Computer Engineering

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Computer Engineering

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Start date: 2014End date: 2019

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    Development and Implementation of Microcontroller-based Improved Digital Timer and Alarm System
    (Federal University of Technology Minna, 2016-05-06) 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.
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    Modification of Bacterial Foraging Optimization Algorithm Using Elite Opposition Strategy
    (IEEE Nigeria Computer Chapter, 2019-05-06) Maliki, D., Muazu, M.B., Olaniyi, O. M., & Kolo, J.G. (2019)
    This research work presents the modification of Bacterial Foraging Optimization Algorithm (BFOA) using the elite opposition strategy. The BFOA uses a random search strategy which affect it convergence performance due poor diversification in the search process and the possibility of Oscillatory behaviour towards the search process. The Elite Opposition BFOA is developed to provide more search space so as to enhance more exploitation. The Elite Opposition BFOA (EOBFOA) and the BFOA have been tested using twelve standard benchmark functions (Unimodal and Multimodal benchmark functions). From the simulation result obtained, the EOBFOA outperform BFOA by obtaining better global minimum solution.
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    Development of an Intelligent Aquaculture Control System for Fish Farm”, Journal of Science Technology Mathematics and Education (JOSTMED)
    (Journal of Science Technology Mathematics and Education (JOSTMED), 2017-06-17) Maliki, D., Lawrence, C., Nuhu B. K., Abdullahi I. M., & Umar, B. U.
    Fish farming has become an important practice worldwide and it has been existence for many years. The growing and cultivation of fish which is an important branch of agriculture has served as a source of protein, vitamin and oil for mankind. Manual method of feeding at any choice of tie and inadequate water level monitoring device has been identified to be a limitation affecting the survival of fish in the pond. To this extend, there is a need to constantly monitor water level in the pond due to the fact that water can be lost as a result of seepage and inadequate watershed area which also interferes with fish movement to see and capture prey. In this research, an intelligent aquaculture control system using a fuzzy logic approach has been developed. The developed system is capable of providing feed to fishes at a selected time interval and also detecting and maintaining the level of water in the fish pond by pumping water if the need arises. The overall system performance was achieved base don the system response from generated rules of the fuzzy logic system. This research can further be improved by using the internet and data transmission system for further analysis and remote monitoring of the fish pond.
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    An Intelligent Financial Fraud Indication System Using Fuzzy Logic
    (African Journal of Computing & ICT, 2014-06-22) Maliki, D., Aibinu, A. M., & Olaniyi, O. M
    The issue of financial fraud is taking different dimensions in various countries due to rise in fraud enabling factors emanating from internal and external challenges. The internal challenges from unemployment rate depend on overpopulation, poor standard of living and nature of existing leadership of government. Recent advancement in modern technology and increase in tourist activities have contributed to the existing external challenges. In this paper, an intelligent financial fraud indication system using fuzzy logic is proposed, which involves the use of fuzzy arithmetic, fuzzy degree of association, fuzzy inference, fuzzy rules and different surface plot in determination of different relationship as it relate to certain choice of inputs. The selected input indices were meant to determine how certain degree of changes in inputs can affect the nature of fraud indication. The proposed system also depends on fraud enabling factors in the determination of appropriate fraud indication level. From the results obtained, it is shown that people from areas with high population, high political activities and high education are likely to be engaged in more financial fraud compare to an area in which population, political activities and education are low
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    WIRELESS SENSOR NETWORKS BASED-INTERNET OF THING FOR AGRO-CLIMATIC PARAMETERS MONITORING AND REAL-TIME DATA ACQUISITION
    (Journal of Asian Scientific Research, 2017-05-25) Ajao, L. A., Agajo, J., Kolo, J. G., Maliki, D., & Adegboye, M. A
    The recent advent of internet of things technology with incorporating wireless sensor devices for supervisory, monitoring and security application has necessitated further development of embedded technology, of course, ability to monitor environmental conditions of greenhouse, gardens and farmland is crucial to research for effective seed germination, rapid plant growth and maximizing food production, which is due to some effect ranging from climate variability, soil information and irrigation periods. This paper proposes a real-time data acquisition and monitoring system for effectively monitoring changed in agricultural and environmental parameters using (IEEE 802.11 b/g/n) Wi-Fi, wireless sensor system and Android Web Apps. It is more important and concerned in this research to proffer long way solution to the farmers, agronomist, meteorologist and others based on weather stations, climatic changes and soil conditions. The developed smart agroclimatic parameter monitoring system consists of ATmega2560 controller based measuring units which collects the value of wireless sensor nodes like temperature, humidity, soil moisture and soil pH. These units send their data to the base station (BS), where data are collected and delivered through wireless module to the cloud database using HTTP POST where incoming data are stored. With android Web application, will permit users to view and download a real- time agro-climatic parameters on the dashboard using HTTP GET.
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    A Hybrid Web Caching Design Model for Internet-Content Delivery
    (Covenant Journal, 2016) Alfa, A. A., Ogwueleka, F. N., Dogo, E. M., & Sanjay, M.
    The need for online contents (or resources) to be shared and distributed in a large and sophisticated networks of users, geographical dispersed location of servers and their clients, time taken to fulfil clients requests pose major challenge. Therefore the choice of suitable architecture for Internet-based content delivery (ICD) technologies readily comes to mind. To achieve this, Akamai and Gnutella Web technologies are extensively reviewed to identify their strengths and weakness because of their popularity across the world for delivering contents. This new design for Internet-based content distribution is called AkaGnu because of the extra layer (Gnutella network) inserted into Akamai architecture, which provides greater Internet edge over each technology deployed independently. The paper presents a new ICD technology that performs better than Akamaisystem as a result of new features and behaviours introduced that reduce network traffic, more clients Internet connectivity, increase file sharing, improved speed of contents deliveries, and enhanced network security.
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    Mathematical Modeling of an Intelligent Poultry Feed Dispensing System
    (The AIMS Research Publications, 2017) Ameh, C. A., Olaniyi, O. M., Dogo, E. M., Usman, A., Aliyu, S., Alkali, B.
    The mathematical modeling of control systems and other industrial applications has helped to shape the design and performance of different systems. One of the problems faced by existing designs of poultry feed dispensing system in the tropics is feed wastage often resulting in high cost of production. Several measures that can be used to evaluate the performance of poultry flock especially broilers are growth rate, days to market, mortality, and feed efficiency. Feed is typically the most costly expense in broiler production. As a result, feed efficiency is typically the primary tool by which a flock is evaluated. This research mathematically model an intelligent poultry feed dispensing system that will dispense both solid and liquid feed which will reduce the unusual level of human involvement, feed wastage, contamination and high cost of production. The mathematical model encompasses the speed control of a DC motor which will regulate the to and fro motion of the conveyor brushes and control the flow of the solid feed. The control of the digital valves regulates the flow rate of the liquid feed in and out of the dispensing system. The mathematical model was simulated in MATLAB r2015b environment. The simulated results showed that the system under state-space is controllable and observable when the Kalman matrix test was carried out. At the end, a dynamic model for optimized balance among better yield, returns on investment and cost of operation in dispensing poultry feed was developed.
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    Taking Cloud Computing to the Extreme Edge: A Review of Mist Computing for Smart Cities and Industry 4.0 in Africa
    (Springer, 2019) Dogo, E.M., Salami, A.F., Aigbavboa, C.O., Nkonyana, T.
    The advancement and convergence of Internet of Things (IoT), mobile devices technology, big data and cloud computing with its various technological implementations are finally enabling the vision of Smart Cities and Industry 4.0. However, cloud computing concept has been built with the assumptions of good network connectivity, adequate bandwidth and low latency. But with the proliferation of interconnected smart devices and the expected huge amount of traffic and data to be generated, coupled with the stringent and extremely demanding connectivity, high bandwidth and low latency requirements placed on applications and services were embedded in Smart Cities and Industry 4.0 concepts. The traditional cloud-centric architectural arrangement no longer holds due to these cloud architectural model assumptions. Cloud computing is therefore gradually evolving into new complementary concepts as edge and fog computing, and now mist and dew computing. Mist computing addresses these concerns by extending the capabilities and features of cloud and fog computing, with some level of computing intelligence further on the extreme edge of the network closer or on the sensing devices. With the technological revolution currently spreading across Africa, policy makers, academics and businesses in Africa are gradually recognizing the potential opportunities embedded in embracing emerging and future technologies to tackle issues related to urbanization and industrialization as catalyst for sustainable development and growth. This chapter studies the current trend in mist computing and discusses the application and the potential use case scenarios for Smart Cities and Industry 4.0 in the context of Africa. The chapter also explores practical implementation challenges and drivers supporting growth of these emerging cloud technologies in the region. Finally, pertinent technical recommendations were proposed as solution to the challenges identified together with a qualitative analysis of future opportunities of mist computing in the overall vision of Smart African Cities and Industry Africa 4.0.
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    Blockchain and Internet of Things-Based Technologies for Intelligent Water Management System
    (Springer, 2019) Dogo, E.M., Salami, A.F., Nwulu, N.I., Aigbavboa, C.O.
    Water is a critical and indispensable resource for the sustainability of life, economic development, and the environment. According to the United Nations (UN) estimates, 70% of the world’s population will live in cities by the year 2025, and the current centralized piped infrastructure relied upon by water utilities will be inadequate. Leveraging on the advancement in emerging blockchain, Internet of Things (IoT), and sensor technologies offers a means for efficient water management. In this era of Fourth Industrial Revolution (4IR), human creativity will be a critical requirement in this regard. This chapter explores the impact of blockchain and IoT on water management and examines the feasibility of its adoption in multiple case scenarios and instances such as stormwater management, water quality monitoring and reporting directly to consumers and other relevant stakeholders, and smart payment and contract, in order to sustainably deal with the challenges of global water crisis induced by climate change and rapid population growth. This chapter makes special and unique emphasis on the relevance of the research through an African perspective and view. Furthermore, the technical advantages, socioeconomic gains, and technological benefits of synergizing blockchain and IoT such as enhanced security and transparency, reduced operational cost, overall efficiency, and other merits are expatiated.
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    Performance Evaluation of Data Mining Techniques in Steel Manufacturing Industry
    (Elsevier, 2019) Nkonyana, T.; Sun, Y.; Twala, B.; Dogo, E.
    Industry 4.0 has evolved and created a huge interest in automation and data analytics in manufacturing technologies. Internet of Things (IoT) and Cyber Physical System (CPS) are some of the recent topics of interest in the manufacturing sector. Steel manufacturing process relies on monitoring strategies such as fault detection to reduce number of errors which can lead to huge losses. Proper fault diagnosis can assist in accurate decision-making. We use in this study predictive analysis to help solve the complex challenges faced in industrial data. Random Forest, Artificial Neural Networks and Support Vector Machines are used to train and test our industrial data. We evaluate how ensemble methods compare to classical machine learning algorithms. Finally we evaluate our models’ performance and significance. Random Forest outperformed other ML methods in our study. Keywords: Machine Learning; Manufacturing; Fault Diagnostics