Revolution of Smart Healthcare Materials in Big Data Analytics

Renugadevi, N.; Saravanan, S.; Sudha, C.M. Naga

doi:10.1016/j.matpr.2021.04.256

Cited by 11 publications

(2 citation statements)

References 34 publications

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“…Wearable IoT generates extensive health data, requiring real-time security measures to prevent breaches. An unsynchronized sensor data analytics model is proposed (Jonny and Toshio, 2021;Puthal, 2019) using Storm and Spark to monitor health data (Renugadevi, Saravanan, and Sudha, 2021). IoT devices lack biological data but use big data analytics and ML to predict activities (Syed et al, 2019), benefiting elder care, rehabilitation, and chronic disease management.…”

Section: Internet Of Thingsmentioning

confidence: 99%

A Review of Big Data Trends and Challenges in Healthcare

Baloch,

Bazai,

Marjan

et al. 2023

IJTech

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The healthcare sector produces an enormous amount of complicated data from several sources, such as health monitoring systems, medical devices, and electronic health records. Big data analytics may improve healthcare by enabling more effective decision-making, improving patient outcomes, and reducing costs. To improve the operational efficiency of healthcare organizations, scientific studies must search for the standardization and integration of data analysis equipment and methods. This systematic literature review aims to provide current insights on the topic by analyzing a total of 60 relevant articles published between 2017 and 2023. The review explores the challenges and opportunities in using big data in healthcare, including data security, privacy, data quality, interoperability, and ethical considerations. The article also explores big data analytics' potential uses in healthcare, such as personalized treatment, disease prediction and prevention, and population health management. It provides significant insights for healthcare providers, researchers, and practitioners to make evidence-based decisions, as well as underlines the need for more research in this area to fully realize the promise of big data in healthcare.

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Section: Internet Of Thingsmentioning

confidence: 99%

A Review of Big Data Trends and Challenges in Healthcare

Baloch,

Bazai,

Marjan

et al. 2023

IJTech

View full text Add to dashboard Cite

show abstract

“…Sharma et al [65] implemented a remote access IoT-based model with a bio wearable sensor system for early detection of COVID-19 utilizing an ontology method and biomedi-cal signals, including ECG, PPG, temperature, and accelerometer. Renugadevi et al [66] investigated the importance of big data in smart health applications, which are critical in ensuring human safety. Seda Savaşcı Şen [67] presented an Internet of Things-based surveillance system for coronavirus pandemics in particular.…”

Section: Iot or Iomt Framework For Covid-19mentioning

confidence: 99%

A Systematic Review and IoMT Based Big Data Framework for COVID-19 Prevention and Detection

et al. 2022

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The Internet of Medical Things (IoMT) is transforming modern healthcare systems by merging technological, economical, and social opportunities and has recently gained traction in the healthcare domain. The severely contagious respiratory syndrome coronavirus called COVID-19 has emerged as a severe threat to public health. COVID-19 is a highly infectious virus that is spread by person-to-person contact. Therefore, minimizing physical interactions between patients and medical healthcare workers is necessary. The significance of technology and its associated potential were fully explored and proven during the outbreak of COVID-19 in all domains of human life. Healthcare systems employ all modes of technology to facilitate the increasing number of COVID-19 patients. The need for remote healthcare was reemphasized, and many remote healthcare solutions were adopted. Various IoMT-based systems were proposed and implemented to support traditional healthcare systems with reaching the maximum number of people remotely. The objective of this research is twofold. First, a systematic literature review (SLR) is conducted to critically evaluate 76 articles on IoMT systems for different medical applications, especially for COVID-19 and other health sectors. Secondly, we briefly review IoMT frameworks and the role of IoMT-based technologies in COVID-19 and propose a framework, named ‘cov-AID’, that remotely monitors and diagnoses the disease. The proposed framework encompasses the benefits of IoMT sensors and extensive data analysis and prediction. Moreover, cov-AID also helps to identify COVID-19 outbreak regions and alerts people not to visit those locations to prevent the spread of infection. The cov-AID is a promising framework for dynamic patient monitoring, patient tracking, quick disease diagnosis, remote treatment, and prevention from spreading the virus to others. We also discuss potential challenges faced in adopting and applying big data technologies to combat COVID-19.

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