IoT-Based Patient Health Monitoring: A Comprehensive Survey

Murthy, B. S.; Peddoju, Suresh K.

doi:10.1007/978-981-15-8354-4_35

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…Development should continually be attempting to unite people, instead of separation them further considering pay or preparing levels. Contemplating these networks, related to different issues tended to in this article, will advance the general outcome of an answer past the space of educated clients [15].…”

Section: Being Socially Inclusivementioning

confidence: 96%

Recent Trends and Challenges in Smart Cities

Pooja

Sundar²,

Harshini³

et al. 2022

EAI Endorsed Trans Smart Cities

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Smart systems are wanting for smart communities to adapt to restricted spaces and assets across the world. Thus, smart urban communities arose mostly because of exceptionally inventive ICT ventures and markets, and furthermore, they have begun to utilize novel arrangements exploiting the Internet of Things (IoT), huge information and distributed computing innovations to lay out a significant association between every part and layer of a city. Smarter solutions need to be executed to make digital services for economic and social advancement seamlessly reach the occupants in an easy and secure way and encourage them to continue using the amenities. A holistic development rather than just technological advancement is essential for the betterment of Smart lifestyle of the present and future population. This paper attempts to analyze advancements, and the challenges involved in implementing them in various sectors should be executed to make computerized administrations for monetary and social headway flawlessly arrive at the tenants in a simple and secure manner and urge them to keep utilizing the conveniences.

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Section: Being Socially Inclusivementioning

confidence: 96%

Recent Trends and Challenges in Smart Cities

Pooja

Sundar²,

Harshini³

et al. 2022

EAI Endorsed Trans Smart Cities

View full text Add to dashboard Cite

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Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues

et al. 2022

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Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare field. Traditionally, the healthcare system works based on centralized agents sharing their raw data. Therefore, huge vulnerabilities and challenges are still existing in this system. However, integrating with AI, the system would be multiple agent collaborators who are capable of communicating with their desired host efficiently. Again, FL is another interesting feature, which works decentralized manner; it maintains the communication based on a model in the preferred system without transferring the raw data. The combination of FL, AI, and XAI techniques can be capable of minimizing several limitations and challenges in the healthcare system. This paper presents a complete analysis of FL using AI for smart healthcare applications. Initially, we discuss contemporary concepts of emerging technologies such as FL, AI, XAI, and the healthcare system. We integrate and classify the FL-AI with healthcare technologies in different domains. Further, we address the existing problems, including security, privacy, stability, and reliability in the healthcare field. In addition, we guide the readers to solving strategies of healthcare using FL and AI. Finally, we address extensive research areas as well as future potential prospects regarding FL-based AI research in the healthcare management system.

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