Browsing by Author "Oyewobi S. Stephen"

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A delay-aware spectrum handoff scheme for prioritized time-critical industrial applications with channel selection strategy
(Elsevier, Computer Communications, 2019-05-11) Oyewobi S. Stephen; Gerhard P. Hancke; Adnan M. Abu-Mahfouz; Adeiza Onumanyi
Cognitive radio has emerged as an enabling technology in the realization of a spectrum-efficient and delaysensitive industrial wireless communication where nodes are capable of responding in real-time. However, particularly for time-critical industrial applications, because of the link-varying channel capacity, the random arrival of a primary user (PU), and the significant delay caused by spectrum handoff (SH), it is challenging to realize a seamless real-time response which results in a quality of service (QoS) degradation. Therefore, the objectives of this paper is to increase spectrum utilization efficiency by allocating channel based on the priority of a user QoS requirements, to reduce SH delay, to minimize latency by preventing avoidable SHs, and to provide real-time response. To achieve an effective spectrum utilization, we proposed an integrated preemptive/non-preemptive priority scheme to allocate channels according to the priority of user QoS requirements. On the other hand, to avoid significant SH delays and substantial latency resulting from random PU arrival, a unified spectrum sensing technique was developed by integrating proactive sensing and the likelihood estimation technique to differentiate between a hidden and a co-existence PU, and to estimate the mean value of the busy and the idle periods of a channel respectively. Similarly, to prevent poor quality channel selection, a channel selection technique that jointly combines a reward system that uses metrics, e.g. interference range, and availability of a common channel to ranks a set of potential target channels, and a cost function that optimizes the probability of selecting the channel with the best characteristics as candidate channels for opportunistic transmission and for handoffs was developed. The simulation results show a significant performance gain of the delay-PritSHS in terms of number of SHs, Latency, as well as throughput for time-critical industrial applications in comparison to other schemes.
A review of industrial wireless communications, challenges, and solutions: A cognitive radio approach
(Wiley, 2020-09-09) Oyewobi S. Stephen; Karim Djouani; Anish Matthew Kurien
Abstract Integral and crucial to performance of wireless sensor networks (WSNs), and specifically industrial wireless sensor network (IWSN) is stable, robust, reliable, and ubiquitous communications system. Though, wired communications system is suitable for industrial communications and is resilient to shadowing and multipath fading effects of industrial-WSN environments, yet its wireless counterpart is a much preferred industrial communications technology due to reduced cost and high flexibility which it offers in comparison to wired communications. However, overcrowding of the industrial, scientific, and medical band, where IWSN is deployed together with other heterogeneous technologies, as well as resultant scarcity of usable frequency spectrum has restrained exclusive application of wireless technology for industrial communications. Nonetheless, cognitive radio (CR) has ability to increase spectrum utilization efficiency and channel capacity for industrial wireless communications (IWC) through opportunistic/dynamic spectrum access (DSA) technique. In this review article, we examine how DSA can benefit IWC through exploitation of new perspectives of white space definitions in the licensed bands as well as unlicensed bands. While discussing the potential of DSA for IWC, we have considered the unique characteristics of IWC as well as technical challenges and issues imposed by industrial-WSN. Accordingly, we have suggested and proffered appropriate CR-based solutions in mitigating some of the challenges where necessary.
A Smart Optimization-Enabled Omnidirectional Dipole Antenna Design for Campus and Conventional FM Radio: A Case Study of 92.3 MHz Campus Radio FUT Minna,
(ATBU Journal of Science, Technology and Education, 2023) O. Akamike; C. Alenoghena; Oyewobi S. Stephen
An antenna performs the most important function in any communication system, this underscores the reason most researchers in the field of antenna design pay close attention to specifics in designing smart antennas. Radio on the other hand is a medium or channel through which information can be disseminated to the audience, to achieve this, an antenna is required. This paper presents a novel optimization based technique to design a smart antenna to meet the demands of both educational institutions and the broadcasting industry. There has been a paradigm shift from conventional antenna designs to smart antennas designs to meet the ever changing world of communication where end users demand high quality of service, and high connectivity, especially with the roll out of 5G wireless network and other evolving technologies. Optimization techniques can be leveraged when the available resources cannot be replaced. A case study of Search FM 92.3MHz FUT Minna has been carried out to address the poor signal coverage within Minna and environs.
A Spectrum Management Strategy for Visible Light Communications Using an Adaptive Threshold Approach
(SATNAC 2021 conference, 2021-11-24) Oyewobi S. Stephen; K. Djouani; A. Kurien
The accessibility of network resources is the primary criteria used to perform handover in existing handover strategies in communication systems. Moreover, the access technique approach implemented in visible light communications (VLC) which utilizes the availability of the channel as the sole criteria for handover instead of the capacity of the channel to support QoE of nodes leads to frequent handovers and poor QoE performance. In this work, the use of adaptive threshold-fixing is proposed to dynamically fix the trigger threshold for handover to match the minimum QoE constraints of the VLC node. Therefore, a node will remain in its current channel as long as the minimum QoE requirements are supported by the present channel. Hence, nodes will only handover if the current channel does not support the least QoE constraints of specific node applications and new channels with better QoE are available. To achieve this, the proposed algorithm dynamically adjusts the handover triggering threshold based on link information extracted from channel at discrete time to meet the minimum QoE constraints of node applications instead of switching to a new available channel. The proposed alogorithm is implemented using Monte Carlo simulations of different VLC scenarios and is compared with a reactive spectrum handoff strategy. Simulations results of the proposed strategies demonstrate a significant reduction of spectrum handoffs while maintaining better throughput for node applications.
A survey of cognitive radio handoff schemes, challenges and issues for industrial wireless sensor networks
(Elsevier, Journal of Network and Computer Applications, 2017-08-25) Oyewobi S. Stephen; Gerhard Hancke
Industrial wireless sensor network (IWSN) applications are mostly time-bound, mission-critical and highly delay sensitive applications therefore IWSN defines strict, stringent and unique QoS requirements such as timeliness, reliability and availability. In IWSN, unlike other sensor networks, late arrival of packets or delay or disruption to an on-going communication are considered as critical failure. Also, because IWSN is deployed in the overcrowded industrial, scientific, and medical (ISM) band it is difficult to meet this unique QoS requirements due to stiff competition for bandwidth from other technologies operating in ISM band resulting in scarcity of spectrum for reliable communication and/or disruption of ongoing communication. However, cognitive radio (CR) provides more spectral opportunities through opportunistic-use of unused licensed spectrum while ensuring minimal interference to licensed users. Similarly, spectrum handoff, which is a new type of handoff in cognitive radio, has the potential to offer increase bandwidth, reliable, smooth and interference-free communication for IWSNs through opportunistic-use of spectrum, minimal switching-delays, and efficient target channel selection strategies as well as effective link recovery maintenance. As a result, a new paradigm known as cognitive radio industrial wireless sensor network (CR-IWSN) has become the interest of recent research efforts. In this paper, we highlight and discuss important QoS requirements of IWSN as well as efforts of existing IWSN standards to address the challenges. We discuss the potential and how cognitive radio and spectrum handoff can be useful in the attempt to provide real-time reliable and smooth communication for IWSNs.
An Effective Spectrum Handoff Based on Reinforcement Learning for Target Channel Selection in the Industrial Internet of Things
(MDPI Sensors, 2019-03-21) Oyewobi S. Stephen; Gerhard Hancke; Adnan M. Abu-Mahfouz; Adeiza J. Onumanyi
The overcrowding of the wireless space has triggered a strict competition for scare network resources. Therefore, there is a need for a dynamic spectrum access (DSA) technique that will ensure fair allocation of the available network resources for diverse network elements competing for the network resources. Spectrum handoff (SH) is a DSA technique through which cognitive radio (CR) promises to provide effective channel utilization, fair resource allocation, as well as reliable and uninterrupted real-time connection. However, SH may consume extra network resources, increase latency, and degrade network performance if the spectrum sensing technique used is ineffective and the channel selection strategy (CSS) is poorly implemented. Therefore, it is necessary to develop an SH policy that holistically considers the implementation of effective CSS, and spectrum sensing technique, as well as minimizes communication delays. In this work, two reinforcement learning (RL) algorithms are integrated into the CSS to perform channel selection. The first algorithm is used to evaluate the channel future occupancy, whereas the second algorithm is used to determine the channel quality in order to sort and rank the channels in candidate channel list (CCL). A method of masking linearly dependent and useless state elements is implemented to improve the convergence of the learning. Our approach showed a significant reduction in terms of latency and a remarkable improvement in throughput performance in comparison to conventional approaches
An Improved GSM Technology-Based Microcontroller Multi-Sensor Home Security and Monitoring System
(International Engineering Conference (IEC), School of Engineering and Engineering Technology (SEET), 2015) Oyewobi S. Stephen; M. Okwori; E. U. Mpkuma; W. M. Audu
With increasing rate of crime all over the world, and with no pointer to this rate of crime abating anytime soon, home security has now become a major concern. Therefore most people; rich or poor are taking measures from highly sophisticated to very crude methods to prevent intrusion. This work presents a GSM technology-based home security and monitoring system. However, unlike the traditional magnetic switch alarms equipped on doors and windows, this system has incorporated a fire detector, a motion sensor and a moisture (rainfall) sensor. On any attempt of a break in, rainfall or possible smoke or fire a short message service (SMS) is sent to the house owner. The system is built using a programmed microcontroller interfaced with mobile phone (NOKIA 1209) such that the three major buttons of the mobile phone are switched at intervals to send a message to the owner of the house anytime there is an intruder, rainfall or fire accident. The system was tested and it worked on attempt of intrusion, rainfall (water) and smoke.
An Improved Rain Activated Automatic Window
(Biennial Engineering Conference, School of Engineering and Engineering Technology (SEET), 2013) Oyewobi S. Stephen; Okwori M; Achonu A. O; Waheed A. M
Meteorological conditions like temperature, wind, clouds, and precipitation (rainfall) influence the condition of comfort inside a house, especially through wind doors and windows; hence the need for proper control activator (either to is close aimed or at open) having of window control made convenient to home owners by the use of a switch to open windows in a an improved automatic window with rain or close the window. The design was conceived after observing the stress mechanical windows give us in our control of it to let air and light come into the house; therefore, advancement in electronics technology was used to design this automatic window. However, unlike existing automatic windows, a rain sensor has been included in this work to help shut the window automatically when rain is falling. To achieve this, a moisture sensor is incorporated in the design to sense rainfall, a forward and reversing DC Motor to move the window pane back and forth, a bistable circuit to control the movement of the DC Motor and a power supply to power the system.The design of ble circult to control work effectively in convenient control of windows for the comfort of the homes and in protecting the homes from rainfall. Keywords: Automatic window, rain activator, mechanical window, electronics, DC motor.
Conservation of Mobile Terminal’s Battery Life Using Dynamic Power Control Algorithm
(SAP, Journal of Wireless Networking and Communications, 2012) Oyewobi S. Stephen; Elizabeth N. Onwuka
Most of our activities today are tied around being able to make a call or connect to the Internet with our Mobile devices. However, to optimally utilize the network and deliver the needed satisfaction to the user the mobile device needs to be powered. Sadly most mobile devices are powered by energy-limited batteries, which impose a constraint on the mobile terminal optimal performance and on the network utility. As a result, special emphasis is now being laid on extending the battery life of mobile devices. In this work, we present a simple and effective power control algorithm, which conserves battery power by dynamically responding to real-time network conditions to adjust mobile terminal’s transmit power. BER (bit error rate) in measurement reports obtained from signals received from the mobile terminal were used to estimate signal quality that helps to determine the network conditions and adjust mobile terminal’s transmit power accordingly. Our algorithm was tested using simulation models, and our results were compared with the Stepwise algorithm, which is a popular power control algorithm in literature. A reasonable improvement was recorded for length of operation time and battery-energy saved for the mobile terminal over stepwise algorithm.
COVID-19 - Environment, Economy, And Energy: Note from South Africa
(JCR, 2021) Daniel R.E. Ewim; Oyewobi S. Stephen; Sogo M. Abolarin
The coronavirus disease (COVID-19) started in Wuhan, China in December 2019 and quickly spread to other parts of the world at lightning speed leaving devastating effects in its tracks. As a result,governments in different countries imposed several contingency measures such as lockdown, stay at home, work from home, study and meet virtually, quarantine and closure of international borders to curtail the spread of the virus and to flatten the curve of infection in their respective countries. Even though the containment measures had positive effects in curtailing the spread and flattening the curve of the COVID-19 pandemic there are also negative aspects such as the closure of businesses, loss of jobs, economic uncertainty and depression. Many articles have been written in the medical field related to the pandemic,however, there has been no study on the impact of the pandemic with respect to the environment, energy, and economy in South Africa. Thisinitial study uses COVID-19 data collected from social media and network services in South Africa to evaluate the impact of COVID-19 on the environment, economy and energy.
Deployment of an Artificial Intelligent Robot for Weed Management in Legumes Farmland
(ABUAD Journal of Engineering Research and Development (AJERD), 2023-08-14) A. A. Adeniji; K. E. Jack; M. K. Idris; Oyewobi S. Stephen; H. Musa; A. O. Oyelami
This groundbreaking research introduces an AI-based approach for revolutionizing weed management in legume farmland, addressing the limitations of traditional methods and introducing a new era of cost-effective and precise weed detection and removal. Traditional methods of removing weeds from farmland involving machinery or chemicals often resulted in high costs and imprecise outcomes. To address these challenges, an advanced image recognition algorithm was proposed, which harnessed smart machines to minimize costs and environmental risks. By utilizing computer vision technology, weeds were accurately identified and targeted for removal. A machine learning model was trained using relevant datasets to enable precise weed management. The AI-powered robot, equipped with advanced image recognition algorithms, demonstrated exceptional accuracy and speed, performing weed removal and decomposition 1.2 times faster than traditional manual labour. This breakthrough in weed management technology offers farmers a means to optimize crop yields, enhance food production, and minimize the environmental impact associated with chemical herbicides. A prototype of the robot was fabricated and evaluated in real-world farming conditions. Field tests were conducted on a bean farm and it’s demonstrated the robot's exceptional accuracy, with only a 2% deviation from the actual weed quantity. This research showcased the potential of AI-based weed management systems in legume farming, offering cost-effective and precise weed detection and removal. This research sets a precedent for the integration of AI in modern agriculture, driving the industry toward a more environmentally conscious and economically viable future. The AI-based weed management system empowers farmers, ensuring bountiful harvests, increased profitability, and a greener, more sustainable tomorrow while attention should be given to manufacturing this model for industrial and or commercial applications.
Development of a cost-friendly home-range TV transmitter to provide safe TV content to underage unsupervised Kids
(Engineering Conference, School of Engineering and Engineering Technology, 2011) Michael Okwori; Oyewobi S. Stephen; M Saidu; U Abdulahi
The security of a nation is directly linked to the moral conduct of her citizens, and this is affected by the kind of upbringing such citizens received as kids. Direct access of kids to video players and satellite TV receivers can lead to unwholesome programs being watched by the Kids especially when they are unsupervised, which can lead to character degradation and deformation. As a solution to this problem, this work is aimed at restricting unsupervised access of underage persons to programs on these electronics devices. Therefore, a low cost home range TV transmitter with pre-select channel-transmit capability, and auto timed turn-on and turn-off was designed. The designed Transmitter powers a Video player or Satellite TV Decoder at a preset time and transmits pre-selected programs on a Video player or Satellite TV Decoder in a restricted region in the house to a Television Set in an unrestricted region in the House that kids have access to for a preset duration. The Transmitter was tested, and it powered the Decoder and transmitted pre-selected programme at the preset time and for the preset duration.
Development of an artificial intelligent agent for library hard materials distribution operations
(AFIT Journal of Science and Engineering Research, 2024) Kufre Esenewo Jack; Waheed Moses Audu; Lanre Joseph Olatomiwa; Umar Suleiman Dauda; Bello Kontagora Nuhu; Oyewobi S. Stephen
In recent years, automation has emerged as a technological solution that is gaining grounds across various fields. The task of managing updates like sorting, shelving and documenting large collections of books in the shortest possible time is stressful with limited personnel and can be automated. Other important library tasks such as consultation can, therefore, be undertaken effortlessly. This paper which explores the use of automated solutions for the purpose of book sorting in libraries, proposes the You Only Look Once version 5 (YOLOv5) model to detect books, then performs optical character recognition using EasyOCR on the detected book. After the characters have been extracted, the system then classifies the book into its respective library section using OpenAI. The result from testing the system shows that the book detection model gave an accuracy of 74%, the EasyOCR performed with an accuracy of 91% with variations across different image formats. For simplicity, images used were stored in jpg formats for faster execution time and easy processing. The paper emphasizes the revolutionary impact of AI and machine vision in educational institutions, especially in libraries beyond what can be imagined, pushing for the formation of library robots. This project's benefits include object detection and intelligent book categorization which phase to a new direction for study and advances library automation technologies that boost education.
Development of smart electricity distribution algorithm for multi-source and segmented loads in buildings
(Proceedings of the 5th European International Conference on Industrial Engineering and Operations Management Rome, Italy,, 2022-07-28) Abdul-Azeez Dauda; Oyewobi S. Stephen; Supreme A. Okoh; Umar S. Dauda
Nigeria has encountered numerous power issues in recent years, including limited and irregular power supply, high power costs, and underdeveloped power facilities, all of which have had major negative consequences on the country's socio-economic development. To improve power availability in buildings and ensure adequate usage efficiency, this paper presents the development of a smart electric power distribution algorithm for multi-source and segmented loads, for implementation on distribution boards. This research aims to develop an algorithm that may be used to support the current building wire infrastructure in Nigeria, allowing for 24/7 reliable power supply and effective management of limited power supply in buildings. It employs a multi-source and segmented load system to provide reliability and energy efficiency measures to balance power supply and demand in buildings. Actual data from offices in the engineering complex of Niger State Polytechnic Zungeru, Nigeria, was used to simulate the developed system in MATLAB Simulink. Results showed that the developed algorithm conserved power by 33.71% compared to the conventional distribution board.
Dipole antenna design leveraging optimization techniques
(ABU-Zaria, 2023) Akamike, Ogechi; Caroline Alenoghena; Oyewobi S. Stephen
Dipole antenna are commonest type of antenna in terms of design. This paper presents a technical review on the subject matter of dipole antenna design leveraging optimization techniques to design a better dipole antenna
Dipole Antenna Design Leveraging Optimization Techniques.
(Harvard International Journal of Engineering Research and Technology, 2023-12-31) Akamike, Ogechi; Caroline Alenoghena; Oyewobi S. Stephen
Dipole antennas are the commonest and simplest type of antennas in terms of design. Antenna Engineers and researchers have been looking for ways to design dipole antenna that can address specific needs of their clients, without incurring additional expenses on the available resources. Therefore, optimization techniques becomes necessary to be leveraged in order to design cost-effective antennas. This paper presents dipole antenna and its varieties as well as different optimization techniques that can be leveraged to design dipole Omnidirectional antennas that can stand the test of time. Most dipole antenna designs carried out by some researchers did not include integrating optimization techniques in their approach.
Enabling a Battery-Less Sensor Node Using Dedicated Radio Frequency Energy Harvesting for Complete Off-Grid Applications
(MDPI, 2020-10-16) Timothy Miller; Oyewobi S. Stephen; Adnan M. Abu-Mahfouz; Gerhard Hancke
The large-scale deployment of sensor nodes in difficult-to-reach locations makes powering of sensor nodes via batteries impractical. Besides, battery-powered WSNs require the periodic replacement of batteries. Wireless, battery-less sensor nodes represent a less maintenance-intensive, more environmentally friendly and compact alternative to battery powered sensor nodes. Moreover, such nodes are powered through wireless energy harvesting. In this research, we propose a novel battery-less wireless sensor node which is powered by a dedicated 4 W EIRP 920 MHz radio frequency (RF) energy device. The system is designed to provide complete off-grid Internet of Things (IoT) applications. To this end we have designed a power base station which derives its power from solar PV panels to radiate the RF energy used to power the sensor node. We use a PIC32MX220F32 microcontroller to implement a CC-CV battery charging algorithm to control the step-down DC-DC converter which charges lithium-ion batteries that power the RF transmitter and amplifier, respectively. A 12 element Yagi antenna was designed and optimized using the FEKO electromagnetic software. We design a step-up converter to step the voltage output from a single stage fully cross-coupled RF-DC converter circuit up to 3.3 V. Finally, we use the power requirements of the sensor node to size the storage capacity of the capacitor of the energy harvesting circuit. The results obtained from the experiments performed showed that enough RF energy was harvested over a distance of 15 m to allow the sensor node complete one sense-transmit operation for a duration of 156 min. The Yagi antenna achieved a gain of 12.62 dBi and a return loss of −14.11 dB at 920 MHz, while the battery was correctly charged according to the CC-CV algorithm through the control of the DC-DC converter.
Enhancing Industrial Workplace Safety With Internet of Things Using Arduino Micro-Controller
(SIPET & SEET, Nigeria Journal of Engineering and Applied Sciences (NJEAS), 2023) Oyewobi S. Stephen; Usman A. U,; Innocent C; Abdulbaki O. A; Jack K. E
IoT (Internet of Things) technologies are widely used in many industrial sectors as a result of their rising technological performance and reduced buying costs. For these reasons, IoT has been considered for use in many emerging fields of application, such as workplace safety. The industry workplace which comprises human and nonhuman factors is becoming more saturated on a daily. These rising activities expose and make the industrial environment prone to uncertainties, e.g. accidents, injuries, explosions, fire outbreaks, and other industrial hazards that undermine man’s industrial environment safety. However, over the past few years, IoT technologies have proffered industrial solutions for a variety of industrial projects, particularly to dynamically manage safety levels at complex workplaces. In this work, an enhanced IoT-based industrial safety system is developed and implemented using an Arduino microcontroller. The Arduino serves as an interface between the different sensors that sense signals from the environment and send messages to the Buzzer/GSM module/Internet. The Arduino is programmed to send a signal and activate the buzzer whenever the sensors sense a value <25oc or >35oc (for Temperature sensor) or low intensity (Light sensor) or smoke (Gas sensor) in the environment. A short message (SMS) is delivered to the safety operator/manager’s phone whenever the gas sensor, temperature sensor, or light sensor senses gas leakage, low light intensity, and temperature respectively. It will also activate a buzzer and upload data to a web server for remote access. A performance test of the system shows that the system was able to sense gas leakage, low light intensity, and temperature very accurately at a low response time and over a wide range effectively.
Evaluating the effectiveness of machine learning models for path loss prediction at 3.5GHz with focus on feature extraction
(Nigerian Journal of Technology, 2024) F. E. Shaibu; E. N. Onwuka; N. Salawu; Oyewobi S. Stephen
Accurate path loss prediction is vital for efficient resource allocation, interference reduction, and overall network reliability in 5G networks, particularly in the widely deployed mid-band frequency spectrum (such as 3.5 GHz). This study evaluates the effectiveness of machine learning models for path loss prediction at 3.5 GHz with a focus on feature prioritization. A feature selection method, recursive feature elimination, was used to identify significant features from datasets obtained through measurement campaigns, weather stations, 3-D ray tracing, geographical data, and simulations. Out of eighteen features, eleven, including new environmental features, were identified as significant features contributing to path loss. These selected variables were then utilized to optimize and train four common machine learning models (ANN, XGBoost, RF, and k-NN) to evaluate their performance in predicting path loss in a specific urban area called an irregular urban environment. The performance of these models was assessed by comparing their predictions with the measured path loss. The Random Forest model closely matched the measured path loss over the entire path length in both LoS and NLoS scenarios, achieving the lowest MAE of 0.15 dB and RMSE of 0.57 dB in the LoS scenario and 0.62 dB and 1.42 dB in the NLoS scenario, with R2 scores of 0.999995437 and 0.999996828, respectively. This indicates its superior performance in predicting path loss in the urban environment
Exploring the perception of Nigerians towards nuclear power generation
(Routledge, Taylor & Francis Group, 2021-07-07) Daniel R.E. Ewim; Oyewobi S. Stephen; Micheal O. Dioha; Chibuike E. Daraojimba; Suzzie O. Oyakhire; Zhongile Huan
To decarbonize the Nigerian power sector and ensure a reliable electricity supply, nuclear power will play a key role. However, public acceptance must be considered for the successful introduction of nuclear power. This study examines the perceptions of Nigerians towards nuclear power generation and its opportunity as a viable source of power in Nigeria. The study adopts a quantitative method through surveys, using simple random sampling by administering questionnaires of structured close-ended questions to 10,001 respondents via social networking services and handdelivered questionnaires. However, the response rate was only 71%. The data were analyzed using Pearson’s Product Moment Correlation to measure the relationship between the various perceptions of nuclear power as a viable solution to the electricity problems in Nigeria using the statistical analysis software, Statistical Product and Service Solutions Statistics (IBM SPSS). The Cronbach’s alpha value of 0.821 of the items (questions) illustrates the acceptable internal consistency of the study and shows that it has reliability and validity on a five-point Likert scale. The study shows that over 56% of the respondents support the use of nuclear power generation as a viable option for electricity supply in Nigeria. Furthermore, it is recommended as a boost to the Nigerian economy, safety, security, and environmental sustainability, therefore, indicating positive perceptions towards building a nuclear power plant in Nigeria.