THE INTEGRATION OF INTERNET OF THINGS, BIG DATA ANALYTICS, AND CLOUD COMPUTING TECHNOLOGIES FOR REAL-TIME APPLICATION DEVELOPMENT

• Dr. Jessica L. Monroe

  Department of Communication, Kent State University, Kent, OH, USA

  Author

• Dr. Eric D. Langford

  Department of Political Science, University of Arkansas at Little Rock, Little Rock, AR, USA

  Author

The convergence of Internet of Things (IoT), Big Data analytics, and Cloud Computing has revolutionized the landscape of real-time applications across various domains, particularly in healthcare, smart cities, and industrial automation. This comprehensive review examines the synergistic integration of these emerging technologies and their collective impact on developing robust, scalable, and efficient real-time systems. The study analyzes the architectural frameworks, implementation challenges, security considerations, and performance optimization strategies that characterize modern IoT-enabled applications. Through systematic analysis of current literature and technological trends, this research identifies key opportunities and challenges in deploying integrated IoT-Big Data-Cloud solutions for real-time processing. The findings reveal that while these technologies offer unprecedented capabilities for data collection, processing, and decision-making, significant challenges remain in areas of data privacy, security, interoperability, and resource management. The integration demonstrates substantial potential for transforming traditional systems into intelligent, responsive platforms capable of handling massive data volumes with minimal latency. Future research directions include enhanced edge computing integration, improved security protocols, and development of standardized frameworks for seamless technology convergence. This study contributes to understanding the current state and future prospects of integrated IoT-Big Data-Cloud ecosystems in real-time application development.

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