http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/42 Computer Engineering 2026-05-03T21:00:11Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/29238 Title: Development of a Smart Wearable Antidrowning System for Swimmers Authors: Kontagora, Nuhu Bello; Ugbede, Buhari Umar; Abu, Adishetu Khadijat; Guda, Blessed; Kim, Jinsul Abstract: Drowning is one of the major causes of unintentional death in the world. owning to this reason, there is a need to curb the issue of drowning. some systems have been developed over the years, but most of the systems are not accurate in detecting a drowning person and do not provide an effective rescue scheme to prevent the swimmers from drowning. The smart anti-drowning and alert system is a system which detects, rescues the swimmer experiencing drowning and alerts the necessary authorities. The system uses two sensors, pulse sensor and accelerometer for the detection of the heartbeat rate and tilting pattern of the swimmer. The Arduino Nano microcontroller receives analogue signal from the sensors and sends a signal to trigger the air vacuum pump and sends a message, when the threshold value is met. The threshold value of the pulse sensor is 45bpm-150bpm (minimum and maximum value) while the threshold value of the accelerometer is 750 -1100 (minimum and maximum value). 2022-05-07T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/29234 Title: A Real-Time Secure-Based Oil and Gas Supply Chain Management using Blockchain Authors: Gumut, Gabriel; Umar, Buhari Ugbede; Abdullahi, Ibrahim Mohammed; Ajao, Lukman Adewale; Olaniyi, Olayemi Mikail; Adeniyi, Samuel Abstract: The security of petroleum product supply chains is essential to mitigate issues such as theft, diversion, hijacking, confidentiality breaches, and privacy violations during the supply chain processes. This study presents a real-time secure-based oil and gas supply chain management system that tracks information using blockchain technology. By integrating telematics with the Ethereum blockchain, the system ensures adequate tracking and secures product distribution information, enhancing transparency and operational efficiency. Key features include smart contracts for automated transaction logging, secure data transmission, and immutable ledger entries. The system's performance was rigorously validated through simulations, demonstrating its effectiveness in real-time data acquisition and secure data management. Prospect and Recommendations: This integration of blockchain technology and IoT fosters data confidentiality and immutability, enhancing trust among stakeholders in the petroleum industry. Future work should explore the scalability of the system, particularly when applied to larger and more complex supply chains. Further integration with advanced IoT sensors and predictive analytics could improve system accuracy and provide predictive maintenance capabilities. This study recommends deploying the system in environments with high theft risks and monitoring its long-term performance to validate its robustness and reliability under real-world conditions. 2024-01-01T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/29233 Title: Artificial intelligence model for prediction of cardiovascular disease: An empirical study Authors: Umar, Buhari Ugbede; Ajao, Lukman Adewale; Dogo, Eustace Mananyi; Ajao, Falilat Jumoke; Atama, Micheal Abstract: 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 networkgenetic 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. 2023-09-01T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/29230 Title: Blockchain for securing electronic voting systems: a survey of architectures, trends, solutions, and challenges Authors: . Ohize, Henry Ohize; Onumany, Adeiza James; Umar, Buhari Ugbede; Lukman, Adewale Ajao; Isah, Rabiu Omeiza; Dogo, Eustace Manayi; Nuhu, Bello Kotongora; Olaniyi, Olayemi Mikail; Ambafi, James Garba; Sheidu, Vincent B.; Ibrahim, Muhammad M. Abstract: 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. 2024-09-19T00:00:00Z