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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Journal of Information Systems and Informatics
Elegbeleye, Ife
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Computer Science & IT Engineering

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Cost-effective internet of things privacy-aware data storage and real-time analysis Elegbeleye, Femi Abiodun; Mbodila, Munienge; Esan, Omobayo Ayokunle; Elegbeleye, Ife
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i1.pp247-255

Abstract

It has been estimated that about 20 billion internet of things (IoT) devices are currently connected to the Internet. This has led to voluminous data generation which makes storaging, managing, and decision making on data to be challenging. Hence, exposes users’ privacy to be vulnerable to unauthorized people. To address these issues, this research proposed cost-effective storage for keeping and processing the IoT data in real-time. The proposed Fframework utilized a reliable hybridised data privacy model to protect the personal information of users. An empirically evaluation was done to identify the best models using data k-anonymity (KA), l-diversity (LD), t-closeness (TC), and differential privacy (DP). The performance evaluation of cloud computing and fog computing was done through simulations. The results obtained show that the combination of two data privacy models: differential privacy and k-anonymity models performed better than any individual model and any other combined models in the protection of users’ personal information. Lastly, fog computing was found to perform better than the cloud in terms of latency, energy consumption, network usage and execution time. In conclusion, the current study strongly recommends the use of hybridised privacy model of differential privacy (DP) and k-anonymity (KA) for the protection of IoT generated data privacy.
Blockchain and IoT for Sustainable Agriculture: Innovations and Impacts Elegbeleye, Femi Abiodun; Oguntona, Olusegun; Elegbeleye, Ife
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1136

Abstract

The integration of Blockchain and the Internet of Things (IoT) is emerging as a transformative force in sustainable agriculture. This review explores the synergistic potential of these technologies to enhance transparency, traceability, resource efficiency, and resilience in agricultural systems. We conducted a systematic review of peer-reviewed articles and conference proceedings published between 2015 and 2024, sourced from databases such as IEEE Xplore, Scopus, ScienceDirect, and SpringerLink. Studies were selected based on relevance to agricultural sustainability, the implementation of IoT and blockchain, and empirical or conceptual insights. The findings reveal that IoT devices enable real-time data collection and monitoring, while blockchain ensures secure, immutable records for supply chain transparency and smart contracts. Despite their promise, challenges persist, including high implementation costs, scalability issues, and limited digital infrastructure in rural areas. The review underscores the need for collaborative frameworks and policy support to foster adoption and recommends future research to focus on hybrid models and localized applications.
Co-Authors Elegbeleye, Femi Abiodun Esan, Omobayo Ayokunle Mbodila, Munienge Oguntona, Olusegun