Telecommunication Engineering http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/45 2026-05-15T05:40:27Z 2026-05-15T05:40:27Z Ahmed, Danasabe Suleiman Abubakar, Saddiq Mohammed Bala, Alhaji Salihu Michael, David Abdullahi, Ibrahim Mohammed Ibrahim, Mohammed http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31169 2026-05-14T21:39:35Z 2025-11-24T00:00:00Z

Title: Development of Multi-Objective Particle Swarm Optimisation (MOPSO) Strategy in Enhancing Interference Mitigation in Machine-to-Machine (M2M) Communication Based on Fault Clearance and Communication Delay in Smart Grid Networks Authors: Ahmed, Danasabe Suleiman; Abubakar, Saddiq Mohammed; Bala, Alhaji Salihu; Michael, David; Abdullahi, Ibrahim Mohammed; Ibrahim, Mohammed Abstract: The proliferation of connected devices has led to a paradigm shift in cellular standards, typified by the long-term evolution (LTE) standard. The fifth-generation (5G) standard supports numerous promising mobile technologies, including Machine-to-Machine (M2M) and Device-to-Device (D2D) communication, which enable the communication of a large number of intelligent devices and ubiquitous devices. The deployment of M2M devices in the application of smart grid (SG), specifically in power systems, has introduced new compromising challenges in the areas of resource allocation and interference management. The 5G cellular network's quality of service (QoS) and performance deteriorate due to interference brought on by the reduced inter-cell distance and the smooth integration of heterogeneous devices. In this paper, an interference-aware multi-objective particle swarm optimisation (MOPSO) scheme is proposed for M2M communication in SG to mitigate the interference generated as a result of the localisation of M2M devices on the grid. In order to evaluate performance, the MOPSO approach was developed and implemented for smart grid situations based on pre-fault, during-fault, and post-optimisation conditions. The initial step was to use the multi-objective particle swarm optimisation (MOPSO) algorithm to optimise the smart grid network in order to decrease grid interference. According to simulation results, under different pre-fault and post-optimisation settings, the system throughput and signal-to-interference-to-noise ratio (SINR) were greatly increased by 32.69 and 21.94%, respectively. Furthermore, by using MOPSO, the fault clearance time was reduced by 106.06%, reducing the amount of time needed to clear an impending fault with interference. Additionally, the smart grid network's power loss was improved and maintained at levels comparable to those of the pre-fault conditions. In the subsequent step, the performance of the developed MOPSO technique was compared to that of the non-dominated sorting genetic algorithm (NSGA-II) in terms of convergence in fault clearance time, SINR, and throughput. Simulation results indicated that, in comparison to NSGA-II's performance, MOPSO throughput and SINR were enhanced by 5.93%, 4.65%, and 0.96%, respectively. In comparison to NSGA-II, the proposed MOPSO converges to the optimal solution more quickly for the various objective functions. The findings provided by the developed MOPSO demonstrate that it can efficiently compete with similar algorithms when tackling problems involving interference optimisation algorithms. Description: Journal Article

2025-11-24T00:00:00Z Ahmed, Danasabe Suleiman Micheal, David Abubakar, Saddiq Mohammed Abdullahi, Ibrahim Bala, Alhaji Salihu Ephraim, Micheal http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31167 2026-05-14T21:28:37Z 2025-02-01T00:00:00Z

Title: A Multi-Objective Particle Swarm Optimisation Approach in Interference Mitigation Underlay 5G-Enabled Machine-to-Machine (M2M) Network in Comparison with Genetic Algorithm (GA) and Simulated Annealing (SA) Algorithms Authors: Ahmed, Danasabe Suleiman; Micheal, David; Abubakar, Saddiq Mohammed; Abdullahi, Ibrahim; Bala, Alhaji Salihu; Ephraim, Micheal Abstract: The increase in the number of connected devices has caused a paradigm shift in cellular standards, which has characterized the Long-Term Evolution (LTE) standard. The fifth-generation (5G) standard supports several promising mobile technologies, including Machine-to-Machine (M2M) communication and Device-to-Device (D2D) communication, connecting numerous ubiquitous intelligent devices. M2M communication has found applications across various areas of human activity, such as industrial automation, geological and environmental monitoring, e-health, smart grids, intelligent monitoring, and intelligent transport systems. The deployment of M2M devices underlaid 5G cellular network has introduced new challenges in resource allocation and interference management. Interference due to decreased inter-cell distance and the seamless integration of heterogeneous devices into the 5G cellular network results in degraded Quality of Service (QoS) and network performance. This paper proposes an interference-aware architecture for M2M communication on 5G network to mitigate interference arising from the localization of M2M devices. Furthermore, the proposed interference mitigation scheme will be mathematically modeled as a multi-objective particle swarm optimization (MOPSO) problem, considering the complexity of the fitness function and the trade-off among particles. However, the proposed interference mitigation scheme was bench-marked with Genetic Algorithm (GA) and Simulated Annealing (SA) optimisation algorithms. Simulation results proved that the optimal configuration identification process of the MOPSO has achieved significant improvement in interference reduction from M2M devices relative to GA and SA strategies. Furthermore, the SINR (25.0 dB) and throughput (95.0 Mbps) of the overall network was enhanced with MOPSO in comparison with lower results obtained when GA (SINR 21.5 dB, Throughput 85.0 Mbps) and SA (SINR 18.0 dB, Throughput 78.0) were applied. The improvements achieved by MOPSO shows that the SINR when compared with SA and GA decreased by 28% and 14% respectively. While the throughput achieved by MOPSO when compared with SA and GA showed a decrease by 18% and 10% respectively. Therefore, a balance between optimal M2M separation distance and improved network performance was achieved. Description: Journal Article

2025-02-01T00:00:00Z ALIYU, I ALENOGHENA, C Zubair, S SALAWU, N APOLLOS, W http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31164 2026-05-14T20:38:19Z 2025-06-30T00:00:00Z

Title: IMPLEMENTATION OF A VITAL SIGNS MONITORING SYSTEM WITH BLOCKCHAIN STORAGE Authors: ALIYU, I; ALENOGHENA, C; Zubair, S; SALAWU, N; APOLLOS, W Abstract: The advent of wearable devices has placed people at the centre of the healthcare delivery process, empowering them to take control of their health and simplifying interactions with healthcare professionals. However, these wearable devices face data loss, theft, unavailability, or misuse by health information managers. In this article, blockchain technology is employed to store patients’ medical data in a decentralised blockchain made available to the patient or the Doctor upon request. The patient’s medical data is secured by a passphrase that the user keeps securely. To achieve real-time patient health monitoring with cloud storage, this study implemented a wearable device that monitors the temperature and pulse of the patient using the Arduino nano microcontroller, Air 208 GSM Module, MAX30102 Pulse sensor, DS18B20 Temperature sensor, Li-ion batteries, and a 1.7-inch TFT LCD. The medical data collected is sent at intervals to the blockchain via an HTTP request. The system reached 99.4% accuracy for temperature readings when measured against clinical values, and 93.4% accuracy for pulse, and the data collected is stored securely in a decentralised manner on the Ethereum Blockchain.

2025-06-30T00:00:00Z Zubair, Suleiman Oyewobi, Stephen S Abdulbaki, Abdulkadir O Lawal, Lawal O Jack, Kufre E http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31163 2026-05-14T20:28:10Z 2025-06-27T00:00:00Z

Title: Development of an IoT-Based System for Boosting Safety in Manufacturing Environments Using Arduino Authors: Zubair, Suleiman; Oyewobi, Stephen S; Abdulbaki, Abdulkadir O; Lawal, Lawal O; Jack, Kufre E Abstract: The rapid advancement and affordability of Internet of Things (IoT) technologies have enabled their integration into diverse operational domains, including safety management in production environments. Modern manufacturing and operational facilities are increasingly complex, with numerous human and mechanical activities contributing to the potential risk of hazards such as fire outbreaks, toxic gas leaks, and equipment malfunctions. To address these challenges, this study presents the design and implementation of a smart safety monitoring system powered by the IoT and controlled via an Arduino microcontroller. The system integrates multiple environmental sensors—including gas, temperature, and light sensors—that continuously monitor manufacturing environment conditions. When abnormal parameters such as gas presence, sub-optimal light levels, or critical temperature deviations (below 25°C or above 35°C) are detected, the Arduino processes these signals to trigger a local alarm (buzzer), transmit Short Message Service (SMS) alerts to designated safety personnel via a GSM module, and upload real-time data to an online server for remote supervision. Experimental validation demonstrates that the proposed system delivers reliable, prompt detection of hazardous events with minimal response time and high operational accuracy across various scenarios, thereby enhancing the overall safety management framework in technical environments.

2025-06-27T00:00:00Z