Real-Time Edge Analytics for IoT Networks: Optimizing Data Processing and Decision-Making in Smart Cities

C.S.Sp Anthony Nduka
Additional contact information
C.S.Sp Anthony Nduka: Spiritan University Nneochi, Onitsha, Anambra, Nigeria

International Journal of Research and Innovation in Applied Science, 2024, vol. 9, issue 9, 127-145

Abstract: As urban cities become smarter, the increasing number of Internet of Things (IoT) devices leads to the generation and collection of large amounts of data. Real-time processing and analysis of this data is extremely important in many applications. However, the bottleneck in conventional cloud processing stems from latency, bandwidth constraints and privacy concerns. The future framework proposed in this research will cater towards enabling real-time edge analytics in IoT networks while optimizing edge-based data processing decisions to improve smart-city benefits. Such benefits include making intelligent decisions regarding energy usage and network congestion through advanced predictive analytics on traffic management. The methods for enabling distributed data processing, optimized resource management, and deploying predictive models at specific edge nodes will be explored within this study. Similarly, it aims to propose approaches for maintaining the data security and privacy of IoT users while ensuring minimal latency and high accuracy in predictive analytics. The efficacy of the proposed framework will be demonstrated through case studies in smart city settings involving automated traffic management, energy optimizations and real-time monitoring of environmental parameters.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijrias/ ... -issue-9/127-145.pdf (application/pdf)
https://rsisinternational.org/journals/ijrias/arti ... ing-in-smart-cities/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjf:journl:v:9:y:2024:i:9:p:127-145

Access Statistics for this article

International Journal of Research and Innovation in Applied Science is currently edited by Dr. Renu Malsaria

More articles in International Journal of Research and Innovation in Applied Science from International Journal of Research and Innovation in Applied Science (IJRIAS)
Bibliographic data for series maintained by Dr. Renu Malsaria ().