Emerging Technologies in Secure Data Sharing, Predictive Maintenance, and Autonomous Systems in 5G Networks

2024-09-25T14:23:30-06:00

This paper explores the integration of 5G communication, UAV systems, predictive maintenance, and NFV to address challenges in healthcare, smart grids, and autonomous vehicle navigation. The rapid development of 5G-enabled technologies has transformed secure data sharing in healthcare networks, optimized smart grid performance, and enhanced autonomous driving capabilities. These advancements, driven by multi-source data fusion, machine learning, and hybrid V2X-UAV frameworks, demonstrate the potential of modern technologies to revolutionize existing systems. This paper reviews the state-of-the-art approaches in predictive maintenance, secure communication protocols, and sensor fusion, highlighting the critical role of 5G and advanced analytics. The research focuses on the technological synergies and innovations that drive these applications, discussing the challenges, benefits, and future implications of integrating these systems. By drawing on diverse studies, this paper aims to provide a comprehensive overview of the latest advancements in 5G-enabled networks and their impact on healthcare, smart grid optimization, and autonomous vehicle navigation.

Evaluating Sustainable Development Frameworks for Transforming Agricultural Practices through Integrative Resource Management Approaches in Developing Economies

2024-11-08T13:21:54-07:00

Sustainable development in agriculture within developing economies has gained significant attention due to the critical need for food security, environmental protection, and economic viability. As agricultural practices largely rely on natural resources, integrating sustainable frameworks that emphasize efficient resource management can potentially transform these practices. This paper evaluates existing sustainable development frameworks for agriculture, with a particular focus on their application in developing economies where resource constraints and environmental challenges are pervasive. By examining integrative resource management approaches, such as ecosystem-based management (EBM), agroecology, and circular economy principles, this paper seeks to identify strategies that are both economically feasible and environmentally sound. A comprehensive analysis of these frameworks is conducted, highlighting their strengths, limitations, and applicability in varied agricultural contexts within developing regions. Key challenges faced by developing economies, including resource degradation, climate variability, and economic limitations, underscore the need for sustainable agricultural practices that not only increase productivity but also enhance resilience to environmental stressors. This paper proposes a multi-criteria assessment methodology for evaluating the effectiveness of sustainable frameworks and suggests context-specific adaptations to better align with local socio-economic and ecological conditions. Through a synthesis of recent studies and case examples, the analysis identifies factors that contribute to successful implementation, such as policy support, community engagement, and knowledge-sharing systems. The findings indicate that integrative resource management approaches, when adapted to the unique challenges of developing economies, can lead to more sustainable agricultural practices, improved livelihood resilience, and better ecosystem services. Conclusively, this paper argues that the adoption of sustainable development frameworks requires both structural changes and participatory approaches to ensure that resource management strategies are inclusive, locally adapted, and sustainable over the long term.

Journal of Humanities and Applied Science Research

Emerging Technologies in Secure Data Sharing, Predictive Maintenance, and Autonomous Systems in 5G Networks

Evaluating Sustainable Development Frameworks for Transforming Agricultural Practices through Integrative Resource Management Approaches in Developing Economies