I.E OBAYAGBONA

The intersection of data science and artistic expression has given rise to innovative forms of generative art, one of which is music visualization. This project, "From Data to Art: Generative Music Visualization," explores the transformation of audio data into dynamic visual representations using computational algorithms and artificial intelligence. The system analyzes real-time music input, extracting key audio features such as frequency, amplitude, and rhythm, and maps these elements to generate visually appealing and interactive graphics.

The project employs signal processing techniques, machine learning models, and creative coding frameworks to develop an immersive audiovisual experience. Technologies such as Python, Processing, WebGL, and TensorFlow are utilized to process and interpret music data, translating it into fluid, evolving visuals that synchronize seamlessly with the audio. The visualization system supports multiple artistic styles, ranging from geometric abstraction to organic particle animations, ensuring a diverse range of expressive outputs.

Through this research, the project aims to enhance the way audiences engage with music by creating a synesthetic experience that bridges sound and visual perception. The study also examines how generative music visualization can be applied in areas such as live performances, virtual reality, and therapeutic environments. Ultimately, this work contributes to the growing field of computational creativity, demonstrating the potential of AI and data-driven techniques in redefining digital art.

The rapid evolution of digital technologies has transformed e-commerce design standards, leaving many early websites outdated and ineffective. This study focuses on the user- centered redesign of a legacy e-commerce interface, using Arngren.net as a case study. The objective was to evaluate the usability and visual experience of the site and to propose a redesign framework that aligns with modern user experience (UX) and interface design (UI) principles. The research adopted a qualitative case study approach, emphasizing heuristic evaluation and comparative analysis. Using Nielsen’s (2020) ten usability heuristics, Arngren.net was assessed for issues relating to layout consistency, navigation flow, accessibility, and visual hierarchy. Findings revealed significant usability flaws, including poor visual organization, low mobile responsiveness, and non-intuitive navigation. These weaknesses were compared with modern e-commerce platforms such as Amazon, eBay, and Shopify-based stores, which prioritize responsive layouts, accessibility compliance, and streamlined user journeys. Based on these insights, a user-centered redesign framework was proposed, integrating simplicity, responsive design, and user trust as key pillars. The redesigned interface emphasizes clear visual hierarchy, improved navigation menus, accessible content structure, and consistency across devices.

The growing demand for energy conservation and sustainable technologies has highlighted the need for intelligent systems to optimize energy consumption in various domains, including lighting. This paper presents the design and implementation of a real-time energy-efficient smart lighting system that integrates advanced sensors, wireless communication, and adaptive control strategies. The system employs motion sensors, ambient light sensors, and time-based algorithms to dynamically adjust lighting levels based on environmental conditions, occupancy, and user preferences. The smart lighting system is capable of reducing energy wastage by automatically dimming or turning off lights in unoccupied spaces, while ensuring adequate illumination when needed. Additionally, the system incorporates real-time monitoring and data analytics to track energy consumption patterns, providing actionable insights for further optimization. Experimental results demonstrate the effectiveness of the proposed system in reducing energy consumption, enhancing user comfort, and contributing to sustainable building management practices. The system offers a scalable solution for residential, commercial, and industrial applications, addressing both environmental and economic goals of energy efficiency