Skip to content

Author

B. Iyaomolere

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Review Open access Aug 2026

Greenhouse Monitoring and Control Systems: A Review of Internet of Things and Wireless Sensor Network Technologies

The convergence of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) has strengthened smart greenhouse management by enabling continuous environmental monitoring, automated control, and more informed use of agricultural resources. This review examines and synthesises research on IoT- and WSN-enabled greenhouse systems published between 2015 and 2026. Peer-reviewed studies retrieved mainly from IEEE Xplore and Google Scholar were analysed across sensing technologies, system architecture, communication methods, network topology, control approaches, cloud–edge computing, energy management, and performance assessment. The reviewed studies show that achieving strong performance in one area often requires compromises elsewhere, particularly among communication range, energy demand, reliability, scalability, latency, computational capacity, and cost. ZigBee is particularly suitable for low-power, short-range mesh networks, whereas LoRa better supports wider-area deployments. Clustered and hybrid network structures offer favourable scalability and reliability, while cloud–edge architectures combine scalable analytics with rapid local processing. Intelligent control improves prediction, adaptability, and resource use, whereas renewable energy and intelligent energy management can reduce reliance on conventional power sources. Practical deployment, however, remains constrained by sensor reliability, energy limitations, communication instability, interoperability, cybersecurity risks, and limited long-term validation. Future studies should place greater emphasis on energy-autonomous systems, edge intelligence, secure and interoperable architectures, digital twins, adaptive autonomous control, and realistic evaluation of emerging communication technologies for greenhouse applications. Overall, future smart greenhouses are likely to depend increasingly on integrated architectures that combine energy efficiency, adaptive control, reliable connectivity, and security to support sustainable operation.

J. Popoola, B. Iyaomolere, K. Akingbade et al. · 0 citations
Open access Jul 2026

Invasive Device Human Activity Recognition based on Smartphone Dataset

This study used accelerometer and gyroscope data to train the proposed SVM and Random Forest for human activity recognition and confirmed the accuracy, F1 score, precision, recall and visualize confusion matrix of the proposed HAR model.

Taiwo Samuel Aina, B. Iyaomolere · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.