Health Behaviors and Outcomes of Mobile Health Apps and Patient Engagement in the USA

Journal of Computer and Communications, Год журнала: 2024, Номер 12(10), С. 78 - 93

Опубликована: Янв. 1, 2024

Язык: Английский

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Advancing Healthcare: A Comprehensive Review and Future Outlook of IoT Innovations

Engineering Technology & Applied Science Research, Год журнала: 2025, Номер 15(1), С. 19700 - 19711

Опубликована: Фев. 2, 2025

Rapid innovation leading to better patient outcomes have been driven by recent breakthroughs in the Internet of Things (IoT), which drastically changed healthcare sector. In order highlight importance IoT applications, this article presents a user-friendly and integrated approach for bibliometric analysis. Traditional methods often rely solely on Web Science (WoS) or Scopus, limiting scope To address issue, proposed uses R program Bibliometrix combine data from seven databases, namely WoS, IEEE, ACM Digital Library, PubMed, Direct, Google Scholar (GS). After having developed an inclusion/exclusion criterion, 2,990 journal papers published between 2011 2022 were subjected thorough literature review This study demonstrates that industry is highly interested IoT, as well rapid growth research into blockchain, Artificial Intelligence (AI), 5G telecoms, analytics. Authentication methods, fog computing, cloud-IoT integration, cognitive smart healthcare, other essential topics are further examined employing co-citation network addition illuminating potential avenues investigation, these results provide academics with comprehensive picture where standing at moment. The output conducted analysis shows there has dramatic uptick publishing since 2017, most articles appearing prestigious journals related computer science. By integrating multiple methodology represents significant advancement analysis, enabling more exploration IoT's impact facilitating deeper understanding emerging trends critical themes rapidly evolving field.

Язык: Английский

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A Review of the Authentication Techniques for Internet of Things Devices in Smart Cities: Opportunities, Challenges, and Future Directions

Sensors, Год журнала: 2025, Номер 25(6), С. 1649 - 1649

Опубликована: Март 7, 2025

Smart cities have witnessed a transformation in urban living through the Internet of Things (IoT), which has improved connectedness, efficiency, and sustainability. However, adoption IoT devices presents significant security vulnerabilities, particularly authentication. The specific limitations contexts, such as constrained computational resources, are frequently not adequately addressed by traditional authentication techniques. existing methods used for smart critically examined this review study. We evaluate advantages disadvantages each mechanism, emphasizing real-world applicability. Additionally, we examine cutting-edge developments that offer scalability, blockchain technology, biometric authentication, machine learning-based solutions. This study aims to identify gaps propose future research directions develop robust frameworks protect user privacy data integrity.

Язык: Английский

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IoT-Enabled RFID in Supply Chain Management: A Comprehensive Survey and Future Directions

Journal of Computer and Communications, Год журнала: 2024, Номер 12(11), С. 207 - 223

Опубликована: Янв. 1, 2024

Язык: Английский

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Integrating Blockchain Innovation: A Sustainable Adoption Model for Business

Journal of Computer and Communications, Год журнала: 2024, Номер 12(11), С. 141 - 161

Опубликована: Янв. 1, 2024

Язык: Английский

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Online Marketing: Social Media Influencer’s Impact on Shopping Tactics in the United States

American Journal of Industrial and Business Management, Год журнала: 2024, Номер 14(11), С. 1545 - 1561

Опубликована: Янв. 1, 2024

Язык: Английский

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Identifying suspicious internet threat exchanges using machine learning algorithms to ensure privacy and cybersecurity in the USA

Journal of Infrastructure Policy and Development, Год журнала: 2024, Номер 8(15), С. 8848 - 8848

Опубликована: Дек. 13, 2024

The usage of cybersecurity is growing steadily because it beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone connected through the internet. It’s much easier for a thief connect important data cyber-attacks. Everyone needs precious personal and sustainable infrastructure development in science. However, systems protecting our using existing difficult. There are different types threats. It be phishing, malware, ransomware, so on. To prevent these attacks, need advanced systems. Many software helps not able early detect suspicious internet threat exchanges. This research used machine learning models enhance detection. Reducing cyberattacks enhancing protection; this system makes possible browse anywhere securely. Kaggle dataset was collected build technology untrustworthy online exchanges early. obtain better results accuracy, few pre-processing approaches were applied. Feature engineering applied improve quality Ultimately, random forest, gradient boosting, XGBoost, Light GBM achieve goal. Random forest obtained 96% which best helpful get good outcome social system.

Язык: Английский

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Identification of Cardiovascular Disease via Diverse Machine Learning Methods

Journal of Computer and Communications, Год журнала: 2024, Номер 12(12), С. 134 - 150

Опубликована: Янв. 1, 2024

Язык: Английский

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Deep Learning Approaches for the Identification and Classification of Skin Cancer

Journal of Computer and Communications, Год журнала: 2024, Номер 12(12), С. 55 - 71

Опубликована: Янв. 1, 2024

Язык: Английский

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