School of Electrical Engineering and Technology (SEET)

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School of Electrical Engineering and Technology (SEET)

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A Comparative Analysis of Gradient Descent-Based Optimization Algorithms on Convolutional Neural Networks
(IEEE, 2018) Dogo, E. M.; Afolabi, O. J.; Nwulu, N. I.; Twala, B.; Aigbavboa, C. O.
In this paper, we perform a comparative evaluation of seven most commonly used first-order stochastic gradient-based optimization techniques in a simple Convolutional Neural Network (ConvNet) architectural setup. The investigated techniques are the Stochastic Gradient Descent (SGD), with vanilla (vSGD), with momentum (SGDm), with momentum and nesterov (SGDm+n)), Root Mean Square Propagation (RMSProp), Adaptive Moment Estimation (Adam), Adaptive Gradient (AdaGrad), Adaptive Delta (AdaDelta), Adaptive moment estimation Extension based on infinity norm (Adamax) and Nesterov-accelerated Adaptive Moment Estimation (Nadam). We trained the model and evaluated the optimization techniques in terms of convergence speed, accuracy and loss function using three randomly selected publicly available image classification datasets. The overall experimental results obtained show Nadam achieved better performance across the three datasets in comparison to the other optimization techniques, while AdaDelta performed the worst.
A decade bibliometric analysis of underwater sensor network research on the Internet of Underwater Things: An African perspective
(Springer, Cham, 2020) Salami, A. F.; Dogo, E. M.; Makaba, T; Adedokun, E. A.; Muazu, M. B.; Sadiq, B. O.; Salawudeen, A. T.
Recent advancements in cloud computing (CC) and the rapid growth of the Internet of Things (IoT) have tremendously revolutionized terrestrial wireless sensor networks (TWSN) communication. These have resultantly paved the way for the practical realization of underwater wireless sensor networks (UWSN) and the emergence of the Internet of Underwater Things (IoUT). The need for better environmental monitoring within the context of smart cities and the recent spate of global natural disasters has further aroused research interest in IoUT which has motivated a number of UWSN innovations, such as the development of tethered remotely operated underwater vehicles (ROUVs), untethered autonomous underwater vehicles (AUVs), unmanned/autonomous surface vehicles (USVs/ASVs) and other smart underwater technologies. While these inventions hold promising prospects for technologically advanced countries, the same assertion cannot be made for most African countries due to challenges inherent in research and development activities into critical IoUT/UWSN projects in the region. This chapter conducts a systematic bibliometric analysis that highlights the knowledge base for core research works in UWSN globally and within the African region. This research discovered 1025 peer-reviewed articles in 5 Scopus-indexed document sources published between 2008 and July 2019. Microsoft Excel and VOSviewer science mapping software tool was used to analyse the retrieved data from Scopus repository. The bibliometric analysis was used to evaluate specific criteria, namely, major subject area, document sources, most cited and productive authors, countries, institutions, funding institutions and most used keywords. The findings of this research indicated that UWSN/IoUT research is still in its infancy in the African region. This chapter concludes by highlighting vital missing links, essential research directions and unique technical recommendations that will be of relevance in helping the successful actualization of IoUT/UWSN research projects in Africa.
A GSM-Based Remote Controlled Poultry Feed Dispensing System Using DTMF
(2016) Ahmed, A.; Olaniyi, O. M.; Dogo, E. M.; James, E.
Poultry rearing for small scale and commercial farmers has made large contribution in food production. With the recent decline in contribution of livestock subsectors to the national economy, there is a need to device a means of making poultry farming convenient, attractive and maximize yield. Automated Feeding is considered very important in poultry production; however, many famers in the tropical regions practice subsistence farming and mostly employ manual poultry feeding. This paper presents the development of a GSM-based remote-control poultry feed dispensing system via Dual Tone Multi-frequency (DTMF) for intermittent control of poultry feed dispensing. Proper knowledge in this area by farmer will help in running effective production and increase yield in meat and egg to maximize profit. The system is multi state fully input dependent system whose change of state can be controlled by a remote control. The developed mechatronic system reduces manpower, saves time and operates efficiently with minimal human involvement in poultry feeding. The system demonstrated practical effort regarding the improvement in performance of existing solid feed dispensing for high yield with minimal human intervention
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 smart switch control system using ESP8266 Wi-Fi module integrated with an android application
(IEEE, 2019) Makhanya, S. P.; Dogo, E. M.; Nwulu. N. I.; Damisa, U.
There is an increase in demand for low-cost Smart Switch Control Systems (SSCS) that can remotely control home switches or devices in residential environments using mobile applications or websites. In this paper, an SSCS which uses open source software, and can be configured without any physical adjustment to the environment, is developed to automatically minimize energy consumption. The device comprises two parts: An Android application and a unit made up of a programmable Arduino board, ESP8266 Wi-Fi module, wall socket and an SD card. In the SSCS, the Android application is used to remotely control switches using the Wi-Fi technology. Tests carried out on the system proved its effectiveness and quick response to signals.
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.
A survey of machine learning methods applied to anomaly detection on drinking-water quality data
(2019) Dogo, E.M.; Nwulu, N.I.; Twala, B.; Aigbavboa, C.O.
Traditional machine learning (ML) techniques such as support vector machine, logistic regression, and artificial neural network have been applied most frequently in water quality anomaly detection tasks. This paper presents a review of progress and advances made in detecting anomalies in water quality data using ML techniques. The review encompasses both traditional ML and deep learning (DL) approaches. Our findings indicate that: 1) Generally, DL approaches outperform traditional ML techniques in terms of feature learning accuracy and fewer false positive rates. However, it is difficult to make a fair comparison between studies because of different datasets, models and parameters employed. 2) We notice that despite advances made and the advantages of the extreme learning machine (ELM), its application is sparsely exploited in this domain. This study also proposes a hybrid DL-ELM framework as a possible solution that could be investigated further and used to detect anomalies in water quality data.
Adaptive Resource Allocation and Mode Switching for D2D Networks With Imperfect CSI in AGV-Based Factory Automation
(IEEE, 2024-12-16) GBADAMOSI, Safiu Abiodun; HANCKE, Gerhard Petrus; ABU-MAHFOUZ, Adnan M.
In industrial factory automation and control system, reliable communication for automated guided vehicles (AGVs) in dynamic, interference laden factory settings are essential particularly for real-time operations. Device-to-device (D2D) technology can enhance industrial network performance by offloading traffic and improving resource utilization. However, deploying D2D-enabled networks presents challenges such as interference control and imperfect channel state information (ICSI). In this paper, we investigate an adaptive resource allocation and mode switching strategy (ARAMS) in D2D-enabled industrial small cell (SC) networks with ICSI to maximize the system throughput and address reuse interference for AGVs. The ARAMS scheme integrates mode switching (MS), channel-quality factor (CQF), and power control (PC) within a bi-phasic resource-sharing (RS) algorithm to lower the computational complexity. In the initial phase, the operational mode for each D2D user (DU) per cell is adaptively selected based on the channel gain ratio (CGR). Subsequently, it computes the CQF for each cell with a reuse DU to identify an optimal reuse partner. The final phase employs the Lagrangian dual decomposition method to decide the DU’s and industrial cellular users (CUs) optimum distributed power to maximize the system throughput under the interference constraints. The numerical results show that as channel estimation error variance (CEEV) increases, the ARAMS scheme consistently outperforms other approaches in maximizing system throughput, except for the AIMS scheme.
An Electronic Voting System with Directed Acyclic Graph (DAG)- Based Blockchain Using ShimmerEVM
(El-Amin University Journal of Computing (EAUJC)., 2024-04-07) Maliki. D., C. Oruche, I. M. Abdullahi, B. G Najashi, O. R. Isah
This research introduces an innovative electronic voting system that enhances transparency, anonymity, and reliability, aiming to revolutionize both traditional and existing electronic voting methodologies. The system increases accessibility, security, and efficiency in the electoral process. Advanced web development technologies, including NextJs, TailwindCSS, TypeScript, and JWT tokens, are integrated for an improved e-voting experience. This system employs encryption and cryptographic hashes to secure sensitive information, alongside smart contracts on ShimmerEVM— a Directed Acyclic Graph (DAG)-based blockchain—to ensure data persistence and immutability. A user-friendly front-end interface serves as a portal to the web application, enabling seamless interaction with the ShimmerEVM network. A critical feature of the system is the activation of a biometric hardware component, essential for voter registration and participation. ShimmerEVM facilitates the execution of smart contracts, offering a decentralized, transparent, and secure environment without relying on traditional blockchain technology. The focus of this system is on the implementation of security-centric smart contracts, which are pivotal in maintaining voting data integrity and mitigating the risks of vote count manipulation.
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.
An Internet of Things (IoT)-based Veterinary Support System for Livestock Skin Disease Health Care using MobileNetV2
(Journal of Contents Computing, 2022-12-04) Maliki, D., Aliyu, I., Kim, J., Ogunbase, E. F., Suleiman, A., & Abdullahi, I. M
In this work, we present a novel approach for the early detection and diagnosis of skin diseases in farm animals, a major concern that can lead to reduced productivity, decreased animal welfare, and economic losses. Using Internet of Things (IoT) and MobileNetV2, we have developed a system that is built using Raspberry Pi for the gateway and low-power ESP 32 microcontrollers for sensor attachment. This system consists of sensors placed on the animals' bodies, including an electrocardiogram (ECG) sensor and a DS18B20 temperature sensor, which continuously monitor the animals' vital signs and skin temperature. The collected data is transmitted to a central server where it is processed using MobileNetV2, a deep learning model trained to recognize three common skin diseases in farm animals: Dermatophilosis, Dermatophycosis, and Papillomatosis. The results of this processing are then made available to animal owners and farmers through a mobile app. Our results show that the proposed system can accurately detect and diagnose skin diseases in farm animals with a high degree of recall (0.96), precision (0.96), and f1 score (0.96). The use of IoT and machine learning allows for real- time monitoring and early detection of skin diseases, which can significantly re- duce the spread of infection and improve the overall health and welfare of farm animals. In addition, the system is intended to support veterinarians in assessing the health status of farm animals. Overall, this work demonstrates the potential of using IoT and machine learning for the early detection and diagnosis of skin dis- eases in farm animals and highlights the importance of continuous monitoring and proactive management in maintaining the health and welfare of these animals
Analysis of Double Salient Reluctance Machine Using Total Surface Gap Area
(2nd International Engineering Conference (IEC2017) Federal University of Technology, Minna, Nigeria, 2017-06-12) Enesi, A. Y; Ejiogu, E. C; Anih, L. U
In this paper, we analyze the stator-rotor design of a double salient reluctance machine using total surface gap area. The high number of poles in a 4-phase reluctance machine makes it suitable for the analysis. An expression is derived for the total surface gap area which includes the sum of the area of the air-gap (between the inner stator radius and the outer rotor radius), the area between the gaps of the stator poles and the area between the gaps of the rotor poles. The rated torque and the rated power output are expressed through the total surface gap area and the geometrical parameters. The total surface gap area is used to predict the torque ripple and the average torque developed by the machine for different pole arcs, air gaps, number of poles, number of phases and frequencies which are investigated by MATLAB simulation. The stator and the rotor of the machine are drawn by ANSYS software for the purpose of visualization.
Analysis of Reluctance Synchronous Motor Under Hybrid Fault Condition
(IEEE, 2023-09) Ghalavand, Fatemeh; Yusuf, Latifa; Ilamparithi, Thirumarai Chelvan
A small degree of static eccentricity is inevitable due to manufacturing tolerances and assembly imperfections. Therefore, when stator inter-turn fault happens, it is important to analyze it along with static eccentric condition. Unfortunately, there is not much literature that analyzes such a condition. This paper focuses on the analysis of a Reluctance Synchronous Machine (RSM) when subjected to stator inter-turn and static eccentricity faults simultaneously. In particular, the work focuses on determining the impact of relative position between the minimum airgap point and the stator inter-turn fault. The goal of the paper is achieved by simulating a 1.5 hp, 4-pole, RSM using Finite Element (FE) software. Line current data is captured under different fault conditions and motor current signature analysis is carried out. Furthermore, the lower sideband harmonic frequency is reconstructed in time domain using Inverse Fourier Fast Transform. Clarke’s transformation is applied on the reconstructed harmonic frequency currents to estimate the alpha, beta components. Afterwards, Principal Component Analysis (PCA) is implemented on the alpha, beta currents. The major benefits of the work include establishing the impact of hybrid faults on motor current signatures, developing a new measure to predict the relative position of the point of minimum airgap.
ANALYSIS OF SPECTRUM OCCUPANCY PREDICTION RESULTS FOR MAITAMA ABUJA
(International Conference on Communication and Information Science (ICCIS), 2024) Ajiboye, Johnson Adegbenga; Mary Adebola Ajiboye; Babatunde Araoye Adegboye; Daniel Jesupamilerin Ajiboye; Jonathan Gana Kolo; Abiodun Musa Aibinu
This research investigates the efficacy of Artificial Neural Networks (ANN) in predicting spectrum occupancy in Maitama, Abuja, Nigeria, focusing on frequency bands ranging from 30 MHz to 300 MHz. The primary objective was to evaluate the accuracy of ANN-based predictions of spectrum usage and compare these predictions with actual measurements. The study employed ANN to forecast spectrum occupancy across various frequency bands, and the predicted data were then compared with empirical measurements to assess the performance of the model. The analysis revealed that prediction errors were generally low across all frequency bands, with most errors falling below 1.5%. Specifically, the 30-47 MHz sub-band demonstrated an average percentage difference between the actual and predicted value of 0.087%, with a maximum error of 1.12% occurring at frequency of 44.65 MHz. For the 47.05-68 MHz band, the average percentage difference was slightly higher at 0.106%, and the maximum error was 2.18% occurring at frequency of 50.2 MHz. In the 68.05-74.8 MHz band, the average percentage error was 0.040%, but with highest error of 0.232% at frequency of 73.95 MHz. The 74.85-87.45 MHz band showed the most accurate predictions with an average error of just 0.010%, and a maximum error of 0.174% at 75.1 MHz. Overall, the highest prediction error was 0.106% in the 47.05-68 MHz band, whereas the lowest was 0.010% in the 74.85-87.45 MHz band. These results highlight the high accuracy of ANN in predicting spectrum usage, demonstrating its potential for effective spectrum management and planning in Maitama, Abuja.
Artificial intelligence model for prediction of cardiovascular disease: An empirical study
(AccScience Publishing, 2024) Umar, B. U.; Ajao, L. A.; Dogo, E. M.; Ajao, F. J.; Atama, M.
Cardiovascular disease (CVD) is a disease related to the heart and blood vessels. Prediction of CVD is essential for early detection and diagnosis, which is however compounded by the complex interplay between medical history, physical examination outcomes, and imaging results. While the existing automated systems are fraught with the usage of irrelevant and redundant attributes, artificial intelligence (AI) helps in the identification of potential CVD populations by prediction models. This work aims at developing an AI model for predicting CVD using different classifications of machine learning techniques. The CVD dataset was obtained from the UCI repository containing about 76 cardiac attributes for training in various machine learning models, which include a hybrid of artificial neural network genetic algorithm (ANN-GA), artificial neural network, support vector machine (SVM), K-means, K-nearest neighbor (KNN), and decision tree (DT). The performance of the models was measured in terms of accuracy, means square error, sensitivity, specificity, and precision. The results showed that the hybrid model of ANN-GA performs better with an accuracy of 86.4%, compared to the SVM, K-means, KNN, and DT measured at 84.0%, 59.6%, 79.0%, and 77.8%, respectively. It was observed that the system performs better as the number of datasets increases in the database, with a fewer selection of attributes using genetic algorithm for selection. Thus, the ANN-GA model is recommended for CVD prediction and diagnosis.
Artificial Neural Network Application for Error Estimation in Wireless Sensor Network
(IEEE Forum (ICSTEM), 2017-05-06) Agajo, J., Kolo, J. G., Maliki, D., Umar, B. U., Inalegwu, O. C.
This paper comes up with an error estimation model for Wireless Sensor Nodes,, the integrity of data received after transmission within a signal coverage range less or equal to 45 metres is analysed, Neural Network linear regression method was used to evolve resolve equation that compares error with weight of data received as δ℮(w) against δwij , an equation for error rate was also evolved after carefully comparing between data packet transmitted and Packet received, error rate er for sensor node was calculated to be 0.00918 thereby establishing the fact that expected packet to be received for every data transmitted is the product of er and Packet Transmitted.
Automated Hydroponic System Integrated With an Android Smartphone Application
(IGI Global, 2021) Nwulu, N.; Suka, D.; Dogo, E
Hydroponics farming is fast gaining acceptance globally as an alternative and viable method of farming, instigated by the contemporary challenges posed by climate change, exploding population growth, and global food insecurity. Hydroponics farming can be greatly improved by leveraging on innovative technological advances that will allow for the effective and efficient utiliza-tion of limited natural resources such as water, energy (sunlight), and dwindling agricultural farmlands, consequently resulting in higher yields. This paper presents the design and implementation of an automated flood and drain hydroponic system with internet of things and Android application functionalities. The design is an integrated and automatic plant-watering, water level, and pH measurement and control system using Android application with wi-fi communication technology. Tests carried out proved the workability of the system in line with expected design considerations.
Automated Microcontroller-Based Irrigation System
(IGI Global, 2021) Makana, M.; Nwulu, N.; Dogo, E
Traditional irrigation systems do not take into consideration the conservation of water. Therefore, automating the plant watering systems to reduce water wastage and loss would be key to water conservation as a means of making use of water wisely and responsibly. In this chapter, a smart irrigation system that helps control the amount of water applied to crops is proposed and developed. The system controls the ON/OFF state of the water pumping motor based on the soil moisture sensor reading. Other sensors incorporated in the system are the water level sensor and light dependent resistor. The system leverages on the Arduino Uno microcontroller development board to collect input signals from the three sensors. The water pump operates depending on the value of the output signal received by the relay module. This technique of watering is feasible and very affordable and reduces human intervention in field watering.