Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities

AIMS Public Health, Год журнала: 2024, Номер 11(1), С. 58 - 109

Опубликована: Янв. 1, 2024

<abstract> <p>In recent years, machine learning (ML) and deep (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications. Further, given current progress fields of ML DL, there exists promising potential for both provide support realm healthcare. This study offered an exhaustive survey on DL system, concentrating vital state art features, integration benefits, applications, prospects future guidelines. To conduct research, we found most prominent journal conference databases using distinct keywords discover scholarly consequences. First, furnished along with cutting-edge ML-DL-based analysis smart a compendious manner. Next, integrated advancement services including ML-healthcare, DL-healthcare, ML-DL-healthcare. We then DL-based applications industry. Eventually, emphasized research disputes recommendations further studies based our observations.</p> </abstract>

Язык: Английский

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Internet of medical things and blockchain-enabled patient-centric agent through SDN for remote patient monitoring in 5G network

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Март 4, 2024

Abstract During the COVID-19 pandemic, there has been a significant increase in use of internet resources for accessing medical care, resulting development and advancement Internet Medical Things (IoMT). This technology utilizes range equipment testing software to broadcast patient results over internet, hence enabling provision remote healthcare services. Nevertheless, preservation privacy security realm online communication continues provide pressing obstacle. Blockchain shown potential mitigate apprehensions across several sectors, such as industry. Recent advancements research have included intelligent agents monitoring systems by integrating blockchain technology. However, conventional network configuration agent introduces level complexity. In order address this disparity, we present proposed architectural framework that combines defined networking (SDN) with is specially tailored purpose facilitating within context 5G environment. The design contains patient-centric (PCA) inside SDN control plane managing user data on behalf patients. appropriate handling ensured PCA via essential instructions forwarding devices. suggested model assessed using hyperledger fabric docker-engine, its performance compared current models fifth generation (5G) networks. our surpasses methodologies, extensive study including factors throughput, dependability, overhead, packet error rate.

Язык: Английский

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Industry 5.0 and sustainability: An overview of emerging trends and challenges for a green future

Innovation and Green Development, Год журнала: 2024, Номер 3(4), С. 100173 - 100173

Опубликована: Авг. 19, 2024

Язык: Английский

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Federated Learning for Cloud and Edge Security: A Systematic Review of Challenges and AI Opportunities

Electronics, Год журнала: 2025, Номер 14(5), С. 1019 - 1019

Опубликована: Март 3, 2025

The ongoing evolution of cloud computing requires sustained attention to security, privacy, and compliance issues. purpose this paper is systematically review the current literature regarding application federated learning (FL) artificial intelligence (AI) improve security while preserving delivering real-time threat detection, meeting regulatory requirements. research follows a systematic (SLR) approach, which examined 30 studies published between 2020 2024 followed PRISMA checklist. analysis shows that FL provides significant privacy risk reduction by 25%, especially in healthcare similar domains, it improves detection 40% critical infrastructure areas. A total 80% reviewed implementations showed improved but challenges like communication overhead resource limitations persist, with 50% reporting latency To overcome these obstacles, study also explores some emerging solutions, include model compression, hybrid architectures, cryptographic enhancements. Additionally, demonstrates unexploited capability for decision-making dynamic edge environments highlights its potential across autonomous systems, Industrial Internet Things (IIoT), cybersecurity frameworks. paper’s proposed insights present deployment strategy models enables scalable, secure, privacy-preserving operations will enable robust solutions AI era.

Язык: Английский

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In-Network Caching for ICN-Based IoT (ICN-IoT): A Comprehensive Survey

IEEE Internet of Things Journal, Год журнала: 2023, Номер 10(16), С. 14595 - 14620

Опубликована: Май 10, 2023

The Internet of Things (IoT) has already emerged as one the most popular directions in today's information and communication technology (ICT) domain. With its advancement over different application areas, such smart home, healthcare, industry 4.0, etc., a huge amount data been generated by billions IoT devices, which aggravates shortcomings network layer (IP)-based networks, limited expressiveness IP addressing, inefficient support for mobility, in-network caching. Building on top information-centric networking (ICN) is believed to be promising solution tackle above challenge, especially caching ICN can significantly benefit terms reducing saving devices' energy. However, more challenging than traditional content, e.g., video, because are usually valid within certain period time, devices typically constrained with battery. Hence, this survey, we first review current implementation proposals ICN-based (ICN-IoT). Next, present conventional decision policies replacement could adopted mitigate aforementioned challenges, traffic, energy, retrieval latency. Further, since leveraging machine learning (ML) techniques have potential further improve efficiency dealing uncertainties, predicting unknown information, adaptively interacting environment, also demonstrate recently proposed ML-based schemes ICN-IoT. In addition, outline open research issues point out future opportunities

Язык: Английский

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Navigating Industry 5.0: A Survey of Key Enabling Technologies, Trends, Challenges, and Opportunities

IEEE Communications Surveys & Tutorials, Год журнала: 2023, Номер 26(2), С. 1080 - 1126

Опубликована: Ноя. 2, 2023

This century has been a major avenue for revolutionary changes in technology and industry. Industries have transitioned towards intelligent automation, relying less on human intervention, resulting the fourth industrial revolution, Industry 4.0. That is why IoT researcher's arena quite some time. With 4.0 still motion, world verge of 5th relatively new concept with many unclear opinions regarding its potential benefits, challenges, opportunities, trends, impact society. There dire need broader more critical perspective. research paints bigger picture "What happening?" to expect?" during transition phase 5.0. In this comprehensive review, we addressed state-of-the-art practices transitional We highlighted most promising key enabling technologies, topics, rising unfolding opportunities that can help prepare society paradigm shift. The paper then surveys work toward outstanding enablers, evolution To spur further avenues researchers industrialists, offers conclusive insights at end. addition, article precise set questions answered consequent sections subsections reader's clarity.

Язык: Английский

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Impacts of blockchain in software‐defined Internet of Things ecosystem with Network Function Virtualization for smart applications: Present perspectives and future directions

International Journal of Communication Systems, Год журнала: 2023, Номер unknown

Опубликована: Фев. 6, 2023

Summary As an emerging technology, blockchain (BC) has been playing a promising role in today's software‐defined networking (SDN)‐enabled Internet of Things (IoT) applications. Because the salient feature network function virtualization (NFV) techniques, SDN can ensure IoT system runs efficiently and smoothly cloud‐driven ecosystem. When cloud‐enabled systems encounter immense security operational challenges caused mainly by third‐party dependency, large‐scale data communication, maintenance, BC offers effective robust transfer solutions without incorporating intermediaries over distributed network. With increased SDN‐BC convergence domain, underlying perspectives deserve proper attention methodically structurally. From motivation addressing such issues, this study provides necessary insights to combine those for successful plug‐and‐play. Therefore, includes purposefully investigating current state‐of‐the‐art extract research trends, future directions, domain. This comprehensive survey IoT, SDN, NFV, BC‐enabled technologies. More importantly, authors intelligently integrated four different technologies—IoT, BC, NFV based on characteristics, scopes, challenges, taxonomies, tables numerous areas. Initially, introduce SDN‐IoT ecosystem brief address features We took close look at SDN's overall taxonomy security, environment, challenges. also briefly describe integration with ecosystems. Moreover, we review prospect technology from perspectives, its extent, practical implementation, possible regarding smart Finally, highlights several directions these

Язык: Английский

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Federated Deep Learning for Monkeypox Disease Detection on GAN-Augmented Dataset

IEEE Access, Год журнала: 2024, Номер 12, С. 32819 - 32829

Опубликована: Янв. 1, 2024

After the coronavirus disease 2019 (COVID-19) outbreak, viral infection known as monkeypox gained significant attention, and World Health Organization (WHO) classified it a global public health emergency. Given similarities between other pox viruses, conventional classification methods encounter difficulties in accurately identifying disease. Furthermore, sharing sensitive medical data gives rise to concerns about security privacy. Integrating deep neural networks with federated learning (FL) presents promising avenue for addressing challenges of categorization. In light this, we propose an FL-based framework using models classify viruses securely. The proposed has three major components: (a) cycle-consistent generative adversarial network augment samples training; (b) learning-based such MobileNetV2, Vision Transformer (ViT), ResNet50 classification; (c) flower-federated environment security. experiments are performed publicly available datasets. experiments, ViT-B32 model yields impressive accuracy rate 97.90%, emphasizing robustness its potential secure accurate categorization

Язык: Английский

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A Survey on Heterogeneity Taxonomy, Security and Privacy Preservation in the Integration of IoT, Wireless Sensor Networks and Federated Learning

Sensors, Год журнала: 2024, Номер 24(3), С. 968 - 968

Опубликована: Фев. 1, 2024

Federated learning (FL) is a machine (ML) technique that enables collaborative model training without sharing raw data, making it ideal for Internet of Things (IoT) applications where data are distributed across devices and privacy concern. Wireless Sensor Networks (WSNs) play crucial role in IoT systems by collecting from the physical environment. This paper presents comprehensive survey integration FL, IoT, WSNs. It covers FL basics, strategies, types discusses WSNs various domains. The addresses challenges related to heterogeneity summarizes state-of-the-art research this area. also explores security considerations performance evaluation methodologies. outlines latest achievements potential directions emphasizes significance surveyed topics within context current technological advancements.

Язык: Английский

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A review of secure federated learning: Privacy leakage threats, protection technologies, challenges and future directions

Neurocomputing, Год журнала: 2023, Номер 561, С. 126897 - 126897

Опубликована: Окт. 4, 2023

Язык: Английский

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