Human Arthritis Analysis in Fog Computing Environment Using Bayesian Network Classifier and Thread Protocol

Tanwar, Sudeep; Vora, Jayneel; Kaneriya, Shriya; Tyagi, Sudhanshu; Kumar, Neeraj; Sharma, Vishal; You, Ilsun

doi:10.1109/mce.2019.2941456

Cited by 67 publications

(16 citation statements)

References 9 publications

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“…It is a three-party protocol, which includes the healthcare provider, the user and the verifier. Here, it is assumed that the healthcare provider makes no deliberate blunders in issuing the certificate; cryptographic systems handle the rest for authentication and verification [120].…”

Section: Security Of Datamentioning

confidence: 99%

RETRACTED ARTICLE: Blockchain for COVID-19: a comprehensive review

Shah

Tanwar

et al. 2021

Pers Ubiquit Comput

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The rampant and sudden outbreak of the SARS-CoV-2 coronavirus also called COVID-19 and its uncontrollable spread have led to a global crisis. COVID-19 is a highly contagious disease and the only way to fight with it is to follow social distancing and Non-Pharmaceutical Interventions (NPIs). Moreover, this virus is increasing exponentially day-by-day and a huge amount of data from this disease is also generated at the fast pace. So, there is a need to store, manage, and analyze this huge amount of data efficiently to get meaningful insights from it, which further helps medical professionals to tackle this global pandemic situation. Moreover, this data is to be passed through an open channel, i.e., the Internet, which opens the doors for the intruders to perform some malicious activities. Blockchain (BC) emerges as a technology that can manage the data in an efficient, transparent manner and also preserve the privacy of all the stakeholders. It can also aid in transaction authorization and verification in the supply chain or payments. Motivated by these facts, in this paper, we present a comprehensive review on the adoption of BC to tackle COVID-19 situations. We also present a case study on BC-based digital vaccine passports and analyzed its complexity. Finally, we analyzed the research challenges and future directions in this emerging area.

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Section: Security Of Datamentioning

confidence: 99%

RETRACTED ARTICLE: Blockchain for COVID-19: a comprehensive review

Shah

Tanwar

et al. 2021

Pers Ubiquit Comput

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“…The images that have a ratio of first least distance to the second least distance is less than 0.8 are taken into consideration. Then the image is given to the classifier that classifies the emotion [112].…”

Section: ) Scale Invariant Feature Transform (Sift)mentioning

confidence: 99%

Facial Sentiment Analysis Using AI Techniques: State-of-the-Art, Taxonomies, and Challenges

et al. 2020

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With the advancements in machine and deep learning algorithms, the envision of various critical real-life applications in computer vision becomes possible. One of the applications is facial sentiment analysis. Deep learning has made facial expression recognition the most trending research fields in computer vision area. Recently, deep learning-based FER models have suffered from various technological issues like under-fitting or over-fitting. It is due to either insufficient training and expression data. Motivated from the above facts, this paper presents a systematic and comprehensive survey on current state-of-art Artificial Intelligence techniques (datasets and algorithms) that provide a solution to the aforementioned issues. It also presents a taxonomy of existing facial sentiment analysis strategies in brief. Then, this paper reviews the existing novel machine and deep learning networks proposed by researchers that are specifically designed for facial expression recognition based on static images and present their merits and demerits and summarized their approach. Finally, this paper also presents the open issues and research challenges for the design of a robust facial expression recognition system. INDEX TERMS Facial sentiment analysis, machine learning, deep learning, convolutional neural network, deep belief network, artificial intelligence.

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“…In [183], Vora et al introduced fog computing to reduce the delay for ambient assisted living. In [184], Tanwar et al also improved WBAN performance using fog computing for monitoring and treating chronic arthritis disease. The existing literature [148], [185] promotes that fog computing has strong potential for assisting doctors in making smart, timely decisions during critical situations (such as stroke or respiratory failure) and providing faster responses 600 securely than standalone cloud-based applications.…”

Section: Fog Computing Integration With Wbanmentioning

confidence: 99%

Medical Sensors and Their Integration in Wireless Body Area Networks for Pervasive Healthcare Delivery: A Review

et al. 2022

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The introduction of sensor technology in our daily lives has brought comfort, convenience, and improved health over the past few decades. Technological advances further expanded the use of medical sensors by reducing their size and costs. Medical sensors improve the intelligence and capabilities of healthcare services including, remote health monitoring, surgical procedures, therapy, and rehabilitation. We present a comprehensive review of medical sensors in the last 50 years focusing on their deployment in healthcare applications. The review also discusses the role of Internet of Things (IoT) technology in enhancing the capabilities of sensor technologies for the healthcare domain. Moreover, we also investigate the benefits and challenges of various integrated architectures which have been proposed recently to seamlessly integrate heterogeneous medical sensors with emerging technologies and paradigms that include edge, Mobile Cloud Computing (MCC), fog, and cloud computing technologies. Finally, we identify future challenges that must be addressed to achieve the maximum potential and benefits of medical sensor technologies and ultimately provide robust, scalable, reliable, and cost-effective healthcare delivery.

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Human Arthritis Analysis in Fog Computing Environment Using Bayesian Network Classifier and Thread Protocol

Cited by 67 publications

References 9 publications

RETRACTED ARTICLE: Blockchain for COVID-19: a comprehensive review

RETRACTED ARTICLE: Blockchain for COVID-19: a comprehensive review

Facial Sentiment Analysis Using AI Techniques: State-of-the-Art, Taxonomies, and Challenges

Medical Sensors and Their Integration in Wireless Body Area Networks for Pervasive Healthcare Delivery: A Review

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