Enhancing Decision-Making in IoT Ecosystems with Big Data Analytics and Hadoop Frameworks

Autores/as

  • Anu Vij,Aniket Goyal Autor/a

Palabras clave:

Big Data Analytics (BDA), Decision-Making, Hadoop Framework, IoT Ecosystems, Machine Learning

Resumen

Background: Decision-making in IoT ecosystems involves using data from interconnected devices to make real-time, informed decisions that improve efficiency and functionality. This research tackles the significant challenge of real-time decision-making in Internet of Things (IoT) ecosystems by integrating Big Data Analytics (BDA) and Hadoop frameworks. This study aims to develop and assess a sophisticated decision-making model that utilizes BDA and Hadoop to boost operational efficiency, predictive maintenance, and actionable insights in IoT settings.

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Referencias

Nathali Silva, B., Khan, M., & Han, K. (2017). Big data analytics embedded smart city architecture for performance enhancement through real‐time data processing and decision‐making. Wireless communications and mobile computing, 2017(1), 9429676.

Bibri, S. E. (2018). The IoT for smart sustainable cities of the future: An analytical framework for sensor-based big data applications for environmental

sustainability. Sustainable cities and society, 38, 230-253.

Nisar, Q. A., Nasir, N., Jamshed, S., Naz, S., Ali, M., & Ali, S. (2021). Big data management and environmental performance: role of big data decision-making capabilities and decision-making quality. Journal of Enterprise Information Management, 34(4), 1061-1096.

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Publicado

2025-01-10

Cómo citar

Enhancing Decision-Making in IoT Ecosystems with Big Data Analytics and Hadoop Frameworks (Anu Vij,Aniket Goyal , Trans.). (2025). Cuestiones De Fisioterapia, 54(2), 1334-1350. https://cuestionesdefisioterapia.com/index.php/es/article/view/840