DEPARTMENT OF MECHATRONICS ENGINEERING

Automated gate systems have become essential in modern residential security due to the need for controlled access and reduced manual operation. Traditional manually operated gates often pose safety risks, increase security vulnerabilities, and require physical effort from users. This project presents the virtual design and simulation of an automated residential sliding gate using SolidWorks for mechanical modeling and Proteus for electronic control simulation. The system integrates key mechanical components such as the gate frame, rollers, track, and rack-and-pinion mechanism, alongside a microcontroller-based control circuit designed to operate the motor responsible for gate movement. The SolidWorks simulation was used to analyze the gate’s mechanical performance, focusing on linear motion, component alignment, and the conversion of rotational motor input into smooth sliding action. Proteus was employed to simulate the automation logic, including motor activation, direction control, and stopping at predefined limits. These simulations allowed full validation of system behavior without physical prototyping, reducing cost and eliminating real- world testing constraints. Results from both platforms confirmed that the gate moves smoothly, responds correctly to control inputs, and maintains proper synchronization between mechanical and electronic subsystems. The study demonstrates that virtual simulation tools provide an effective method for evaluating automated gate mechanisms before fabrication. The design also offers a foundation for future enhancements such as remote wireless control, improved safety features, and integration with smart-home systems.

An Automated Residential Gate project aims to enhance security, convenience, and energy efficiency through the integration of automation and solar power technology. Traditional manual gates require significant human effort and are often inconvenient, especially for large or heavy gates. To address these issues, this project involves designing an automated sliding gate system controlled by remote access, keypads, and IOT connectivity. The system incorporates a D5V6 Smart Centurion Machine, a 60W solar panel, a 30A charge controller, and a deep-cycle battery to ensure uninterrupted operation, even during power outages. The design includes a 0.37 kW motor with a gearbox to enhance torque efficiency, along with infrared sensors for obstacle detection and limit switches for precise movement control. Safety features such as emergency manual release and predictive maintenance alerts further improve usability and reliability. Structural materials such as steel and corrosion-resistant components ensure durability under various environmental conditions. Through performance testing, the system demonstrated smooth operation, energy efficiency, and enhanced security compared to conventional gates. The solar-powered system effectively reduces reliance on grid electricity, making it a cost-effective and sustainable solution. Future improvements may include AI-driven security enhancements and higher-efficiency solar panels to further optimize performance.

With increased urbanization and the growing need for better sanitation hygiene practices across several countries, including many developing nations such as Nigeria, there was a great need for better sanitary facilities that would allow for cleaner sanitation. Most conventional latrines have required high manual intervention and constant maintenance, creating an environment that is often dirty, wastes water, and does not have enough cleaning facilities, even in places like restrooms at homes and public places. Despite some innovative restrooms being designed before, the majority of such restrooms either lack feasibility financially or do not contribute effectively to smart hygiene monitoring. The smart toilet design mentioned in this paper seeks to overcome the above challenges. The proposed system comprises User Detection using Sensors, automatic Flushing, Optimization of Water Usage, Surface Hygiene monitoring, with Logic implemented using a microprocessor, and Wireless Communication as well. The design employs Infrared and Proximity Sensors for detecting the presence of the user and seat usage. The system utilizes solenoid valves for controlling the amount of water used in flushing. Furthermore, the proposed system will incorporate Adaptive Flushing Logic whereby the amount of water will be optimized to improve its usage and conserve more water. Testing will be done to evaluate the performance and ensure the proper functioning of the sensors and accuracy of the flushing. After completion of the project, the expected outcome would be a working smart toilet with automatic flush capability. Moreover, after testing it is expected that the system will be capable of reliably detecting users and communicating wirelessly while optimizing water usage as well as ensuring restroom hygiene. Not only is the project useful for home and public usage but also it will go a long way to improving the sanitation level in the ever-growing cities.

This research presents the design and implementation of a low-cost Artificial Intelligence-Based Battery Management System (AI-BMS) for lithium-ion batteries used in portable devices, solar power systems, and small electric vehicles. The study addresses thelimitations of existing systems-traditional thres hold based BMS that offer only reactive protection, and commercial smart BMS that are prohibitivelyexpensive and powerhungry.Using real degradation data from the NASA Prognostics Data Repository,an XGBoost machine learning model was developed to predict the State of Health (SoH) anddetect early thermal runaway precursors through voltage, current, and temperature trends. The trained model was deployed on an ESP32 microcontroller, integrated with low-cost sensors (INA3221 and ADS1115) and a 128×64 LCD for live system feedback.The AI-BMS achieved ±1.87% SoH accuracy, 100% safety response in fault simulations, and an average response time of 0.82 seconds, all at a total cost of approximately ₦22,450 ($18). Compared to conventional threshold-only protection and mid-range commercial BMS units, the proposed system offers proactive fault detection, predictive analytics, and real-time monitoring at a fraction of the cost and power consumption (35–48 mA). This study demonstrates that affordable, intelligent, and locally assembled BMS solutions can significantly enhance battery safety, extend lifespan, and democratize access to advanced energy storage technologies in developing regions.