Journal of Advanced Technology and Systems

Integration of Artificial Intelligence in Cyber-Physical Systems

James Analo — 2024-01-11

This study on the integration of Artificial Intelligence in cyber-physical systems advances Socio-Technical Systems theory, offering crucial insights for policymakers to formulate ethical guidelines and targeted interventions addressing human factors, ultimately shaping responsible innovation in the evolving landscape of AI integration. The main objective of this study was to explore the integration of Artificial Intelligence (AI) in cyber-physical systems. The study was anchored on the Socio-Technical Systems (STS) Theory. The study conducted a thorough review and synthesis of diverse scholarly works on integration of Artificial Intelligence in cyber-physical systems, aiming to gain insights into key theories, methodologies, findings, and gaps in the existing body of knowledge. This study revealed significant advancements in efficiency and adaptability across sectors like manufacturing and transportation. Studies by Smith et al. (2012) and Li et al. (2015) showcased the broad applicability of AI, leading to reduced downtime and optimized traffic flow. Additionally, ethical considerations, as highlighted by Chen et al. (2014), emphasized the need for careful addressing of issues such as data privacy and algorithmic bias. The study underscores the promising technological advancements in AI integration while emphasizing the critical importance of responsible and ethical deployment, prompting the ongoing development of guidelines for sustainable implementation. The findings from studies on AI integration in Cyber-Physical Systems (CPS) showcase transformative potential across industries, demonstrating positive impacts on efficiency and adaptability. However, ethical challenges, including data privacy and algorithmic bias, emphasize the need for a responsible AI integration, warranting ongoing attention and guideline development. In terms of contributions, the study advances Socio-Technical Systems theory and offers valuable insights for ethical guidelines and regulatory frameworks. It highlights the importance of addressing human factors in AI adoption, providing guidance for policymakers promoting AI integration within organizations and communities. Overall, these contributions form a solid foundation for advancing theoretical frameworks and shaping policy recommendations in the evolving landscape of AI integration in Cyber-Physical Systems.

Blockchain Technology for Secure and Transparent Supply Chain Management Systems

Gunther Theo — 2024-01-11

In an era marked by the increasing complexity and globalization of supply chains, this study explores the transformative potential of blockchain technology as a catalyst for achieving unprecedented levels of security and transparency in supply chain management systems. The main purpose of the study was to examine blockchain technology for secure and transparent supply chain management systems. The study was anchored on the Diffusion of Innovations Theory. The study conducted a thorough review and synthesis of diverse scholarly works on blockchain technology for secure and transparent supply chain management systems, aiming to gain insights into key theories, methodologies, findings, and gaps in the existing body of knowledge. This study highlights blockchain's transformative potential in enhancing security and transparency in supply chain management. Blockchain's decentralized, tamper-resistant nature reduces risks of fraud and counterfeiting, ensuring data integrity. It improves transparency by offering real-time visibility into the movement of goods and fostering trust among stakeholders. As a key enabler, blockchain revolutionizes supply chain collaboration, addressing security and transparency concerns for more resilient and efficient systems. In conclusion, the study on "Blockchain Technology for Secure and Transparent Supply Chain Management Systems" offers a thorough examination of blockchain's potential impact on supply chain dynamics, emphasizing its decentralized and tamper-resistant nature as a promising solution to enhance security and transparency. Theoretical frameworks, including the Diffusion of Innovations theory, guide the exploration of blockchain adoption factors, highlighting its significance in addressing challenges such as security breaches and lack of transparency in supply chains. Conceptually, the study underscores blockchain's role in improving accountability, traceability, and disrupting existing power structures within supply chains. Methodologically, it advocates for future research to empirically validate theoretical and conceptual insights through large-scale quantitative assessments of blockchain adoption in diverse supply chain environments. Overall, the study contributes not only to theoretical understanding but also holds practical implications for policy, informing decision-makers and policymakers about the potential of blockchain to bolster security and transparency in supply chains. The research lays a foundation for future empirical investigations and offers insights crucial for shaping regulations and guidelines in the evolving landscape of supply chain management.

Quantum Computing Algorithms for Solving Complex Optimization Problems

Nice Njeri — 2024-01-11

In the pursuit of revolutionizing computational capabilities, quantum computing has emerged as a transformative frontier. This study delves into the exploration of Quantum Computing Algorithms designed to address the intricacies of solving complex optimization problems, aiming to unravel the potential and challenges that quantum approaches bring to the forefront of computational science. The main purpose of this study was to investigate the potential applications and effectiveness of quantum computing algorithms in solving complex optimization problems, with a focus on real-world systems and technological implications. This study was anchored on two major models, that is, Quantum Approximate Optimization Algorithm (QAOA) and the Grover's Quantum Search Algorithm. The study conducted a thorough review and synthesis of diverse scholarly works on quantum computing algorithms for solving complex optimization problems, aiming to gain insights into key theories, methodologies, findings, and gaps in the existing body of knowledge. In conclusion, this study significantly advances our understanding of quantum algorithms' potential and challenges in solving complex optimization problems. Quantum algorithms, particularly Quantum Approximate Optimization Algorithm (QAOA) and Grover's Quantum Search Algorithm, show promise in providing speedup and efficiency compared to classical counterparts, hinting at the transformative impact of quantum computing. Research gaps identified, such as the need for more empirical studies and exploration of fault-tolerant quantum computing, underscore the ongoing nature of quantum optimization research. The study contributes to theory by showcasing QAOA and Grover's Algorithm's potential, enriching our foundational understanding of quantum algorithms. On the policy front, the study emphasizes the importance of fostering an ecosystem supporting quantum computing integration into practical applications. The applicability of quantum-inspired genetic algorithms in logistics optimization suggests policies encouraging exploration and implementation of quantum-inspired approaches. Additionally, identified research gaps in scalability and fault tolerance highlight the need for policies promoting investments in quantum computing research and infrastructure. The study's contributions extend to ethical and regulatory considerations, urging policymakers to anticipate and address ethical implications, privacy concerns, and security risks associated with advancing quantum technologies. Policymakers are encouraged to consider the theoretical insights to inform policies facilitating the practical integration and ethical deployment of quantum computing technologies.

Integration of Augmented Reality (AR) in Healthcare Systems

Rasim Kalhoro — 2024-01-11

As healthcare systems globally embrace technological innovation, the integration of Augmented Reality (AR) emerges as a transformative force with the potential to revolutionize patient care, professional training, and overall healthcare performance. The main objective of this study was to investigate the use of augmented reality in healthcare settings, exploring its potential for improving patient care, medical training, and surgical procedures. This study was anchored on the Technology Acceptance Model (TAM). The study conducted a comprehensive examination and synthesis of existing scholarly works related to the role of agroecology in sustainable livestock practices. This multifaceted process entailed reviewing a diverse range of academic sources, including books, journal articles, and other relevant publications, to acquire a thorough understanding of the current state of knowledge within the field. Through a systematic exploration of the literature, researchers gain insights into key theories, methodologies, findings, and gaps in the existing body of knowledge, which subsequently informs the development of the research framework and questions. The exploration of Augmented Reality (AR) integration in healthcare systems highlights its transformative potential with positive impacts on surgical precision, professional training, and patient engagement. However, challenges like data security, usability issues, and ethical considerations underscore the need for cautious implementation. The observed heterogeneity in study designs calls for refined evaluation metrics and contextual understanding. The study significantly contributes to theoretical understanding by applying the Technology Acceptance Model (TAM) and addressing ethical dimensions, shedding light on privacy concerns. In policy realms, it informs the development of guidelines and regulations, offering insights into potential barriers and emphasizing cultural and contextual considerations for responsible AR integration into diverse healthcare systems. Overall, the study's contributions bridge theoretical gaps and provide practical guidance for policy formulation in the evolving landscape of AR integration in healthcare.

5G Network Integration for Ultra-Reliable Low Latency Communications (URLLC)

Chumo Kipng’etich — 2024-01-18

Amidst the rapidly evolving landscape of telecommunications, this study delves into the intricate dynamics of 5G network integration for Ultra-Reliable Low Latency Communications (URLLC), aiming to unravel the promises, challenges, and transformative potential that this cutting-edge technology holds across diverse applications and industries. The main purpose of this study was to explore 5G network integration for Ultra-Reliable Low Latency Communications (URLLC). This study was anchored on the Information Theory and Communication Engineering. The study conducted a comprehensive examination and synthesis of existing scholarly works related to 5G network integration for Ultra-Reliable Low Latency Communications (URLLC). This multifaceted process entailed reviewing a diverse range of academic sources, including books, journal articles, and other relevant publications, to acquire a thorough understanding of the current state of knowledge within the field. Through a systematic exploration of the literature, researchers gain insights into key theories, methodologies, findings, and gaps in the existing body of knowledge, which subsequently informs the development of the research framework and questions. The collective findings from studies on 5G network integration for Ultra-Reliable Low Latency Communications (URLLC) reveal both promises and challenges, highlighting 5G's potential to enhance communication in critical sectors while addressing issues like network congestion and limited infrastructure. The studies emphasize the importance of tailored optimization strategies and standardized protocols for seamless integration. The need for a unified conceptual framework and standardized methodologies is underscored to ensure consistent assessment of URLLC performance in 5G networks. In conclusion, while 5G shows transformative potential, a comprehensive approach is essential. The studies contribute to theory by developing varied conceptual frameworks and offer valuable policy insights for regulatory frameworks and industry standards, emphasizing the necessity of an enabling environment for 5G adoption to align with broader societal goals across diverse sectors.