Survei IoT Healthcare Device

Suryandari, Yulia

doi:10.37396/jsc.v3i2.55

Cited by 7 publications

(9 citation statements)

References 11 publications

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“…In [5], a Remote Patient Monitoring System (RPMS) aims to effectively manage hospital resources through patient monitoring at home. RPMS is an IoT-based solution for patient monitoring that supports the automatic collection and transmission of patient data to remote databases.…”

Section: Related Workmentioning

confidence: 99%

“…The Internet of Things offers many opportunities in the field of e-health. This technology can improve health services and lead to various innovations in this regard [5]. The Internet of Things acts as a catalyst for healthcare and plays an important role in healthcare services [6].…”

Section: Introductionmentioning

confidence: 99%

“…Besides, it allows remote storage of data on cloud-based platforms and enables the cooperation of any authorized person, including external specialists and the internal team [5]. It is also an appropriate platform for health applications based on mobile / tablet / PDA devices.…”

Section: Introductionmentioning

confidence: 99%

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Remote Patient Monitoring and classifying Using the Internet of Things Platform Combined with Cloud Computing

Iranpak

Shahbahrami

Shakeri

2021

Preprint

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Patients' health and providing an optimal and appropriate solution have recently been considered by many researchers. With the advent of technologies such as cloud computing and 5G network, information can be exchanged faster and more securely. Using cloud computing in this process can significantly improve the monitoring of certain patients. Therefore, providing a favorable method in the medical industry and computer science to monitor the status of patients using connected sensors is very important. Thus, due to its optimal efficiency, speed, and accuracy of data processing and classification, the use of cloud computing to process the data collected from remote patient sensors and the Internet of Things (IoT) platform has been suggested. In this paper, a prioritization system is used to prioritize sensitive information in IoT, and in cloud computing, LSTM deep neural network is used to classify and monitor patients' condition remotely, which can be considered as an important innovative aspect of this paper. Sensor data in the IoT platform is sent to the cloud with the help of the 5th generation Internet. The core of cloud computing uses the LSTM deep neural network algorithm. Through simulating the proposed method and comparing the obtained results with other methods, it was observed that the accuracy of the proposed method has been improved significantly compared to other methods.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Remote Patient Monitoring and classifying Using the Internet of Things Platform Combined with Cloud Computing

Iranpak

Shahbahrami

Shakeri

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…IoT offers many opportunities in the field of e-health. This technology can improve health services and lead to various innovations in this regard [5]. IoT acts as a catalyst for healthcare and plays a key role in healthcare services [6].…”

mentioning

confidence: 99%

“…C. Comprehensive analysis of mobile health plans and sharing medical data. Furthermore, it allows remote storage of data on cloud-based platforms and enables the cooperation of any authorized person, including external specialists and the internal team [5]. It is also an appropriate platform for health applications based on mobile/tablet/PDA devices.…”

mentioning

confidence: 99%

Remote patient monitoring and classifying using the internet of things platform combined with cloud computing

2021

View full text Add to dashboard Cite

Many researchers have recently considered patients’ health and provided an optimal and appropriate solution. With the advent of technologies such as cloud computing, Internet of Things and 5G, information can be exchanged faster and more securely. The Internet of things (IoT) offers many opportunities in the field of e-health. This technology can improve health services and lead to various innovations in this regard. Using cloud computing and IoT in this process can significantly improve the monitoring of patients. Therefore, it is important to provide a useful method in the medical industry and computer science to monitor the status of patients using connected sensors. Thus, due to its optimal efficiency, speed, and accuracy of data processing and classification, the use of cloud computing to process the data collected from remote patient sensors and IoT platform has been suggested. In this paper, a prioritization system is used to prioritize sensitive information in IoT, and in cloud computing, LSTM deep neural network is applied to classify and monitor patients’ condition remotely, which can be considered as an important innovative aspect of this paper. Sensor data in the IoT platform is sent to the cloud with the help of the 5th generation Internet. The core of cloud computing uses the LSTM (long short-term memory) deep neural network algorithm. By simulating the proposed method and comparing the obtained results with other methods, it is observed that the accuracy of the proposed method is 97.13%, which has been improved by 10.41% in average over the other methods.

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