Computer Engineering

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Computer Engineering

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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 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 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.
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 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
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.
Blockchain Technology in Healthcare Systems: Applications, Methodology, Problems, and Current Trends.
(2021-04-19) Dauda, I. A., Nuhu, B. K., Abubakar, J., Abdullahi, I. M., & Maliki, D.
Blockchain Technology (BT) is a secured ledger that has the potential to enhance the safety, quality as well as efficiency of healthcare provision. This will benefit healthcare administrators and healthcare end-users. This paper is focused on expanding the significance of blockchain technology in healthcare information. It identifies those aspects that are not being recorded by many researchers in establishing the prospects of Blockchain Technology in the healthcare domain. Accordingly, the paper looked at Blockchain involvement in administering healthcare services such as telemedicine, health information exchange, and electronic prescribing. The review can discover the huge potential of Blockchain technology in healthcare such as in storing healthcare data on a shared Block that is accessible to concerned stakeholders without undue privacy distresses. This research provides the desired guide and identified open perspectives for researchers that will improve the level of adoption of Blockchain in the healthcare domain.
Cross-Layer Integration Approach for Improving QoS for IPv6 Based VOIP
(iJET, 2014) Dogo, E. M.; Ahmed, A.; Olaniyi, O. M.
Voice over IP (VOIP) is today one of the most innovative IP based Communication Technologies in the Telecommunications industry. This has made it to enjoy a high degree of success in its application in small, medium and large scale enterprises, primarily to save cost as well as leveraging on its enhance functionalities such as mobility and scalability. Despite all its successes, VOIP still faces challenges with Quality of Service (QoS) degradation. This paper proposes a cross-layer model to effectively manage interactions in the data, network and transport layers guided by tradeoff between three performance metrics that affect QoS of VOIP for an improved QoS for Voice over IPv6 (VOIPv6). The parameters taken into consideration in this proposed model are: packet loss, delay and throughput observe by the end user.
Dataset for a wireless sensor network based drinking-water quality monitoring and notification system
(Elsevier, 2019) Sithole, M. P. P.; Nwulu, N. I.; Dogo, E. M.
This paper presents the collected experimental data for water quality monitoring which was conducted in ten experiments by using five different common sources of water contaminants namely soil, salt, washing powder, chlorine and vinegar and their combination. The data were collected indoors at room temperature during the day for several days using sensors that measure pH, turbidity, flow rate, and conductivity in water. The water consumption risk (CR) was calculated as deviation based on the water quality parameters standards proposed by the World Health Organisation (WHO) and the South African Department of Water Affairs (DWA), with respect to the sensor measurement readings obtained. While the error measurements were calculated based on the expected parameter measurement per conducted experiment and repeated for 26 measurements. Pure tap water was the benchmark of water safe for human consumption. The first five experiments were performed by introducing each contaminant into the water and thereafter, two contaminants in the sixth experiment and their additions until all different contaminants were experimented at once in the last experiment.
Design of a Simple and Low-Cost Microcontroller Based Medicare Device for Heart Beat Monitoring
(IEEE, 2013) Dogo, E. M.; Sado, F.; Adah, S. M.
Heart beat monitoring is vital to ensuring healthiness of the human cardiovascular system, but availability of a simple and low-cost heart beat monitoring device that does not require expert medical personnel to handle still remains a challenge especially in rural and semi urban areas of developing countries like Nigeria. This paper describes the design and implementation of a simple, reliable, accurate and cost effective microcontroller based heart beat monitoring device with Liquid Crystal Display (LCD) and voice outputs. The heart rate of the subject is measured from the fingertip using optical sensors and the rate is then displayed on a text based LCD and voice outputs in English language and two Nigerian indigenous languages (Hausa and Yoruba).
Development of a Biometric Based Car Park Access Control and Billing System
(2017) Inalegwu, O. C., Dogo, E. M., Kolo, J. G., Bima, M. E., Ajao, L. A., & Inechioma, J.
Access control involves the granting of authorization for a service to selected persons while restricting others. This paper involves the development of a car park access control system using both biometric and barcode system for the authentication. In addition to providing security to the parked cars, the developed system also automates billing for the car park users. The associated barcode is scanned while entering and exiting the car park. The difference in time is used to compute the amount payable and this is deducted from the specified user’s account. Furthermore, the developed system was evaluated using response time, false acceptance and rejection metrics. The result derived therein proves that the system is reliable with very low false rejection and false acceptance rates of 0.5% and 0.45% respectively. The response time of the system, measured as 1.407s, demonstrates its level of efficiency. In conclusion, the working prototype designed, proves that it can be easily implemented on a large scale with a low maintenance cost.
Development of A Model for Generation of Examination Time Using Genetic Algorithm
(Federal University of Technology Minna, 2019-04-22) Ahmed, A., Umar, B. U., Abdullahi, I. M., Maliki, D., Anda, I., & Kamaldeen, J. A
Examination time table scheduling problem is one of the complexes, NP-complete and typical combinational optimization problem faced by the university community across the globe. Many researches have studies the problem due to its NP-complete nature and highly-multi-constrained problem which seeks to find possible scheduling for courses. Creating an examination timetable for university is a very difficult, time-consuming and the wider complex problem of scheduling, especially when the number of students and courses are high. Several factors are responsible for the problem: increases number of students, the aggregation of schools, changes in educational paradigms, among others. In most universities, the examination time table schedule is usually ended up with various courses clashing with one another. I order to solve this problem of time table scheduling for University examination and effective utilization of resources, this research proposed a model for examination time table generation using Genetic Algorithm (GA) probabilistic operators. GA has been successful in solving many optimization problems, including University time table. This is based on the fact that GA is accurate, precise, free from human error and robust for complex space problem. GA theory was also covered with emphasis on the use of fitness function and time to evaluate the result. The effects of altered mutation rate and population size are tested. By using Genetic algorithm, we are able to reduce the time required to generate a timetable which is more accurate, precise and free of human errors. The implication of this research is a solution, minimizing the time taken in timetable allocation and the clashing that usually characterize time table schedule.
Development of a solar-powered greenhouse integrated with SMS and web notification systems
(IGI Global, 2021) Jafta, L.; Nwulu, N.; Dogo, E.
Energy for heating and cooling is among the biggest costs in greenhouse crop production. This has led to a rethink on energy-saving strategies, including the demand for solar energy as a viable renewable and sustainable choice for greenhouse farming. This chapter presents the development of a solar-powered system leveraging on internet of things and GSM technologies for sensing, controlling, and maintaining optimal climatic parameters inside a greenhouse. The proposed system is designed to automatically measure and monitor changes in temperature, humidity, soil moisture, and the light intensity. The strategy utilized in the design framework provides the user with the information of the measured parameters online and via SMS regardless of their geographical location. The chapter also incorporates a mechanism to self-regulate the climatic condition inside the greenhouse, suitable for the plant growth. Such a system can help improve the quantity and quality of crops grown in a greenhouse. Tests carried out on the system prove its effectiveness according to the design considerations.
Development of an IoT Based Irrigation Control System using Convolutional Neural Network
(JOURNAL OF SCIENCE TECHNOLOGY AND EDUCATION, 2023-06-22) Adamu, M., Abdul-Malik, U. T., Maliki, D
The automation of irrigation activities has the potential to revolutionize traditional manual and static irrigation practices, leading to increased productivity with reduced human intervention. Manual irrigation practices often result in water wastage or inadequate water supply to specific crops, as different crops have varying water requirements (crop water need). Moreover, manual irrigation methods consume significant time and effort, especially when the farmland is located at a distance. This paper presents an IoT-based irrigation system that utilizes computer vision technology to capture and recognize crops in the irrigation field using a Convolutional Neural Network (CNN) model. The developed system continuously monitors and maintains the optimal soil moisture content for each specific crop, employing soil moisture and temperature sensors. The control unit of the system is implemented using the Raspberry Pi 3b+ platform. The performance of the developed system was evaluated using two key metrics: Accuracy and Response time. The CNN model achieved high accuracy, with a stabilized accuracy of 95 percent after 50 epochs of training and validation, using a dataset of 800 pictures. This indicates the system's capability to accurately identify crops in the field. The response time of the system was assessed through ten trials, resulting in an average response time of 14.3 seconds, which is considered satisfactory. The findings of this study demonstrate the effectiveness of the proposed IoT-based irrigation system in automating irrigation processes and optimizing water usage. By integrating crop recognition, soil moisture monitoring, and temperature sensing, the system ensures efficient irrigation practices, reducing water wastage and minimizing human effort. The successful implementation of the developed system paves the way for intelligent and dynamic irrigation systems, fostering higher agricultural productivity and sustainable water resource management
Development of Feedback Mechanism for Microcontroller Based SMS Electronic Strolling Message Display Board. African Journal of Computing & ICT
(African Journal of Computing & ICT, 2014-08-12) Dogo, E.M., Akogbe A.M., Folorunsho, T. A., Maliki, D., & Akindele, A
Digital electronic display board is fast gaining acceptance and application in different spheres of life which include educational education institution, public utility places and in advertisement due to the problem associated with constitution of signposts and manually placement of papers on walls, buildings, and edifies which makes the environment look untidy. This paper presents the design and development of a microcontroller based electronic strolling message display board, which will be used to display messages and information in real-time via SMS. This microcontroller based electronic strolling message display board offers the flexibility to a user to control the message or information displayed without recourse to geographical location of the user, provided there is GSM (Global System for Mobile Communication) mobile network. It therefore eliminates the inconveniences of physically going to the display board to manually input information using a computer system. The paper also incorporates a feedback mechanism from the remote display board to ascertain that the message sent by the user has been displayed. The circuit of the devices is designed based on PIC18F4520 microcontroller and C-programming language is used to program the microcontroller.