Bibliographic citations
Mendoza, J., (2024). Módulo de conectividad IoT – BI para monitoreo de producción de sistema robótico agrobot upao en Trujillo, 2024 [Tesis, Universidad Privada Antenor Orrego]. https://hdl.handle.net/20.500.12759/25911
Mendoza, J., Módulo de conectividad IoT – BI para monitoreo de producción de sistema robótico agrobot upao en Trujillo, 2024 [Tesis]. PE: Universidad Privada Antenor Orrego; 2024. https://hdl.handle.net/20.500.12759/25911
@mastersthesis{renati/374430,
title = "Módulo de conectividad IoT – BI para monitoreo de producción de sistema robótico agrobot upao en Trujillo, 2024",
author = "Mendoza Chomba, Jorge Esteban",
publisher = "Universidad Privada Antenor Orrego",
year = "2024"
}
This research work examines the impact of implementing an IoT-BI communication module in the Agrobot UPAO PE501079170-2022-PROCIENCIA robotic system, specifically on the macro-process of production monitoring in the city of Trujillo during the year 2024. Through the automation of three critical micro-processes that comprise it, such as the generation and dissemination of production reports and the daily production report, the goal is to optimize the management times of related information and improve the efficiency of data management for decision-making. Using a pre-experimental quantitative methodology, the duration times of these processes before and after the system implementation were compared, applying T-tests to assess the significance of the observed impact. The results revealed a significant reduction in the times of all micro-processes and the overall macro-process, demonstrating the effectiveness of the IoT- BI module in optimizing production monitoring. This finding is consistent with previous studies in the field of agricultural automation, such as those conducted by (Loyola Diaz, 2022), (Mendoza Vásquez, 2021), and (Arcentales Toledo & Slacedo Mena, 2023), which have also documented significant improvements in operational efficiency through the implementation of similar technologies. Furthermore, it aligns with the growing trend towards the integration of automated systems in agriculture 4.0, highlighted by (Shaukat et al., 2020), (Ahmad et al., 2020), and (Muñoz Choque, 2021), who emphasize the importance of computer automatons and IoT-BI technology in improving information management processes and productivity. The implications of this study suggest that the adoption of IoT-BI technologies can be a key strategy for continuous improvement in modern agriculture. However, the need to implement robust security schemes, expand the sample of robotic systems for future research, and explore the integration of artificial intelligence for the automation of analysis and report writing is recognized, thus ensuring the scalability and long-term sustainability of these technological solutions
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