FACULTY OF ENGINEERING

This study presents the design and implementation of a smart, lightweight, federated deep learning system that integrates solar-powered cameras for automated attendance, unauthorized entry prevention and real-time cyber threat detection in academic environments. Using TensorFlow Lite, Python, and a Flask-based web interface, the model achieved high accuracy in facial recognition while maintaining low computational and energy costs. A structured SQLite3 database supported efficient local data handling, while solar energy integration enabled autonomous and sustainable operation. This project validates the potential of combining renewable energy, artificial intelligence, and federated learning to enhance classroom management and IoT security in lowresource settings.

This project focuses on the design and fabrication of a DC-powered melon shelling machine to improve the efficiency and productivity of melon seed shelling, thereby reducing manual labour and increasing the production capacity of small-scale farmers and entrepreneurs in Nigeria. Melon seed shelling is a crucial process in the production of melon seeds, which are a vital ingredient in various food products. However, the traditional manual method of shelling is labour-intensive, time-consuming, and often results in seed damage. Therefore, there is a need for a mechanized solution to improve the efficiency and productivity of melon seed shelling.This project adopted a design and development approach, involving the conceptualization, design, fabrication, and testing of a DC-powered melon shelling machine. The machine was constructed primarily from mild steel, with additional components such as bolts, nuts, bearings, and a blower. The system is powered by a 12V, 75Ah battery, which gets recharged with the aid of a built-in charging module. The performance of the machine was evaluated through a series of tests, including shelling efficiency, seed damage, and feed rate. The results showed that the machine achieved an average shelling efficiency of 71.8%, an average seed damage of 15.6%, and a feed rate of 55.10 kg/hr. The results of this project demonstrate the potential of the DC-powered melon shelling machine to improve the efficiency and productivity of melon seed shelling. The machine's cost-effectiveness, energy efficiency, and ease of operation make it a viable solution for small-scale farmers and entrepreneurs in Nigeria. The successful development and testing of this machine provide a significant contribution to mechanized agriculture, improving efficiency and reducing manual labor in melon seed shelling. This project has the potential to transform the melon seed production industry in Nigeria, enhancing the livelihoods of farmers and entrepreneurs. Furthermore, this project demonstrates the importance of innovation and entrepreneurship in addressing the challenges faced by small-scale farmers and entrepreneurs in Nigeria. The development of this machine highlights the potential for indigenous innovation to drive economic growth and development in Nigeria. In conclusion, this project has successfully demonstrated the feasibility of designing and fabricating a DC-powered melon shelling machine for improved efficiency and productivity in melon seed shelling. The machine's performance, cost-effectiveness, and ease of operation make it a viable solution for small-scale farmers and entrepreneurs in Nigeria.

Corrosive damage presents widespread problems throughout industries that produce major financial damages and protective hazards. The current study focuses on solving the essential corrosion monitoring requirements in remote industrial sites especially oil and gas pipelines since traditional monitoring techniques often prove expensive and unrealistic. The main objective of this project focuses on developing a wireless sensor network-based corrosion monitoring system that provides time-sensitivedata together with predictive analysis to allow preventive maintenance and decrease operational expenses. The main element of this project requires creating a WSN system through electromagnetic techniques which detects corrosion rates along with humidity and temperature sensors that track environmental conditions affecting corrosion. The system runs data processing through an ESP32 microcontroller linked with wireless transmission capabilities and is supported by Thing Speak cloud software for data storage and visualization. Its design enables quick installation and affordability as well as versatility so industrial operators can use the system across various environments. Wireless communication technology allows remote monitoring thus minimizing the necessity for human inspections.. Field trials of the developed sensor and Laboratory tests verify that the created sensor system successfully detects corrosion by precisely measuring degradation in different environmental parameters. Analysis results and failure predictions based on collected data enable correct timing of maintenance and wise decision-making. Since field trials proved the system valid, WSN-based corrosion monitoring provides both efficiency and economic benefits for traditional measurement approaches together with safety benefits from early warning capabilities.

Managed Pressure Drilling (MPD) has emerged as a critical technology for addressing deepwater drilling challenges including narrow pressure windows, formation uncertainty, and wellbore instability. Despite proven benefits, limited research has comprehensively reviewed optimal MPD configurations and implementation strategies for deepwater environments. This systematic literature review analyzed multiple published sources to identify best practices, evaluate existing technologies, and provide evidence-based recommendations.The review identified four critical success factors: comprehensive planning, appropriate technical configurations, disciplined operational procedures, and effective team integration. Three case studies from Gulf of Mexico, East Malaysia, and Mediterranean demonstrated quantified improvements of 35-81% in performancemetrics with substantial cost savings including USD 3.5 million contingency avoidance. Analysis revealed that MPD effectiveness requires formation-specific customization, with economic benefits extending beyond cost reduction to risk mitigation and enabling access to challenging reserves. Persistent challenges include extended response times, equipment reliability concerns, lack of standardization, and economic evaluation uncertainties. Priority research areas recommended include advanced control systems, equipment reliability enhancement, standardization initiatives, and comprehensive economic frameworks. These findings provide valuable guidance for optimizing MPD application in deepwater drilling environments.

This study examines the performance of the ZigBee Received Signal Strength Indicator (RSSI) in indoor environments, with a focus on understanding how distance and environmental obstacles influence wireless signal propagation. The research was conducted at the Faculty of Engineering, University of Benin, utilizing two ZigBee Pro S2B modules configured through XCTU software. Measurements were taken at distances ranging from 10 feet to 50 feet, under various conditions involving obstacles such as furniture, walls, and human presence. The findings indicate that RSSI values exhibit a progressive decline with increased distance and greater obstacle density. Specifically, the signal strength diminished by approximately 4 to 6 dB for every 10-foot increment, with an additional decrease of 3 to 5 dB for every two additional obstacles encountered. It was determined that walls and human presence are the most significant factors contributing to signal attenuation, due to effects related to reflection, absorption, and scattering. These results are consistent with theoretical path loss models and corroborate prior empirical studies, reinforcing the notion that the performance of ZigBee technology is significantly influenced by environmental conditions. The study concludes that ZigBee is well-suited for short-range, low-power Internet of Things (IoT) and sensor applications; however, optimal node placement and the implementation of mesh networking are critical for ensuring reliable communication in complex indoor environments. The insights derived from this research hold valuable implications for enhancing the design and deployment of wireless sensor networks in academic and smart-building contexts.

Cavitation is a phenomenon that significantly impacts the performance, efficiency, and longevity of ship propellers, often leading to issues such as vibration, noise, erosion, and a reduction in propulsive efficiency. The motivation behind this study stems from the need to better understand the dynamics of cavitation bubbles and their effects on propeller performance to design more efficient and durable marine propulsion systems. As cavitation can cause damage to propeller blades and reduce fuel efficiency, addressing this issue is crucial for the advancement of ship design, particularly in terms of material selection, propeller geometry, and operational strategies. The purpose of this research is to analyze the effect of cavitation-induced bubbles on ship propellers using advanced computational tools, thereby providing insights that could guide future propeller designs and enhance maritime operational efficiency. To achieve this, the study employs ANSYS simulation tools, specifically its Computational Fluid Dynamics (CFD) module, to model and simulate the behavior of cavitation bubbles in proximity to the propeller. The simulations use a multiphase flow model that includes both the liquid and vapor phases, allowing for the simulation of bubble formation, growth, and collapse under various operating conditions using the vp1304 as the propeller model. The study examines different parameters such as propeller rotational speed, fluid velocity, water temperature, and turbulence levels. The simulation environment is built on realistic physical conditions, using detailed mesh generation to accurately capture the complex flow behavior round the propeller blades. ANSYS Fluent's cavitation model is used to simulate bubble dynamics, with a focus on evaluating pressure distributions, vortex shedding, and velocity gradients. The results of the simulations reveal that cavitation has a profound effect on the hydrodynamic performance of the propeller. Areas of the propeller subjected to low-pressure conditions were found to experience intense cavitation, leading to significant performance degradation, including thrust loss, decrease in torque, decrease in the overall efficiency of the model. Additionally, the simulations suggest that optimizing propeller blade shape and operating conditions could mitigate the detrimental effects of cavitation. The findings highlight the importance of considering cavitation dynamics during the design phase and provide a roadmap for improving propeller efficiency, reducing cavitation damage, and enhancing the overall performance of marine propulsion systems.

Due to the general increase in the usage of petroleum resources, drilling of oil wells are frequently done in very challenging and hostile settings. Loss of circulation has been one of the main challenge facing engineers during drilling operations. Hence there have been extensive researches done over the years in order to minimize the impact of loss circulation, however, this have led to a myriad of viewpoints as to what product and method is suitable to battle it. However, a lot of the products and guidelines available for battling lost circulation are often biased towards self-promotion for a particular service company. The purpose of this study is to develop practical guidelines that are universal and not biased towards any particular service company product and which will also serve as a reference guide for lost circulation prevention and control at the well-site for drilling personnel

In Nigeria today and in the world at large, PET bottle waste has grown to become hazardous as it constitutes part of the non-biodegradable waste. Hence, recycling becomes necessary to curb its menace. This project work is centered on designing and fabricating a PET bottle crushing machine from locally sourced materials for both home and industrial use in an attempt to proffer solution to the PET waste problem in Nigeria. Preliminary tests and mechanical factors were extensively evaluated on the conceptual designs to ensure that the design that most suits the purpose was selected and detail design was carried out. Experiment to determine the power required to overcome the shear resistance of the PET bottles was carried out and it was discovered that 10hp at 450N was the power required. Finite element analysis was also performed on the cutting blade to inspect
the materials response to stresses and the corresponding deformation. Furthermore, a design study was carried out in order to ascertain the minimum and maximum loads that can be handled. Tests carried out on the machine showed its efficiency to be 82.2% which is only 6% less than the efficiency of foreign counterparts

This project aimed to design and implement UnibenEngVault, a web-based platform created to provide engineering students of the University of Benin with centralized and convenient access to academic resources such as lecture notes, past questions, and tutorial materials. The initiative was motivated by the persistent difficulty students face in sourcing relevant study materials dueto the lack of a unified and structured digital repository within the Faculty of Engineering. The development followed a structured methodology consisting of project planning and approval, problem analysis, system design, development, and deployment. The UI/UX design was created using Figma to ensure an intuitive and visually appealing interface. The frontend was developed with ReactJS, while the backend was implemented using Python (Flask) and PostgreSQL for database management. AWS S3 was utilized for cloud storage, and deployment was achieved through Docker, GitHub Actions (CI/CD), and DigitalOcean Droplets to ensure scalability and reliability. Security measures such as session authentication, CORS configuration, and bcrypt password hashing were implemented, alongside thorough unit, integration, and user testing. The final outcome is a secure, functional, and user-friendly platform that enables students to easily access department- and level-specific academic materials. UnibenEngVault enhances academic collaboration, improves resource accessibility, and provides a sustainable technological solution to the long-standing challenge of academic material distribution within the Faculty of Engineering

The multipurpose pounding machine was designed with the aim of increasing the range of food that can be processed by the traditional pounding machines while making it compact enough to fit within standard kitchen spaces and portable enough to be moved around easily. It was designed to perform the cooking and pounding of yam, fufu, amala, wheat and yam flour (poundo). The machine was fabricated using stainless steel, mild steel, Bolts and nuts, Screws. The Components of the machine are the beater, the pounding bowl, the steaming pot, the shaft, the heating element, electric motor, contactor, and temperature contoller. After fabrication, the machine was able to cook the various food via the heating element which has a rating of 700watts and pound with the help of an electric motor having a rating of 12v, 500watts that transmits power (via rotary motion) through the shaft to the beaters. The result from the testing showed that the pounding machine produced hygienic products with acceptable texture and consistency.This makes the machine a good home appliance for safe and effective for making pounded yam and other types of swallow.