Extraction of value and impact from IoT big data sets: A qualitative exploration of current methodologies and future directions

Oluwaseyi Olakunle Mokuolu *

Department of Information Technology, University of the Cumberlands, Kentucky, U.S.A.
 
Review
International Journal of Science and Research Archive, 2024, 13(01), 503–507.
Article DOI: 10.30574/ijsra.2024.13.1.1669
Publication history: 
Received on 30 July 2024; revised on 08 September 2024; accepted on 10 September 2024
 
Abstract: 
Integrating the Internet of Things (IoT) with big data analytics has created transformative opportunities across various domains, including smart cities, healthcare, and industrial automation. However, the challenges of extracting value from the vast and heterogeneous IoT data sets are significant. This study aims to explore methods for maximizing value extraction from IoT-generated big data and evaluate their impact on decision-making processes. A systematic literature review was conducted, and an exploratory qualitative methodology was employed to assess existing frameworks and propose improvements. The results highlight the importance of edge computing, machine learning algorithms, and data processing architectures in managing IoT data effectively. Additionally, the study identifies gaps in current research and suggests future directions to enhance the practical application of IoT big data analytics.
 
Keywords: 
IoT; Big data; Edge computing; Machine learning; Data analytics; Value extraction
 
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