Computer Engineering
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Computer Engineering
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Item Food Safety 4.0: The Future of Food Safety Leveraging Industry 4.0 Technologies(Springer, 2024) Dogo, E. M.; Bokaba, T.; Makun, H. A.; Aliyu, A.; Kparbong, P. B.The convergence of several factors, including population growth, scarce natural resources, climate change, globalization, sustainability, and advances in modern and emerging technologies, in addition to growing demand by consumers, retailers, regulators, and stakeholders to raise the level of food protection is increasingly driving the global food safety agenda. Industry 4.0 technologies are fast infusing into all fields of human endeavor including the food safety ecosystem, serving as catalysts for innovation and sustainability. However, there is no empirical evidence regarding the extent of their application and the level of acceptance within the food safety domain. This study explored the relationship between Industry 4.0 technologies and food safety by evaluating the applications of the Fourth Industrial Revolution technologies in addressing food safety challenges. The objectives are achieved using qualitative methodology and bibliometric analysis of content. Our analysis indicates that artificial intelligence, the Internet of Things, machine learning, and big data are prominent topics related to the 4IR and food safety, while blockchain and smart manufacturing are emerging topics.Item Automatic Photovoltaic Solar Panel Dust Cleaning System(IGI Global, 2021) Shibane, N.; Nwulu, N.; Dogo, E. M.Renewable energy sources are currently regarded as viable options for stabilizing the energy crisis globally as well as addressing global warming challenges. Solar energy is the most promising and sustainable energy source as compared to other renewable energy sources such as coal, nuclear, wind, gas, and hydro energy. The increasing demand for solar panels should be reason enough to investigate ways in which we can increase their efficiency as much as possible. Dust, dirt, and bird dropping are major factors that can affect the performance of solar panel systems. This work presents the development of a solar panel cleaning system that automatically detects dust particles and cleans the solar panel to ensure the continues efficiency of the solar system is at an optimal level. The system comprises of five subsystems: dust sensing, water pumping, microcontroller, cleaning mechanism, and the power system. Tests carried out on the system shows its quick response to signals and effectiveness in cleaning the solar panel whenever dust particles are detected.Item On the Relative Impact of Optimizers on Convolutional Neural Networks with Varying Depth and Width for Image Classification(MDPI, 2022) Dogo, E. M.; Afolabi, O. J.; Twala, B.The continued increase in computing resources is one key factor that is allowing deep learning researchers to scale, design and train new and complex convolutional neural network (CNN) architectures in terms of varying width, depth, or both width and depth to improve performance for a variety of problems. The contributions of this study include an uncovering of how different optimization algorithms impact CNN architectural setups with variations in width, depth, and both width/depth. Specifically in this study, three different CNN architectural setups in combination with nine different optimization algorithms—namely SGD vanilla, with momentum, and with Nesterov momentum, RMSProp, ADAM, ADAGrad, ADADelta, ADAMax, and NADAM—are trained and evaluated using three publicly available benchmark image classification datasets. Through extensive experimentation, we analyze the output predictions of the different optimizers with the CNN architectures using accuracy, convergence speed, and loss function as performance metrics. Findings based on the overall results obtained across the three image classification datasets show that ADAM and NADAM achieved superior performances with wider and deeper/wider setups, respectively, while ADADelta was the worst performer, especially with the deeper CNN architectural setup.Item A Sensor-Based Data Acquisition System for Soil Parameters to Determine Suitable Crops(2023) Abisoye, B. O.; Dogo, E. M.; Umar, B. U.; Mamman, I. Z.Soil parameters monitoring is significant in sustainable crop and food production. The standard strategy of soil parameters monitoring in developing and underdeveloped nations uses manual labor, resulting in wrong decisions in soil management. Inaccurate measurements due to sensor miscalibration or low sensor quality can lead to incorrect soil management decisions and negatively impact crop yield and environmental sustainability. Due to the mentioned challenges, this work aims to develop a Sensor-based Data Acquisition System for Soil Parameters that will enable users to observe various soil parameters like temperature, humidity, water level and soil pH. The system was developed using the combination of hardware and software components. The hardware component comprises of sensory and processing parts. The study calibrates sensors using known pH, moisture, and temperature values for specific crops to grow in Nigeria. The system will aid farmers in determining suitable crops for their farmland and increasing crop yield. The system collects data through a network of sensors installed in the soil and wirelessly transmits the data to a cloud-based server. The collected data is then analyzed and visualized in through a web-based dashboard, providing farmers with information about the state of their soil. The performance evaluation of the system was carried out using response time and accuracy. The average response time of the system was 4 seconds, and the percentage error for temperature and humidity readings when compared to weather forecast readings were 8.20% and 5.08%, respectively. The results show that the proposed system can provide accurate and reliable measurements of soil parameters and can be easily deployed and operated by small-scale farmers. Using this system can result in improved crop yields, reduced wastage, and better overall efficiency in agricultural operations.Item Blockchain for securing electronic voting systems: a survey of architectures, trends, solutions, and challenges(Springer, 2025) Ohize, H. O.; Onumanyi, A. J.; Umar, B. U.; Ajao, L. A.; Isah, R. O.; Dogo, E. M.; Nuhu, B. K.; Olaniyi, O. M.; Ambafi, J. G.; Sheidu, V. B.; Ibrahim, M. M.Electronic voting (e-voting) systems are gaining increasing attention as a means to modernize electoral processes, enhance transparency, and boost voters’ participation. In recent years, significant developments have occurred in the study of e-voting and blockchain technology systems, hence reshaping many electoral systems globally. For example, real-world implementations of blockchain-based e-voting have been explored in various countries, such as Estonia and Switzerland, which demonstrates the potential of blockchain to enhance the security and transparency of elections. Thus, in this paper, we present a survey of the latest trends in the development of e-voting systems, focusing on the integration of blockchain technology as a promising solution to address various concerns in e-voting, including security, transparency, auditability, and voting integrity. This survey is important because existing survey articles do not cover the latest advancements in blockchain technology for e-voting, particularly as it relates to architecture, global trends, and current concerns in the developmental process. Thus, we address this gap by providing an encompassing overview of architectures, developments, concerns, and solutions in e-voting systems based on the use of blockchain technology. Specifically, a concise summary of the information necessary for implementing blockchain-based e-voting solutions is provided. Furthermore, we discuss recent advances in blockchain systems, which aim to enhance scalability and performance in large-scale voting scenarios. We also highlight the fact that the implementation of blockchain-based e-voting systems faces challenges, including cybersecurity risks, resource intensity, and the need for robust infrastructure, which must be addressed to ensure the scalability and reliability of these systems. This survey also points to the ongoing development in the field, highlighting future research directions such as improving the efficiency of blockchain algorithms and integrating advanced cryptographic techniques to further enhance security and trust in e-voting systems. Hence, by analyzing the current state of e-voting systems and blockchain technology, insights have been provided into the opportunities and challenges in the field with opportunities for future research and development efforts aimed at creating more secure, transparent, and inclusive electoral processes.