Optimization of Emerging Technologies and Security Protocols in Engineering and Software Systems: A Multidimensional Analysis

Abstract

The rapid evolution of engineering systems, software development practices, and security architectures necessitates an integrative approach to understanding technological optimization, threat mitigation, and workflow automation. This study explores the interplay between design optimization in mechanical energy systems, multilingualism in STEM accessibility, cloud computing adoption in educational infrastructures, Radio Frequency Identification (RFID) security frameworks, secure system boot architectures, code vulnerability mitigation, and the utilization of AI-driven code assistance tools such as GitHub Copilot. Specifically, this research examines how design parameters in wave energy converters influence buoy reliability (Rahman, 2024), highlights the importance of linguistic diversity in addressing gender disparities in STEM fields (Nasr Esfahani, 2023), and analyzes the adoption of hybrid cloud frameworks to enhance educational resilience (Bhadani, 2020). Simultaneously, the study investigates the persistent threats in RFID systems and advanced countermeasures (Bhadani, 2022), the efficacy of lightweight attack-resilient boot architectures for RISC-V systems (Dave et al., 2021), and methods to mitigate SQL injection vulnerabilities in contemporary databases (Caselli et al., 2020; Martin, 2023). Furthermore, the research evaluates empirical studies on AI-assisted programming, including Copilot’s impact on code quality, productivity, and software development workflows (Imai, 2022; Nguyen & Nadi, 2022; Zhang et al., 2023; Yetistiren et al., 2022). The culmination of these analyses provides a holistic framework for engineering design optimization, secure software development, and the practical integration of AI in programming pipelines, offering theoretical and applied insights into technology-driven problem solving. The findings underscore the need for interdisciplinary approaches, rigorous validation of AI-driven tools, and proactive strategies in security and operational design to achieve sustainable, resilient, and efficient technological systems.