Industry 4.0 and Health: Internet of Things, Big Data, and Cloud Computing for Healthcare 4.0

Aceto, Giuseppe; Persico, Valerio; Pescapè, Antonio

doi:10.1016/j.jii.2020.100129

Cited by 577 publications

(363 citation statements)

References 93 publications

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“…This is especially true in the area of health care, where the IoT, cloud computing and fog, as well as Big Data technologies are changing the e-health and its entire ecosystem, leading it to health 4.0. Hospitals need high-capacity information technology infrastructure for patients' electronic health records and data related to personal, patients and physicians [68]. Storing this data helps to prevent the spread of infectious diseases.…”

Section: Cloud Computing Fog and Internet Of Things (Iot)mentioning

confidence: 99%

COVID-19 and information - communication technology: Common components in an interactive framework for predicting, preventing, controlling and monitoring the new COVID-19 disease

Yazdani

Sharifian

Ravangard

et al. 2020

Preprint

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BackgroundSince there is no specific treatment for coronavirus, there is an urgent need for global monitoring of people with Covid-19. The use of e-health services should be compatible with the diagnosis and control of the outbreak of zoonotic infectious diseases. The aim of this study is to provide a conceptual model based on health information technology services for Covid-19 disease management.MethodsThe present study is an applied descriptive study that was performed on a cross-sectional basis in a COVID-19 Center Hospital in Fars province of IRAN country in April 2020. The main tool of this research is a questionnaire that has been compiled by reviewing related articles in databases and surveying with experts in order to determine the necessary services in the management and control model of the prevalence of Covid19 disease. Then, in order to determine the necessary services in the conceptual model, this questionnaire was given to various specialists in the COVID-19 Center Hospital. Finally, based on the results of the questionnaire, a comprehensive conceptual model for the management and control of COVID 19 diseases is presented.ResultsThe proposed model consisted of three layers of cloud computing, fog and data acquisition. All services were approved by the surveyed participants. Among the services, Tele- monitoring for home quarantine, Electronic self-assessment, Telepsychology of patients in home and hospital quarantine, Tele prescription, Tele- information Tele- training have the highest agreement rate. proposed model is an integrated model. The innovation that can be mentioned in this research is the use of priority queue service as a service of the fog layer.ConclusionInformation communication technology tools have an important role in all aspects of contagious diseases management.

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Section: Cloud Computing Fog and Internet Of Things (Iot)mentioning

confidence: 99%

COVID-19 and information - communication technology: Common components in an interactive framework for predicting, preventing, controlling and monitoring the new COVID-19 disease

Yazdani

Sharifian

Ravangard

et al. 2020

Preprint

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“…When the literature is examined, it is possible to see some IoT based, and cloud support systems developed for monitoring [84] , [85] , [86] , and diagnosis [87] , [88] , [89] , [90] cases in the context of medical healthcare perspectives. It is clear that the current era rises over IoT systems as the year of 2020 shows increase in especially IoHT side [91] , [92] . However, there is still need for alternative research/development of systems, with focus on especially less complicated solution approach with data security aspects.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network

Deperlioğlu

Köse

Gupta

et al. 2020

Computer Communications

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Objective of this study is to introduce a secure IoHT system, which acts as a clinical decision support system with the diagnosis of cardiovascular diseases. In this sense, it was emphasized that the accuracy rate of diagnosis (classification) can be improved via deep learning algorithms, by needing no hybrid-complex models, and a secure data processing can be achieved with a multi-authentication and Tangle based approach. In detail, heart sounds were classified with Autoencoder Neural Networks (AEN) and the IoHT system was built for supporting doctors in real-time. For developing the diagnosis infrastructure by the AEN, PASCAL B-Training and Physiobank-PhysioNet A-Training heart sound datasets were used accordingly. For the PASCAL dataset, the AEN provided a diagnosis-classification performance with the accuracy of 100%, sensitivity of 100%, and the specificity of 100% whereas the rates were respectively 99.8%, 99.65%, and 99.13% for the PhysioNet dataset. It was seen that the findings by the developed AEN based solution were better than the alternative solutions from the literature. Additionally, usability of the whole IoHT system was found positive by the doctors, and according to the 479 real-case applications, the system was able to achieve accuracy rates of 96.03% for normal heart sounds, 91.91% for extrasystole, and 90.11% for murmur. In terms of security approach, the system was also robust against several attacking methods including synthetic data impute as well as trying to penetrating to the system via central system or mobile devices.

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“…A S big data and cloud computing develop rapidly in the recent years, an increasing number of individuals and enterprises upload data files to cloud servers due to insufficient memory capacity of application devices [1]. However, cloud servers are not completely trusted for the reason that they are not under the full supervision of enterprises and users.…”

Section: Introductionmentioning

confidence: 99%

Multi-Keyword Certificateless Searchable Public Key Authenticated Encryption Scheme Based on Blockchain

et al. 2020

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As a quite attractive secure search mechanism in cloud environments, searchable encryption allows encrypted files to be searched by keyword and does not reveal any information about original data files. However, most existing searchable encryption schemes only support single keyword ciphertext retrieval, and they cannot resist against inside keyword guessing attacks. Besides, the previous schemes rarely focus on integrity verification and fair transactions without any third party. Focusing on these problems, we propose a multi-keyword certificateless searchable public key authenticated encryption scheme based on blockchain. We use certificateless cryptosystem to encrypt keywords, which avoids the problems of certificate management in traditional cryptosystem and key escrow in identity-based cryptosystem. Our scheme also supports multi-keyword search, which locates encrypted files precisely and returns the desired files. Moreover, we upload the real encrypted files to the cloud server, while the encrypted indexes are put in blockchain, which ensures the anti-tampering, integrity and traceability of the encrypted indexes. The anti-tampering of blockchain also ensures that users can receive accurate search results without any third party verification. Furthermore, we utilize smart contract to track monetary rewards, which enables fair transactions between data owners and users without any trusted third party. We prove that the proposed scheme is secure against inside keyword guessing attacks in the random oracle model. Finally, our performance evaluation shows that the proposed scheme has higher computational performance than other related schemes.

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Industry 4.0 and Health: Internet of Things, Big Data, and Cloud Computing for Healthcare 4.0

Cited by 577 publications

References 93 publications

COVID-19 and information - communication technology: Common components in an interactive framework for predicting, preventing, controlling and monitoring the new COVID-19 disease

COVID-19 and information - communication technology: Common components in an interactive framework for predicting, preventing, controlling and monitoring the new COVID-19 disease

Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network

Multi-Keyword Certificateless Searchable Public Key Authenticated Encryption Scheme Based on Blockchain

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