Collaborative Strategies Research Articles

Collaborative Models for Community-Driven Industrial Education: Enhancing Workforce Development Through Partnership Programs in Malaysia

This study analyses the value of collaborative education strategies for improving workforce development in Malaysia, focusing on collaborations between educational institutions and industry. In recent years, the Malaysian job market has experienced major challenges, especially in terms of graduate preparation for employment. Many graduates struggle due to inadequate skills and limited employment opportunities, emphasizing the critical need for comprehensive educational changes. These coordinated activities aim to bridge the education-industry divide by developing connections between academia and the business sector. Moreover, the study uses a qualitative approach, conducting in-depth interviews with industry managers to understand better the impact of partnership programs, government support, and community participation on workforce readiness. Through these interviews, the study emphasizes the importance of collaborative education in providing graduates with the skills and competencies they need to succeed in a competitive work market. The findings show that, while these collaborations significantly boost graduates' employability and skill sets, issues such as unequal access to opportunities and an overreliance on government assistance remain. Furthermore, the analysis discovers gaps in the available literature, particularly in the context of Malaysia, emphasizing the need for further research targeted to this environment. Future research directions will include empirical investigations to quantify the impact of collaborative education initiatives, quantitative analyses to evaluate the efficacy of various programs, and policy recommendations to improve Malaysia's workforce development and foster long-term economic growth. By addressing these issues, the study hopes to contribute to a more comprehensive understanding of how collaborative education may effectively bridge Malaysia’s skills gap.

Fatigue strength reliability assessment of turbofan blades subjected to intake disturbances based on the improved kriging model

This paper aims to develop an efficient and precise reliability analysis method to enhance the numerical prediction accuracy for complex structures. Kriging, an implicit surrogate model, used to address highly nonlinear and complex problems. In this study, genetic algorithms (GA) are utilized to optimize the parameters of the Kriging model, which is then integrated with a distributed collaborative strategy to introduce the Genetic Algorithm Optimized Distributed Collaborative Kriging Model (DCGAK). Using the CFM56-fan blade as a case study, the impact of intake disturbances at the engine inlet is evaluated to assess the fatigue strength reliability of the blade. Comparison with different mathematical models demonstrates that the prediction accuracy of DCGAK closely aligns with the Monte Carlo sampling results, suggesting promising prospects for its application in numerical prediction and reliability analysis. This approach enriches the current methods for structural reliability analysis of complex mechanical systems.

Understanding Career Adapt Abilities, Career Stress, Work Stress, Career Regret, Job Satisfaction Among Nursing Professionals.

This study aims to conduct a comprehensive analysis of the interrelationships among career stress, work stress, career regret, job satisfaction and career adapt abilities within the nursing profession. The research involved a sample of 576 nurses from ten urban hospitals, distributed across five distinct cities in Turkiye, between December 2023 and January 2024. The study employed regression models to systematically test hypotheses, providing nuanced insights into the complex dynamics of the variables under investigation. Regression models were utilized to test the hypotheses systematically, considering the moderating role of career adapt abilities. The study included a sample of 576 nurses from 10 urban hospitals in Turkey, distributed across five distinct cities. This approach allowed for a detailed examination of the intricate relationships between career stress, work stress, career regret, job satisfaction and career adapt abilities within the nursing profession. The findings underscore the delicate balance between the positive gains of job satisfaction and the challenges posed by career stress, work stress and career regret in the multifaceted landscape of nursing. In nursing, the relationship between career stress, work stress, career regret and job satisfaction include progress, resilience and obstacles. Developing strategies requires a cooperative effort from health care organizations, nursing leaders and individual nurses. The research provides valuable insights into the interplay of these factors and emphasizes the moderating role played by career adapt abilities. The implications of the study extend to healthcare organizations, nursing leaders and individual nurses. The research advocates for collaborative strategies aimed at enhancing job satisfaction, alleviating stressors and addressing career regret. The ultimate goal is to contribute to the retention of a resilient nursing workforce, emphasizing the importance of strategies that support the well-being and satisfaction of nurses in their careers. No patient or public contribution.

Technical Innovations and Social Implications: Mapping Global Research Focus in AI, Blockchain, Cybersecurity, and Privacy

This study examines the balance between technical and social focus in artificial intelligence, blockchain, cybersecurity, and privacy publications in Web of Science across countries, exploring the social factors that influence these research priorities. We use regression analysis to identify predictors of research focus and cluster analysis to reveal patterns across countries, combining these methods to provide a broader view of global research priorities. Our findings reveal that liberal democracy index, life expectancy, and happiness are significant predictors of research focus, while traditional indicators like education and income show weaker relationships. This unexpected result challenges conventional assumptions about the drivers of research priorities in digital technologies. The study identifies distinct clusters of countries with similar patterns of research focus across the four technologies, revealing previously unrecognized global typologies. Notably, more democratic societies tend to emphasize social implications of technologies, while some rapidly developing countries focus more on technical aspects. These findings suggest that political and social factors may play a larger role in shaping research agendas than previously thought, necessitating a re-evaluation of how we understand and predict research focus in rapidly evolving technological fields. The study provides valuable information for policymakers and researchers, informing strategies for technological development and international collaboration in an increasingly digital world.

Assessing Clinical Outcomes and Treatment Efficacy in a Patient with Crescentic Glomerulonephritis (CGN)- A Case Report

Crescentic glomerulonephritis (CGN) is a rapidly progressive renal condition marked by crescent formation in the glomeruli, often resulting in end-stage renal disease (ESRD) if not promptly addressed. This case report examines a 54-year-old female with a sudden onset of generalized edema and reduced urine output, which led to her hospitalization. Laboratory evaluations revealed acute renal failure with markedly elevated serum creatinine levels. Despite a background of Antineutrophil Cytoplasmic Antibodies (ANCA)-associated vasculitis, her management was complicated by inconsistent adherence to immunosuppressive therapy. Notably, severe hypertension exacerbated her renal impairment, necessitating immediate intervention. The clinical progression of CGN highlights the critical importance of early diagnosis, continuous monitoring, and a multidisciplinary approach for effective management. Emphasizing patient education and lifestyle modifications, particularly in dietary habits and blood pressure control, can significantly influence treatment outcomes. This case illustrates the urgency of addressing CGN and the necessity of a collaborative healthcare strategy to improve prognosis and enhance the patient's quality of life.

Edge-device collaborative computing for multi-view classification

Motivated by the proliferation of Internet-of-Thing (IoT) devices and the rapid advances in the field of deep learning, there is a growing interest in pushing deep learning computations, conventionally handled by the cloud, to the edge of the network to deliver faster responses to end users, reduce bandwidth consumption to the cloud, and address privacy concerns. However, to fully realize deep learning at the edge, two main challenges still need to be addressed: (i) how to meet the high resource requirements of deep learning on resource-constrained devices, and (ii) how to leverage the availability of multiple streams of spatially correlated data, to increase the effectiveness of deep learning and improve application-level performance. To address the above challenges, we explore collaborative inference at the edge, in which edge nodes and end devices share correlated data and the inference computational burden by leveraging different ways to split computation and fuse data. Besides traditional centralized and distributed schemes for edge-end device collaborative inference, we introduce selective schemes that decrease bandwidth resource consumption by effectively reducing data redundancy. As a reference scenario, we focus on multi-view classification in a networked system in which sensing nodes can capture overlapping fields of view. The proposed schemes are compared in terms of accuracy, computational expenditure at the nodes, communication overhead, inference latency, robustness, and noise sensitivity. Experimental results highlight that selective collaborative schemes can achieve different trade-offs between the above performance metrics, with some of them bringing substantial communication savings (from 18% to 74% of the transmitted data with respect to centralized inference) while still keeping the inference accuracy well above 90%.

Enhancing Collaboration and Interdisciplinary Strategies for Navigating Innovative Technologies and Regulatory Approvals in the Cosmetic Industry

Abstract: The cosmetic industry, driven by innovation, constantly seeks safer, more effective, and sustainable products. However, regulatory hurdles often impede the introduction of innovative cosmetics. This paper explores the convergence of advanced technologies and regulatory conformity, emphasizing the need for collaborative, interdisciplinary approaches. Through an extensive review of literature and case studies, we reveal the multifaceted challenges within the industry. These encompass shifting consumer expectations, ingredient safety concerns, and intricate global regulations. Cross-functional collaborations, uniting researchers, regulators, industry experts, and consumers, are pivotal, driving innovation while ensuring product safety and compliance. Our research stresses the importance of a proactive, all-encompassing approach to product development. This approach should integrate cutting-edge technologies, rigorous safety assessments, and smart regulatory strategies from project inception. Additionally, it emphasizes engaging stakeholders, sharing knowledge, and practicing transparency to earn trust from consumers and regulators. This paper provides a comprehensive overview of the balance between innovation and regulation in the cosmetic industry, advocating for a paradigm shift characterized by collaboration and interdisciplinary efforts. By aligning innovation with regulatory compliance, the industry can effectively navigate the complex landscape of modern cosmetics, fostering the creation of safer, more sustainable, and consumer-centric products.

Praktik Ekonomi Lokal Masyarakat Melalui Bisnis Mangga dalam Perspektif Fikih Muamalah

This research aims to examine community economic empowerment through the mango business from the perspective of muamalah fiqh in Oro-Oro Ombo Kulon Village, Rembang District, Pasuruan Regency. Using a descriptive qualitative approach, this research identifies the economic potential of the mango business in the village and analyzes the application of muamalah fiqh principles in every aspect of the business. The research results show that Oro-Oro Ombo Kulon Village has great potential in mango cultivation and economic empowerment through this business has had a positive impact on the local community. The application of the principles of muamalah fiqh, such as justice, transparency and honesty, in the mango business also creates an ethical and sustainable business environment. This research provides recommendations for infrastructure development, training, product diversification, collaboration, and marketing strategies that can increase the effectiveness of economic empowerment through the mango business and create a business model that is in accordance with Islamic principles.

Synergistic enhancement for energy-saving, emission reduction and profit improvement in iron and steel manufacturing system: Strategies for parameter regulation and technologies integration

The steel industry, characterized by high energy consumption and carbon emission, poses a significant threat to global energy and environmental security. In response to the energy conservation and dual-carbon targets, the steel industry must urgently find sustainable pathways for transformation and development. Steel production structure optimization and the application of cutting-edge technologies have been proven to be highly effective. However, the complexity and variability of actual production conditions highlight the absence of a methodology capable of adapting to real production scenarios, elucidating influencing principles across multiple factors, analyzing synergistic mechanisms of multiple indicators, and proposing collaborative control strategies. Furthermore, the potential for technology applications that are closely integrated with the company’s resource endowment remains uncertain, leading to an unclear overall strategy for energy saving and carbon reduction. This study develops a multi-scale optimization and evaluation model for ISMP, incorporating interconnected and matching processes, as well as nested multi-indicators, in response to the context. Subsequently, the disturbance mechanisms of various factors are accurately identified and a multi-indicator synergistic control strategy and framework are proposed. Following optimization, the exergy loss, energy consumption, carbon emission intensity, cost, and pollutant emissions of ISMP per tonne of steel are reduced by 1418.70 MJ, 42.93 kgce, 154.79 kg, 171.21 CNY, and 0.0168 kg, respectively. Additionally, measures such as reducing moisture content in coking coal can effectively regulate multiple indicators. Based on the proposed sensitivity quantification method, the temperature of hot blast is identified as the most effective controllable factor. Technologies like hydrogen-rich fuel injection, integrated waste heat recovery, and solar photovoltaic & energy storage have shown favorable prospects, according to analysis conducted from various angles regarding economic viability and potential for energy-saving and carbon reduction. However, the application of aforementioned technologies may be limited by financial consideration, necessitating cautious and judicious investment choices.

An on-demand collaborative edge caching strategy for edge–fog–cloud environment

In this paper, we tackle the critical challenges of content edge caching, such as limited storage capacity, content popularity prediction, dynamic user demand, and user privacy, issues that most existing studies only address partially. We present an innovative Genetic Algorithm-based On-demand Collaborative Edge Caching mechanism (GAOCEC), which introduces a multi-tiered caching architecture integrating cloud, fog, and edge computing. To enhance caching efficiency and minimize system cost, a novel on-demand caching quota mechanism is proposed that dynamically allocates cache resources to edge servers. To strengthen user privacy protection during content popularity prediction, a CNN-BiLSTM-based Federated Learning algorithm (CBFL) is presented that ensures high prediction accuracy without the need to upload local data to the cloud. We also refine the genetic algorithm for content placement by fine-tuning various parameter sets to identify the optimal balance between latency reduction and caching cost. Our experimental results validate the effectiveness of our approach, demonstrating increased cache hit rates, decreased content response times, and an overall improvement in system efficiency. This work provides a comprehensive, adaptive, and privacy-preserving solution for the edge–fog–cloud environment.

Construct an instructional approach based on collaborative learning and reflective learning for enhance students’ analytical thinking and critical thinking skills

In the context of rapid globalization and digitalization, the development of students' critical and analytical thinking skills is increasingly prioritized in education. This study aims to address the gap in instructional models by designing an eight-step instructional model that integrates collaborative and reflective learning strategies to enhance these essential skills. Drawing on social constructivist theories and Dewey's reflective thinking framework, the research develops a comprehensive model that includes phases such as goal setting, team formation, exploration, collaborative practice, reflection, integration, and feedback. The findings suggest that this model significantly improves students' analytical and critical thinking abilities by promoting structured collaboration and intentional reflection. Through diverse group interactions and continuous self-assessment, students achieve a deeper understanding and critical analysis. The model's iterative feedback mechanisms also contribute to sustained improvements in student learning outcomes. This study introduces an original instructional model that theoretically supports the enhancement of analytical and critical thinking skills through a systematic integration of collaborative and reflective learning, offering practical implications for educators seeking to foster these higher-order thinking skills in students.

Optimization of the age of correlated information in V2X networks with edge computing

Vehicle-to-Everything (V2X) communication has the potential to revolutionize the travel experience in intelligent transportation, which has received the great attention recently. However, ensuring the freshness of information from multiple sources is critical for the real-time and reliable communication in vehicular networks, especially for timely updates of service centers. To address this issue, we use a promising metric called Age of Correlated Information (AoCI), which can characterize the freshness of multi-source information. Therefore, we propose a novel model that can dynamically regulate the channel activation matching and edge computing collaboration strategy to minimize AoCI in V2X vehicular networks. Firstly, we describe the system model of a V2X network with edge computing, including definitions and assumptions for freshness of information, edge co-computing, etc. Secondly, we formulate the joint optimization problem as a source-related age minimization (SRAM) problem, which is NP-complete. A heuristic algorithm is proposed to solve it under fast-fading channel. Finally, since traditional graph models cannot capture the changing correlation between nodes in dynamic networks, we use graph convolutional networks(GCN) to extract the features of multi-source correlation. The features extracted by GCN include relevant attributes of the sources and its communication links. The features are provided as input to a double deep Q network (DDQN) for training the model that can adapt to a dynamic network environment. Extensive simulation experiments in different network scenarios validate that our proposed method can effectively and efficiently reduce the average AoCI and the computational resources.

Towards common ground: Strategies for effective collaboration between the humanitarian and peacebuilding communities

Abstract In an era marked by growing conflicts, prolonged humanitarian needs and less donor funding, collaboration between the humanitarian and peacebuilding sectors is essential for more effective responses. This paper examines the complexities of fostering such collaboration, emphasizing the importance of integrated multisectoral approaches capable of addressing both immediate necessities and long-term peace and development objectives. While recent initiatives such as the humanitarian–development–peace nexus framework and the United Nations Secretary-General's Agenda for Humanity reflect progress toward integrated approaches, substantial collaborative challenges persist. This paper identifies three key entry points for mutual learning between humanitarian and peace actors. Firstly, it discusses a “peace-responsive” approach to humanitarian activities that proactively contributes to “peace-positive” outcomes. Secondly, it emphasizes the need for the peace sector to learn from humanitarian efforts regarding accountability to affected communities. Thirdly, it underscores the need to understand the normative foundations of each sector and their implications for joint action. Drawing on these insights, the paper offers recommendations for policy-makers and practitioners to help them advance joint approaches to humanitarian assistance and peacebuilding in conflict-affected contexts.

Parents' Role in Fostering Islamic Culture at SD Muhammadiyah 2

Background: The need for character education in Indonesian schools underscores the importance of integrating Islamic values into the educational framework. Specific Background: This study examines parental involvement in fostering an Islamic culture at SD Muhammadiyah 2 Tulangan, highlighting challenges in parents' understanding and engagement with Islamic values. Knowledge Gap: There is limited research on the effectiveness of parental participation in promoting Islamic values in schools, despite existing policies. Aims: The research aims to assess parental synergy's role in building an Islamic culture and identify strategies for enhancing collaboration between parents and educators. Results: Findings reveal significant gaps in parents’ understanding and involvement, exacerbated by technological influences and differing interpretations of Islamic teachings. Novelty: The study proposes a framework to strengthen parental engagement through communication, workshops, and collaborative activities. Implications: The results emphasize the need for an integrated approach that involves both parents and teachers to foster a strong Islamic educational environment, ultimately developing students with robust character and essential life skills. Highlights : Parental Engagement: Essential for fostering an Islamic culture in schools. Understanding Gaps: Parents often lack knowledge of Islamic values and their importance. Collaborative Strategies: Effective communication and workshops can enhance synergy between parents and educators. Keywords: Islamic education, parental involvement, character development, educational framework, SD Muhammadiyah 2 Tulangan

Web-based human-robot collaboration digital twin management and control system

Human-robot collaboration presents a promising application in customized production. The utilization of digital twin technology, an advanced form of virtual reality interaction, is pivotal in augmenting the capabilities of human-robot collaboration by enhancing perception and interaction dynamics. Human-robot collaboration digital twins have been proposed to create collaboration strategies, simulate collaborative processes, and guarantee individual safety. Nevertheless, there remain obstacles in the implementation of digital twins within human-robot collaboration. One notable challenge involves developing a user-friendly and easily accessible digital twin management and control system that is well-suited for human-robot collaboration. The human-robot collaboration digital twin is a sophisticated system that encompasses both physical and virtual environments. Effectively managing diverse resources within this system, devising collaboration strategies, and overseeing the collaboration process is essential for the standardized utilization of digital twins in human-robot collaboration. In response to the specific requirements of digital twins in this context, a web-based system has been conceptualized and implemented for managing and controlling human-robot collaboration digital twins. The system is structured based on the browser/server architecture model. Its functional design is implemented through a modular approach. The server-side database management system chosen is MySQL, while the programming and development of the control system are carried out using the Microsoft.Net Framework 4.8 on the Visual Studio 2022 platform. The system’s functional modules are exemplified through a case study on human-robot collaborative assembly. The findings of this study offer insights that can guide the standardized management and application of digital twins within the realm of human-robot collaboration.

Joint Management Plans in World Heritage serial nominations: the case of Álvaro Siza’s Modern Contextualism Legacy

One of the most important challenges faced by any listed cultural heritage is the development of a management system that conveys a resilient and integrated approach that can sustain its values for future generations. Management is one of the main factors affecting World Heritage Sites; thus, the increased complexity of a serial nomination enhances this risk. By integrating different stakeholders, a Joint Management Plan (JMP) is a key tool to settle common procedures and help different managers maintain a satisfactory balance in safeguarding the Outstanding Universal Value (OUV) in each component part. This paper aims to provide a framework for the development of JMPs for serial nominations, with support on the nomination proposal “Álvaro Siza’s Architecture: A Modern Contextualism Legacy”. Methods result from the cross-analysis of (i) policy analysis; (ii) archival research and digital documentation; (iii) collaborative strategies (surveys, interviews, workshops, meetings, consultations); (iv) fieldwork. Results confirmed that the development of JMPs must be sustained by an open and dynamic process, where engagement, mediation of conflicts, and flexibility are key principles. This work approaches a significant subject concerning the management of World Heritage serial nominations, focusing on JMPs for serial nominations, which are a rising trend in heritage management. A demonstration is applied to the WH nomination of works by Álvaro Siza, a prominent figure in worldwide contemporary architecture.

A Strategic Framework of SARS-CoV-2 Genomic Surveillance in Bangladesh.

The global pandemic caused by SARS-CoV-2 has underlined the significance of strict genomic surveillance to track virus evolution and the possible emergence of new variants, particularly in densely populated countries like Bangladesh. This study outlines a strategic framework of genomic surveillance to track the evolution of the virus in Bangladesh between June 2021 and December 2022 through the National SARS-CoV-2 Variant Surveillance (NSVS) program involving collaboration across 4 major institutes and 13 hospitals nationwide. We aimed to capture the variants of SARS-CoV-2 throughout the country utilizing standardized procedures, modern sequencing technology, and stringent quality control, promoting data accuracy and the timely detection of new variants of concern. We sequenced over 2200 genomes, documenting the prevalence of the Delta variant initially, followed by the emergence of Omicron variants BA.1, BA.2, BA.5, and XBB, each affecting transmission rates and vaccine efficacy differently. The clinical manifestations of the variants differed, with some symptoms occurring more frequently in Delta cases and vice versa. Vaccinated individuals were more affected by Omicron cases compared to Delta cases. These variants were responsible for two major COVID-19 waves in the country, each with significant clinical effects. Phylogenetic analyses placed the local SARS-CoV-2 variants within a global context, indicating the Delta variant likely entered from India and Omicron from Europe. This research highlights the significance of collaborative surveillance strategies for guiding public health choices and the critical role of genomic analysis in monitoring virus evolution, shaping targeted pandemic responses. Bangladesh's contributions significantly enhance global insight into COVID-19's genomic evolution.

Development and evaluation of a collaborative reflection-based debriefing strategy for simulation-based education using virtual simulations in practical nursing: A randomized controlled trial

AimTo develop and validate a debriefing strategy for simulation-based education in practical nursing that fosters collaborative reflection and enhances nursing competencies. The study assesses the effects on knowledge, problem-solving skills, self-confidence in clinical decision-making, reflective thinking and student satisfaction. BackgroundAdvancements in medical technology and the evolving healthcare landscape have increased nurses’ expectations, prompting nursing education to emphasize practical skills in addition to theoretical knowledge. The shortage of clinical practice wards, increased nursing school enrollments and a focus on patient rights have expanded traditional simulation-based education to include virtual clinical scenarios. MethodA randomized controlled trial was conducted with 66 fourth-year nursing students (34 in the experimental group and 32 in the control group) at Dongseo University, Pusan, Republic of Korea (IRB No. 2021-023-HR-02). The collaborative reflection-based debriefing comprised four phases: pre-debriefing, emotional relief, exploration of alternatives and expansion of thinking. The experimental group had three intervention sessions; the control group underwent individual debriefing after completing a structured reflective questionnaire. Outcomes were assessed post-intervention and at four and eight weeks. Data were analyzed using independent t-tests and repeated-measures analysis of variance (mixed model). ResultsThe experimental group exhibited significantly greater improvements in knowledge, problem-solving skills, self-confidence in clinical decision-making, reflective thinking and satisfaction than the control group. ConclusionCollaborative reflection-based debriefing in simulation-based education can improve the nursing competency required in clinical settings.

Research on the collaborative operation strategy of shared energy storage and virtual power plant based on double layer optimization

Large-scale access to distributed energy resources leads to new energy consumption problems and safe operation risks in the power system. Virtual power plants and shared energy storage are effective ways to promote the flexible consumption of distributed energy resources and improve the reliability and economy of power system operation. Based on the concept of sharing economy and considering the complementary characteristics of source and load resources between different virtual power plants, this paper focuses on the optimisation of shared energy storage and multi-virtual power plant operation. Firstly, distributed wind power, distributed photovoltaic and flexible load resources are aggregated into virtual power plants to analyze the cooperative operation mode of shared energy storage and multi-virtual power plant systems. Secondly, a two-layer decision model for shared energy storage configuration and multi-VPP system operation optimisation is constructed, with the upper model solving the optimal energy storage configuration scheme by maximising the revenue of the shared energy storage operator, and the lower model optimising the multi-VPP system operation strategy by minimising the total operation cost, the maximum amount of new energy consumed, and the minimum amount of carbon emission as the multi-objective optimisation strategy. Finally, a simulation analysis is carried out, and the results show that compared with the independent operation mode of each virtual power plant, the model proposed in this paper increases the annual profit of the shared energy storage operator by 7180¥, reduces the operating cost of the VPP system by 7.08 %, improves the rate of renewable energy consumption by 0.82 %, and reduces the annual carbon emission by 54.91 t, which realizes the mutual benefits of the virtual power plant and the shared energy storage.

Research on Collaborative Defense Method of Hospital Network Cloud based on End-to-end Edge Computing

This research introduces a groundbreaking collaborative defense mechanism that utilizes end-to-end edge computing to bolster the security of decentralized hospital cloud systems. By integrating intrusion detection systems, firewalls, anomaly detection, and threat intelligence in a unified manner through the efficiency of edge computing, this approach marks a significant advancement in healthcare cybersecurity. Through rigorous testing with a substantial dataset, the system demonstrated exceptional performance metrics, including a remarkable 95% accuracy in threat detection, a low false positive rate, and a swift response time of merely 0.25 seconds. Notably, the system effectively mitigates computational overhead, thereby optimizing resource utilization. Comparative analysis with existing methodologies underscores the superiority of this novel framework, particularly in terms of geolocation accuracy, the minimization of false positives, and expedited reaction capabilities. This study’s collaborative defense strategy, underpinned by end-to-end edge computing, presents a holistic and innovative solution to the escalating cyber threats facing healthcare infrastructures. By redefining the parameters of security in medical settings, it paves the way for a safer and more resilient healthcare information technology ecosystem.