IoT Data Management and Analytics: Challenges, Solutions & Trends
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How to Cite

Agarwal, Arun, Sayan Prasad Basu, and Sukhankshama Nayak. 2023. “IoT Data Management and Analytics: Challenges, Solutions & Trends”. Journal of ISMAC 5 (3): 257-73. https://doi.org/10.36548/jismac.2023.3.005.

Keywords

— IoT
— Data Management
— Analytics
— IoT Cloud
— IoT Protocol
— Quality of Service
Published: 13-10-2023

Abstract

The Internet of Things (IoT) has revolutionized industries all over the world by introducing an era of unprecedented data generation and connection. Organizations must successfully manage, analyze, and derive meaningful insights from the massive amount of data that billions of devices routinely collect and transmit. This study examines the crucial facets of IoT data management and analytics, as well as the methodology, resources, and best practices that let businesses make the most of their IoT data. The fundamental properties of IoT data, such as their volume, velocity, diversity, and truthfulness, which provide particular obstacles in terms of storage, processing, and analysis, are first described in the study. The importance of data governance and security in the context of the Internet of Things is then discussed, with a focus on the necessity of effective data management techniques to guarantee data integrity, privacy, and compliance with legal requirements. The study incorporates case studies and real-world examples to show how IoT data management and analytics systems may be used in a variety of industries, including manufacturing, healthcare, smart cities, and agriculture. This study 's conclusion emphasizes the critical role that efficient IoT data management and analytics play in maximizing the potential of the Internet of Things. It is a helpful resource for businesses looking to use their IoT data for improved decision-making, efficiency, and competitiveness in the digital age by offering insights into best practices, cutting-edge technologies, and practical applications.

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