidad Continental
• Repositorio: CONTINENTAL-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorio.continental.edu.pe:20.500.12394/18489
• Enlace del recurso: https://hdl.handle.net/20.500.12394/18489; https://doi.org/10.1016/j.envadv.2024.100586
• Nivel de acceso: acceso abierto
• Materia: Realidad aumentada; Augmented reality; Desarrollo sostenible; Sustainable development; https://purl.org/pe-repo/ocde/ford#2.11.00

Climate change has had a negative impact on Andean glaciers, especially on the snow-capped Huascaran in Peru, which has experienced a loss of 42 % of its glacier mass. Lack of access to accurate snowpack data complicates understanding and informed decision-making in mountainous environments. To address this problem, an application has been developed based on an AR-IoT architecture that integrates augmented reality (AR) and the Internet of Things (IoT) for the periodic monitoring of snow cover on the Huascaran snow-capped mountain. This application uses data collected from meteorological repositories and simulates IoT interactions, while a mobile app offers an interactive and understandable visualization of the data. The Scrum methodology was applied iteratively, from the creation of the 3D model to the connection with the Ubidots platform to store and share the data. The analysis of 58 readings, obtained between April and May 2023, showed correlations between variables such as snow depth, temperature, and wind speed, which served to validate the operation of the AR-IoT tech - nology implemented. These variables offer an initial understanding of atmospheric conditions in high mountains. In addition, the technology developed has the potential to expand to include more relevant data in future an - alyses. The tool demonstrates the effectiveness of combining these technologies for monitoring high mountain snow cover and making informed decisions about water resources management.