Computer Engineering
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Computer Engineering
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Item A Comparison of Strategies for Missing Values in Data on Machine Learning Classification Algorithms(IEEE, 2019) Makaba, T.; Dogo, E.Dealing with missing values in data is an important feature engineering task in data science to prevent negative impacts on machine learning classification models in terms of accurate prediction. However, it is often unclear what the underlying cause of the missing values in real-life data is or rather the missing data mechanism that is causing the missingness. Thus, it becomes necessary to evaluate several missing data approaches for a given dataset. In this paper, we perform a comparative study of several approaches for handling missing values in data, namely listwise deletion, mean, mode, k-nearest neighbors, expectation-maximization, and multiple imputations by chained equations. The comparison is performed on two real-world datasets, using the following evaluation metrics: Accuracy, root mean squared error, receiver operating characteristics, and the F1 score. Most classifiers performed well across the missing data strategies. However, based on the result obtained, the support vector classifier method overall performed marginally better for the numerical data and naïve Bayes classifier for the categorical data when compared to the other evaluated missing value methods.Item A Joint Optimization Scheme for Enhanced Breast Cancer Diagnosis using Particle Swarm Optimization (PSO) and Binary Particle Swarm Optimization (BPSO)(International Conference of the Faculty of Science, 2025-01-14) Ahmed, Y.E., Abdullahi, I.M., Maliki, D., & Akogbe, M. AOne of the leading diseases globally is cancer and breast cancer is not exempted. The objective of the WHO Global Breast Cancer Initiative (GBCI) is to reduce global breast cancer mortality by 2.5% per year, thereby averting 2.5 million breast cancer deaths globally between 2020 and 2040. The three pillars toward achieving these objectives are: health promotion for early detection; timely diagnosis; and comprehensive breast cancer management. In this study we propose an early and comprehensive detection technique in combating breast cancer diagnosis by combining the strength of both PSO (Particle Swarm Optimization) and BPSO (Binary Particle Swarm Optimization) to achieve optimal solution. The results obtained indicated the superiority of the Hybrid PSO-BPSO model in detection over an existing solution by achieving an accuracy of 98.82% on both the WBCD and WDBC datasets.Item A Model for an Enterprise Automated RFID-Based Pay and Park System(ceur-ws.org, 2016) Dogo, E. M.; Ahmed, A.; Adelakun, M. O.Traffic management is one of the challenging problems in urban cities as vehicle owners look for where to park and queue to pay for rented car parks usually on an hourly basis. Therefore, the choice of a suitable, reliable and flexible architecture for Radio Frequency Identification (RFID) based pay and park system readily comes to mind. It is assumed in this work that the parking lot is already known and secured by the vehicle owner in a closed car park; this paper therefore seeks to address and automate the billing system for enterprise car parks. To achieve this, a reliable and accurate enterprise star topology networked RFID based system, that computes the amount to be paid by a user which is calculated based on the time the user enters and exits the park, and the amount the park owner is charging at a particular point in time is proposed for the automated pay and park system. The system comprises of both software and hardware components integrated together. The developed prototype system is able to grant authorized users access to the park within 30ms after verification and open the barrier in 30ms whenever the emergency button is pressed for safety consideration.Item A Secure Electronic Voting System Using Multifactor Authentication and Blockchain Technologies.(2022) Olaniyi, O.M.; Dogo, E.M.; Nuhu, B.K.; Treiblmaier, H.; Abdulsalam, Y.S.; Folawiyo, Z.This chapter presents a distributed e-voting system that solves the problems of vote-rigging, voter impersonation, and vote falsification, all of which are prevalent in traditional paper ballot systems. In general, the digitization of democratic decision-making is convenient, fast, and cost-saving but can become a gateway for electoral fraud if not properly secured. Authentication and the simultaneous achievement of confidentiality, integrity, and availability represent major challenges toward establishing e-voting as a reliable means of democratic decision-making. In this chapter, a combination of multifactor authentication (MFA) and blockchain techniques is used to secure electronic voting. MFA hampers the compromising of voters’ identities and allows for easy verification, while blockchain technology protects the integrity of the votes and ensures the verifiability of the cast votes. Combining a facial recognition algorithm and RFID authenticates and authorizes voters to participate in the election process. A smart contract implemented on an Ethereum network provides the required measures of integrity and verifiability for secure e-voting. Performance evaluations of the proposed approach show that the MFA yielded a 0.1% false acceptance rate and a 0.8% false rejection rate for 100 voters, respectively. This illustrates that the proposed technique can solve issues of authentication and integrity, thereby paving the way for free, fair, and credible e-democratic decision-making in digitally enabled voting scenarios.Item A Smart Real-time Attendance System using Smart Data Filtering and Selection Techniques(2024-04-09) Ibrahim M. A., Maliki, D., I. A. Dauda, A. Y. Ogaji, S. YakubuCooperate organizations, firms, companies, and educational institutions in Nigeria and the whole world are concerned about attendance of students and employees as the case may be, student overall performance is affected by it. In order to provide solutions for attendance management systems, a variety of techniques and technologies were used in the development of the attendance systems. However, most of these systems lack the flexibility of use and appropriate resource management. This paper presents the development of a smart real-time attendance system that uses smart data filtering and selection techniques to parse user-defined attendance instructions, optimize performance, and improve efficiency and flexibility. This system also employs a multi-factor approach in terms of security engaging the use of RFID technology and fingerprint biometrics to manage attendance records. Also, the system uses a wireless (Wi-Fi) communication approach for real-time communication. The performance of the system was mainly evaluated in terms of throughput, latency, and accuracy showing an average delay of 3 seconds per student, 21.95Mbps average throughput, and zero percent false acceptance.Item Abdullahi, I. M., Salawu B. T., Maliki D., Nuhu B K., & Aliyu, I. (2017). Development of an Artificial Neural Network Model for Daily Electrical Energy Management. Proceedings of the 2nd International Engineering Conference, (IEC 2017), Federal University of Technology Minna, Nigeria, pp 120-125.(Federal University of Technology Minna, 2017-05-07) Abdullahi, I. M., Salawu B. T., Maliki D., Nuhu B K., & Aliyu, IEfficient monitoring and control of electrical energy do not only prevent fire out-breaks caused by electrical appliances, but can also reduce excessive billings and prevent electrical installations. Most Energy Management Systems (EMS) for remote controlling of electrical appliances rely mostly on sensors, data and GSM networks which are un-reliable or even un-available in most part of developing world, this makes them less reliable. Therefore, there is need for an intelligent system that can manage electrical consumption intelligently using user-appliance interactive pattern over a period of time for intelligent control of users’ appliances in his/her absence. The model parameters (number of neurons and training algorithms) that affects its performance were first investigated and adopted. The performance of the developed model was evaluated using Regression analysis (R) and Mean Square Error (MSE) using ANN and Simulink tool boxes in Matlab R2015b. A good model can be used for real time control when deployed. Also, Scale Conjugate Gradient (SCG) training algorithm should also be used because of its high performance for pattern recognition problems. This work will go a long way in efficiently controlling household electrical appliances in the absence of the users thereby preventing fire disasters caused by electrical appliances, reducing the tariffs of consumers while increasing lifespan of electrical installations.Item Accessing Imbalance Learning Using Dynamic Selection Approach in Water Quality Anomaly Detection(MDPI, 2021) Dogo, E. M.; Nwulu, N. I.; Twala, B.; Aigbavboa, C.Automatic anomaly detection monitoring plays a vital role in water utilities’ distribution systems to reduce the risk posed by unclean water to consumers. One of the major problems with anomaly detection is imbalanced datasets. Dynamic selection techniques combined with ensemble models have proven to be effective for imbalanced datasets classification tasks. In this paper, water quality anomaly detection is formulated as a classification problem in the presences of class imbalance. To tackle this problem, considering the asymmetry dataset distribution between the majority and minority classes, the performance of sixteen previously proposed single and static ensemble classification methods embedded with resampling strategies are first optimised and compared. After that, six dynamic selection techniques, namely, Modified Class Rank (Rank), Local Class Accuracy (LCA), Overall-Local Accuracy (OLA), K-Nearest Oracles Eliminate (KNORA-E), K-Nearest Oracles Union (KNORA-U) and Meta-Learning for Dynamic Ensemble Selection (META-DES) in combination with homogeneous and heterogeneous ensemble models and three SMOTE-based resampling algorithms (SMOTE, SMOTE+ENN and SMOTE+Tomek Links), and one missing data method (missForest) are proposed and evaluated. A binary real-world drinking-water quality anomaly detection dataset is utilised to evaluate the models. The experimental results obtained reveal all the models benefitting from the combined optimisation of both the classifiers and resampling methods. Considering the three performance measures (balanced accuracy, F-score and G-mean), the result also shows that the dynamic classifier selection (DCS) techniques, in particular, the missForest+SMOTE+RANK and missForest+SMOTE+OLA models based on homogeneous ensemble-bagging with decision tree as the base classifier, exhibited better performances in terms of balanced accuracy and G-mean, while the Bg+mF+SMENN+LCA model based on homogeneous ensemble-bagging with random forest has a better overall F1-measure in comparison to the other models.Item Blockchain 3.0: Towards a Secure Ballotcoin Democracy through a Digitized Public Ledger in Developing Countries(i-Manager, 2018) DOGO, E. M.; NWULU, N. I.; NKONYANA, T.; OLANIYI, O. M.; AIGBAVBOA, C. O.This paper reviews scholarly articles on the application of blockchain technology for secure electronic voting (e-voting). Furthermore, the feasibility of using blockchain technology to replace the existing manual or semi-digitized voting system in developing countries with Nigeria as a case study is performed. To analyse the current state and preparedness of adopting Blockchain Enabled E-voting (BEEV) system in Nigeria, this paper employs the qualitative SWOT (Strengths, Weaknesses, Opportunities, and Threats) and PEST (Political, Economic, Social, and Technological) analysis approach. This evaluation leads us to identify internal and external factors and the strategic direction in adopting BEEV in Nigeria. It is the authors' opinion that this approach could also be tailored to evaluate situations of other developing countries.Item Bluetooth Assisted Misplaced Object Finder Using DFRobot Arduino Integrated with Android Application(2024) Dogo, E. M.; Emeni, B.; Nuhu, B. K.; Ajao, L. A.Finding lost or misplaced items can be time-consuming and frustrating. Yet, this is common and occurs to many individuals daily and globally. This paper has developed a system that allows users to locate their misplaced or lost items by leveraging the capabilities of Bluetooth technology and a microcontroller-based control system. The DFRobot Bettle BLE Arduino microcontroller is the main component for communication and control. By interfacing the microcontroller with an LED and a buzzer, the system provides visual and auditory signals to assist in locating the target device or item. The search pro-cess is initiated through an Android application, through establishing a Blue-tooth connection between the microcontroller and the target device, permitting the exchange of signals for tracking purposes. When the device is within range, the LED indicator illuminates, and the buzzer produces audible alerts, guiding the user to the device’s location. The application also provides an estimated distance of the object using Bluetooth signal strength. Tests carried out on the system proved its effectiveness in terms of quick response to signals and reliability in both indoor and outdoor environments.Item Combating Road Traffic Congestion with Big Data: A Bibliometric Review and Analysis of Scientific Research(Springer, 2021) Dogo, E.M.; Makaba, T.; Afolabi, O.J.; Ajibo, A.C.Road traffic congestion is one of the challenging problems confronting city dwellers globally. It is majorly caused by either one or a combination of recurrent congestion, nonrecurrent congestion, and precongestion conditions in urban road networks. This chapter performs a bibliometric analysis and reviews the volume of literature linking big data with combating road traffic congestion between 2011 and 2020. The review employs a quantitative analysis of bibliometric science mapping tool to highlight features that affect knowledge accumulation. The chapter also reviews the intellectual structure of knowledge based on total publications and citations. The key scholars, documents, affiliations, regions, data, and algorithms that influenced the development of this research area are analyzed. The results of documents co-citation evaluation show that the key research clusters are salient elements linked with the development and deployment of connected and autonomous vehicles (CAVs) technology. These research clusters are traffic flow prediction, congestion and accidents alert systems, security and privacy mitigation, vehicle emission profiles, travel time estimation, optimization of vehicular routing, journey planning and congestion prediction, and travel and parking guidance. Finally, the chapter presents the way forward and future research direction for sustainable road traffic management in the context of smart city initiatives leveraging on big data.Item Deploying A Standalone Facial and Emotion Recognition Classroom Management System on Resource-Constrained.(Izmir Turkiye, 2024-12-20) Abdullahi, I.M., Maliki, D., Abdulqudus, A., Abraham, S.A, & Ibrahim, M.In recent times, it has been proven in most industries that deep learning can play a huge part in the development and automation of processes otherwise performed manually by humans alone. The trend however has encountered more of a shift and tend towards transfer learning where standalone systems can be built on weights that have been extensively trained to be use-case agnostic. This project seeks to address the problem of student truancy. The methodology applied is a combination of a deep learning use-case agnostic weight embedding obtained from a popular network called Face net. Recognition is performed by computing facial distances using the weight embedding. Also addressed is the common reliance on internet for functionality present in most modern-day systems by deploying all the resources necessary on a resource-constrained development board. Emotions during class are also analyzed to improve classroom experience which will be displayed on a web application dashboard powered by artificial intelligence back-end. The results obtained show an above average recognition rate of 0.63 with emotional recognition accuracy of 0.72. The implications of these results are that accurate attendance can be taken in an organization with minor increments to the system such as increased computational capabilities.Item Design and Implementation of a Wireless Patient Health Monitoring System(IEEE, 2019) O. Manzombi, O.; Dogo, E. M.; Nwulu, N. I.This paper presents the design and implementation of an IoT wireless patient's health monitoring system. The system can be used to continuously monitor the body temperature and pulse rate of a patient located in a hospital room using biomedical sensors. The temperature and pulse rate values are taken from the sensors and processed by an Arduino Uno. Furthermore, they are sent wirelessly via RF communication using a 433 MHz transmitter and receiver kit. The readings are encoded and sent to the receiver where they are decoded and displayed on an LCD screen. Finally, the temperature and pulse rate values are also displayed and stored online using an Arduino Ethernet Shield 2 for future analysis.Item Development and Implementation of Microcontroller-based Improved Digital Timer and Alarm System(2016) Ajao, L. A.; Adegboye, M. A,; Dogo, E. M.; Aliyu, S. O.; Maliki, D.Time plays an important role in our daily activities, more particularly in sectional events or conference arena where there is need for accurate time management. This paper focuses on the development and implementation of an improved digital timer with audio-visual unit using (PIC16F887) microcontroller chip and other electronics component such as LCD, 7-segment display, LED and buzzer as an I/O device. Thus, the need for this device in our daily activities is to monitor the time scheduled for events, updating and alert the audience using an audio-visual approach. The proposed system allows apt time management and avoids time wastage during seminar presentations and the likes. It particularly helps presenters to be time conscious, thus, making them to naturally adjust such that the allotted time is enough to cover up their presentation. The digital timer and alarm system presented herewith is also of advantage to the physically challenged like the deaf and blind in monitoring their sectional activities and to be fully involved about the event situation. The system was designed in different modules, and all were interfaced together with firmware chip to simplify the mechanism’s fault diagnoses and fault corrections.Item Development of a Small Scaled Microcontroller-Based Poultry Egg Incubation System(IEEE, 2019) Kutsira, G. V., Nwulu, N. I. and Dogo, E. M.Owing to an increase in the commercial production of chickens and demand for local consumption as a source of protein in both rural and urban areas in developing countries. This paper proposes a cost-effective incubator for hatching poultry eggs with minimal human involvement. The paper describes the design and implementation of a prototype microcontroller-based electrical incubator system. The developed incubator has optimized temperature and humidity that facilitates higher hatchability rate provided that the egg fertility is high. The prototype incubator was evaluated by loading it with 6 presumed fertile eggs. The percentage of hatchability obtained was 67% (4 out of 6 egg). The remaining two eggs were not hatched as they may not have been fully fertilized.Item Development of a Wireless Sensor Network Based Water Quality Monitoring and Notification System(2019) Sithole, M. P. P.; Nwulu, N. I.; and Dogo, E. M.In this paper, we present a water quality monitoring and notification system. It is also integrated with a consumer alert system on the safety of the water in accordance with the WHO water quality standard. The consumer alert system is made up of a buzzer for notification, a red-Light Emitting Diode (LED) and green-LED as an indicator for unsafe water and safe water respectively. Five sources of contaminants in water namely, soil, chlorine, vinegar, salt, washing powder and their combination were used in this to validate the performance of the system. Wireless communication between the measuring subsystem and the analysis and notification subsystem was established for mobility using radio frequency modules. The error in measurements and the consumption risk per water parameter were calculated on MS Excel as part of the analysis and presented in this document. This paper also presents an added functionality by using a Light Dependent Resistor (LDR) for turbidity measurement and LEDs in the notification subsystem. The notification system accommodates people with disabilities as the buzzer can be heard by those who can't see, and the LEDs can be seen by those who can't hear. The developed system was compared for functionality and performance using the quality of the results measured in comparison with the expected results.Item Development of feedback mechanism for microcontroller based SMS electronic strolling message display board(2014) Dogo, E. M.; Akogbe, A. M.; Folorunso, T. A.; Maliki, D.; Akindele, A. A.Item Development of Time Controlled Based Solar Radiation Tracking System(Journal of Science Technology Mathematics and Education (JOSTMED), 2017-06-17) Maliki, D., Ibrahim I., Nuhu B. K., Abdullahi I. M., & Ajao, L. AThe increase in daily use of electricity with limited in the amount of fossil fuel necessitated researches to explore other methods of producing energy. Many renewable sources of electricity are in existence, one of the cheapest, free and the most abundant renewable source of energy is the electricity generated from the sun. Electricity from solar radiation is environmentally friendly as it poses no harmful hazard to the surrounding. Today, radiation from the sun can be harnessed with the use of the photovoltaic material like the solar panel. It was observed that the sun direction keeps changing during the day as a result of the rotation of the earth and obtaining maximum amount of solar energy from a fixed solar panel cannot be totally achieved throughout the day. To this extend, a time controlled based solar radiation tracking system was developed. The developed system is capable of continuously changing the direction of sun module as the sun transverse the sky with the use of an intelligent fuzzy rules base on input variations. The performance of the tracking system when compared with the fixed solar device gave an output of 19.54% increase in voltage output.Item Empirical Comparison of Approaches for Mitigating Effects of Class Imbalances in Water Quality Anomaly Detection(IEEE, 2020) Dogo, E. M.; Nwulu, N. I.; Twala, B.; Aigbavboa, C. O.Imbalanced class distribution and missing data are two common problems and occurrences in water quality anomaly detection domain. Learning algorithms in an imbalanced dataset can yield an overrated classification accuracy driven by a bias towards the majority class at the expense of the minority class. On the other hand, missing values in data can induce complexity in the learning classifiers during data analysis. These two problems pose substantial challenges to the performance of learning algorithms in real-life water quality anomaly detection problems. Hence, the need for them to be carefully considered and addressed to achieve better performance. In this paper, the performance of a range of several combinations of techniques to deal with imbalanced classes in the context of binary-imbalanced water quality anomaly detection problem and the presence of missing values is extensively compare. The methods considered include seven missing data and eight resampling methods, on ten different learning state-of-the-art classifiers taking into account diversity in their learning philosophies. The different classifiers are evaluated using stratified 5-fold cross-validation, based on three performance evaluation metrics namely accuracy, ROC-AUC and F1-measure. Further experiments are carried out on nineteen variants of homogeneous and heterogeneous ensemble techniques embedded with resampling and missing value strategies during their training phase as well as an optimized deep neural network model. The experimental results show an improvement in the performance of the learning classifiers, especially when dealing with the class imbalance problem (on the one hand) and the incomplete data problem (on the other hand). Furthermore, the neural network model exhibit superior performance when dealing with both problems.Item Explorative analysis of AUV-aided cluster-based routing protocols for Internet of intelligent underwater sensors(Elsevier, 2020) Salami, A. F., Adedokun, E. A., Al-Turjaman, F., Bello-Salau, H., Sadiq, B. O., Dogo, E. M.Contemporary innovations in underwater acoustic technology (UAT), smart systems (SS), vehicular ad-hoc networks (VANET), micro-electromechanical systems (MEMS), and artificial intelligence (AI) coupled with recent advancements in the field of Internet of underwater things (IoUT) have led to the development of interesting engineering solutions for underwater sensor networks (UWSN). UWSN performs collaborative event observation for adaptive decision-making through a specialized network of submerged sensors, surface sinks, and coastal base station by relying on interactive communication, intelligent computing, and smart sensing. UWSN is obviously a critical and essential asset for smart cities (SC) and because of the explosive potential of UWSN technology; it has been garnering increasing attention from academic researchers and industrial experts in various fields. However, the performance of UWSN applications is limited due to issues closely tied to the underwater environment such as surface noise, narrow bandwidth, long propagation delays, high-temperature gradients, bio-fouling, corrosion, and erratic water current activities. These issues lead to high-energy consumption, high deployment costs, rapid route failures, frequent retransmissions, low reliability, and other challenges that have instigated UWSN researchers to proffer solutions in the form of different routing protocols. Cluster-based routing (CBR) is one of these proposed solutions where the network adopts a dynamic hierarchical process of logically grouping the nodes into cluster heads (CHs) and cluster members (CMs) with respect to well-defined performance indicators. Researchers have also established that CBR protocols are relatively more versatile and capable of yielding better performance in terms of fault tolerance, resource awareness, and route efficiency for large-scale UWSNs. This chapter, therefore, discusses the architecture, network model, and technical features of AUV-aided water quality monitoring (WQM) as a target application for the Internet of intelligent underwater sensors. This research furthermore conducts an explorative analysis of state-of-the-art CBR protocols for UWSNs. This work conducts simulation-based network and statistical analysis to provide useful technical insights on the performance analysis of selected CBR protocols.Item Fingerprint Based Driver’s Identification System.(Federal Univesity of Technology Minna, 2018-09-06) Inalegwu, O. C., Maliki, D., Agajo J., Ajawo, L. A., & Abu, A. DThis design work presents a proposed replacement to the current system used by the Federal Road Safety Commission (FRSC) for checking licensed/unlicensed drivers. It gives a faster and less tedious way of identifying registered and licensed road users using biometric captures. The system employs the use of an Arduino board to control and process the functioning of other peripherals: the fingerprint scanner and the Organic Light Emitting Diode (OLED) screen connected to it to achieve its purpose. The prototype system developed was able to displays driver’s information on the OLED screen (Age, Name, Sex and License ID); the average response time of the system was also calculated to be 1.41 seconds, which is a good response time considering the system in question. The false Accept rate and false reject rate were relatively low (after a sample test with 25 individuals); at 4% and 8% respectively. Also, for its implementation, the components are readily available, relatively cheap and the system is on that can be easily adopted by the FRSC if access to their already existing database is granted. Consequently, it is safe to say that the developed system measured up to the design expectations; it meets the aim of a proposed replacement for the present analogue and easy to beat system employed by the FRSC.