An IOT based human healthcare system using Arduino uno board

Jayapradha, S.; Vincent, Pascal

doi:10.1109/icicict1.2017.8342681

Cited by 25 publications

(9 citation statements)

References 3 publications

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“…Similarly, we also used Arduino and ultrasonic sensors in our proposed SSDWG model to detect the presence of the persons. Another study [10] proposed a healthcare monitoring system in which they used various IoT sensors to check patient's status and stores this basic information on cloud storage. We also used a similar approach to store the data of vulnerable individuals who pass from SSDWG in the database.…”

Section: Iot Healthcare Systemsmentioning

confidence: 99%

IoT and Deep Learning Based Approach for Rapid Screening and Face Mask Detection for Infection Spread Control of COVID-19

Hussain

Ayoub

et al. 2021

Applied Sciences

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The spread of COVID-19 has been taken on pandemic magnitudes and has already spread over 200 countries in a few months. In this time of emergency of COVID-19, especially when there is still a need to follow the precautions and developed vaccines are not available to all the developing countries in the first phase of vaccine distribution, the virus is spreading rapidly through direct and indirect contacts. The World Health Organization (WHO) provides the standard recommendations on preventing the spread of COVID-19 and the importance of face masks for protection from the virus. The excessive use of manual disinfection systems has also become a source of infection. That is why this research aims to design and develop a low-cost, rapid, scalable, and effective virus spread control and screening system to minimize the chances and risk of spread of COVID-19. We proposed an IoT-based Smart Screening and Disinfection Walkthrough Gate (SSDWG) for all public places entrance. The SSDWG is designed to do rapid screening, including temperature measuring using a contact-free sensor and storing the record of the suspected individual for further control and monitoring. Our proposed IoT-based screening system also implemented real-time deep learning models for face mask detection and classification. This module classified individuals who wear the face mask properly, improperly, and without a face mask using VGG-16, MobileNetV2, Inception v3, ResNet-50, and CNN using a transfer learning approach. We achieved the highest accuracy of 99.81% while using VGG-16 and the second highest accuracy of 99.6% using MobileNetV2 in the mask detection and classification module. We also implemented classification to classify the types of face masks worn by the individuals, either N-95 or surgical masks. We also compared the results of our proposed system with state-of-the-art methods, and we highly suggested that our system could be used to prevent the spread of local transmission and reduce the chances of human carriers of COVID-19.

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Section: Iot Healthcare Systemsmentioning

confidence: 99%

IoT and Deep Learning Based Approach for Rapid Screening and Face Mask Detection for Infection Spread Control of COVID-19

Hussain

Ayoub

et al. 2021

Applied Sciences

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“…The Arduino Microcontroller Architecture could also be used [42], [43] in place of the Raspberry Pi. In future iterations, a low-cost, low-profile microcontroller might be used to further reduce product footprint and optimize for various parameters.…”

Section: ) Arduinomentioning

confidence: 99%

Low Cost Design of Non-Contact Thermometry for Diagnosis and Monitoring

Yamanoor¹,

Yamanoor²,

Srivastava

2020

2020 IEEE Global Humanitarian Technology Conference (GHTC)

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The novel coronavirus pandemic has created the need for employee health monitoring and diagnosis in the workplace as one of the measures. The authors have attempted to design a non-contact thermometry device to create an open-source design that is simultaneously inexpensive. Such a device can be manufactured and deployed in a wide variety of economically challenged areas.The first iteration of a working design is summarized in this paper. Future work will include design customizations for cost-savings, accuracy, and precision improvements and considerations such as design for manufacturability and repairability.

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“…The industrial revolution 4.0, one of which gave birth to a technology called the Internet of Things. Internet of Things (IoT) is an integrated technology for exchanging and controlling data between electronic devices via the internet [1]. IoT in its application can identify, find, track, monitor objects automatically and in real-time so that it has a significant impact on society in the fields of economic management, production operations, social management and even personal life [2].…”

Section: Introductionmentioning

confidence: 99%

Development of Integrated IoT Trainer (LRioT) for Practical Work in Electrical Engineering Education Program Amid Pandemic

Nugraha¹,

Pratama²,

Wahyudin³

et al. 2021

Proceedings of the 6th UPI International Conference on TVET 2020 (TVET 2020)

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The COVID-19 pandemic there have been many changes in every segment of human life, including the education segment. The Indonesian state itself is taking action to close all educational institutions and shift learning to distance learning to limit the spread of the virus. However, distance learning cannot always be a learning solution, especially for practicum learning. Department of electrical engineering education, University of Pendidikan Indonesia, especially in the subject of practicum sensors and microprocessors, there is no learning media that can help students to do lab work remotely. On this basis, the researchers made an integrated IoT trainer design that can send and receive data to the IoT platform cloud service and can be developed into an IoT remote laboratory to meet the needs of remote practicum learning. The method used in this study is an experiment which includes design and testing. The design carried out is an integrated IoT trainer communication system, a gateway device, and an integrated IoT trainer. The trials were carried out by ensuring the data that was sended by the trainer was the same as the data accessed by the end-user on the IoT cloud platform. The trial results show that the end-user can access the same data as the existing data on the trainer. So it can be said that the trainer functions according to the plan. In the future development this trainer can be used as IoT remote laboratory that can support online practical work in amid pandemic.

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An IOT based human healthcare system using Arduino uno board

Cited by 25 publications

References 3 publications

IoT and Deep Learning Based Approach for Rapid Screening and Face Mask Detection for Infection Spread Control of COVID-19

IoT and Deep Learning Based Approach for Rapid Screening and Face Mask Detection for Infection Spread Control of COVID-19

Low Cost Design of Non-Contact Thermometry for Diagnosis and Monitoring

Development of Integrated IoT Trainer (LRioT) for Practical Work in Electrical Engineering Education Program Amid Pandemic

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