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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) TELKOMNIKA (Telecommunication Computing Electronics and Control)
Ilesanmi Banjo Oluwafemi
Ekiti State University
Computer Science & IT

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An internet of things-based irrigation and tank monitoring system Tayo Dorcas Obasanya; Ilesanmi Banjo Oluwafemi; Oluwaseyi Olawale Bello; Taiwo Abdulazeez Lawal
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp65-75

Abstract

Agriculture plays a significant role in the development of a nation and provides the main source of food production, income, and employment to nations. It was the most practiced occupation in Nigeria and this formed the backbone of the economy in the early 1960s before the discovery of crude oil, which has led to the derail of sufficient food production, exportation, and the agricultural economy at large. Over time, the dry season has always been challenging with little or no rainfall and there are no irrigation facilities that incorporate different saving practices to adapt to these climate changes on their own. In this paper, a cost-effective internet of things irrigation system that is capable of reducing water wastage, manual labor, monitoring tank water level and that can be controlled remotely is designed. The system integrated Arduino UNO with a soil moisture sensor, HCSR04 ultrasonic sensor, and ESP8266 Wi-Fi module that gives the system capable of being controlled remotely via the internet, thus achieving optimal irrigation using the internet of things (IoT). Some of the challenges facing the existing irrigation system are water wastage, poor performance, and high cost of implementation. The design system helps to control water supply to crops when it is needed, and also monitors soil moisture, temperature, and water tank level. After carrying out the experiments for 15 days, the system saved approximately 49% of the water used in traditional irrigation method. The system is useful in large farming areas to minimize human effort and reduce the cost of hiring personnel.
Quantitative estimation of TV white space in Southwest Nigeria Ilesanmi Banjo Oluwafemi; Ayodeji Peter Bamisaye; Matthew Adedeji Faluru
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.17881

Abstract

The demand for bandwidth has increased in recent years with the advent of new technologies in the wireless systems which have resulted into spectrum crunch. Utilizing the free ultra high frequency (UHF), television (TV) channels also known as TV white space (TVWS) has been proposed as a strategy for increasing spectral efficiency. Deploying TVWS requires the knowledge of the estimate of the available TVWS. In this paper, a quantitative estimation of the available TVWS in South West, Nigeria is computed using the protection view point approach, the pollution viewpoint approach and the Federal Communication Commission (FCC) rule. Results from the estimation shows that the pollution view point approach will guarantee enough protection from the primary users and hence prevent interference from the secondary users. The findings also reveal that there are abundant TVWS in the considered states for the deployment of TVWS devices.
Optimized human detection in NLOS scenarios using hybrid dimensionality reduction and SVM with UWB signals Enoch Adama Jiya; Ilesanmi Banjo Oluwafemi; Emmanuel Sunday Akin Ajisegiri
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 5: October 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i5.26738

Abstract

Trapped victim localization in search and rescue (SAR) operations is especially difficult in non-line-of-sight (NLOS) conditions, where traditional techniques fail due to debris and signal distortion. Ultra-wideband (UWB) NLOS signal datasets offer a promising alternative but are often high-dimensional and noisy. This study proposes an optimized dimensionality reduction framework combining an adaptive human presence detector (AHPD) with genetic algorithms (GA) and independent component analysis (ICA), followed by support vector machine (SVM) classification. The approach is tested on a public NLOS dataset comprising 23,522 dynamic instances, each with 256 signal samples per attribute, simulating complex SAR scenarios including rubble and dynamic obstacles. The results indicate that the AHPD+GA+SVM model reached an accuracy of 85.78%, sensitivity of 80.00%, and specificity of 96.46%, which is better than the AHPD+ICA +SVM model that had an accuracy of 79.20%, sensitivity of 73.07%, and specificity of 81.05%. These findings demonstrate the framework’s robustness and scalability, making it a strong candidate for real-time human detection in disaster recovery missions.
Co-Authors Ayodeji Peter Bamisaye Emmanuel Sunday Akin Ajisegiri Enoch Adama Jiya Matthew Adedeji Faluru Oluwaseyi Olawale Bello Taiwo Abdulazeez Lawal Tayo Dorcas Obasanya