Investigation into Smart Healthcare Monitoring System in an IoT Environment
DOI:
https://doi.org/10.56532/mjsat.v2i2.53Keywords:
Health Monitoring, IoT, Sensor, Raspberry Pi Model BAbstract
Continuous monitoring of progress of a clinical trial is known as health monitoring. It is to assure compliance with policy, best clinical practice, regulatory norms, and standard operating procedures. Monitoring is vital in several health settings. This creates an environment where physician and patient can engage. The doctor may also be up to date with the current patient’s health status. Sensor initialization is this system's first stage. This project includes of many sensor kinds such as blood pressure sensor, temperature sensor, pulse rate sensor. The sensor is then connected to the Raspberry Pi 3 Model B+ which transmits a signal over the internet allowing the doctor to interact with patient data. All sensor data is stored in a cloud database. If the sensor value exceeds the threshold sensor value and the alert email is sent to the doctor and caretaker, then a precautionary notification is sent to the patient. Doctor and patient can interact through a user application where the doctor can even write the patient's prescription. This approach can monitor several patients in severe conditions and save time. This project provides low-cost monitoring from one's home. This is a secure and reliable project that helps patients worldwide.
References
Md. M. Islam, A. Rahaman, and Md. R. Islam, ‘Development of Smart Healthcare Monitoring System in IoT Environment’, SN Comput. Sci., vol. 1, no. 3, p. 185, May 2020, doi: 10.1007/s42979-020-00195-y.
M. Mathivanan, M. Balamurugan, H. L., Nandini, and M. Reddy, ‘IoT based continuous monitoring of cardiac patients using Raspberry Pi’, Karnataka, India, 2018, p. 020025. doi: 10.1063/1.5078984.
R. Vithiya, S. Karthika, and G. Sharmila, ‘Detection, Monitoring and Tracking Of Survivors under Critical Condition Using Raspberry-Pi’, in 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN), Pondicherry, India, Mar. 2019, pp. 1–5. doi: 10.1109/ICSCAN.2019.8878711
Mohd. Hamim, S. Paul, S. I. Hoque, Md. N. Rahman, and I.-A. Baqee, ‘IoT Based Remote Health Monitoring System for Patients and Elderly People’, in 2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST), Dhaka, Bangladesh, Jan. 2019, pp. 533–538. doi: 10.1109/ICREST.2019.8644514.
R. S. Nair et al., ‘Recent Trends and Opportunities of Remote Multi- Parameter PMS using IoT’, in 2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT), Surabaya, Indonesia, Apr. 2021, pp. 325–329. doi: 10.1109/EIConCIT50028.2021.9431926.
A. A. Zainuddin et al., ‘Patient Monitoring System using Computer Vision for Emotional Recognition and Vital Signs Detection’, in 2020 IEEE Student Conference on Research and Development (SCOReD), Batu Pahat, Malaysia, Sep. 2020, pp. 22–27. doi: 10.1109/SCOReD50371 .2020.9250950.
K. Jaiswal, S. Sobhanayak, B. K. Mohanta, and D. Jena, ‘IoT-cloud based framework for patient’s data collection in smart healthcare system using raspberry-pi’, in 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA), Ras Al Khaimah, Nov. 2017, pp. 1–4. doi: 10.1109/ICECTA.2017.8251967.
Nair, R. S., Lawrence, J. M., Vyakaranam, A., Svpk, S. D., Shameem, S. S. S., Sulo, R., ... & Mansor, A. F. (2021, April). Recent Trends and Opportunities of Remote Multi-Parameter PMS using IoT. In 2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT) (pp. 325-329). IEEE.
Zainuddin, A. A., Superamaniam, S., Andrew, A. C., Muraleedharan, R., Rakshys, J., Miriam, J., ... & Taufik, M. S. M. (2020, September). Patient monitoring system using computer vision for emotional recognition and vital signs detection. In 2020 IEEE Student Conference on Research and Development (SCOReD) (pp. 22-27). IEEE.
S. Yattinahalli and R. M. Savithramma, ‘A Personal Healthcare IoT System model using Raspberry Pi 3’, in 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), Coimbatore, Apr. 2018, pp. 569–573. doi: 10.1109/ICICCT.2018.8473184.
R. Kumar and M. P. Rajasekaran, ‘An IoT based patient monitoring system using raspberry Pi’, in 2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE’16), Kovilpatti, India, Jan. 2016, pp. 1–4. doi: 10.1109/ICCTIDE.2016.7725378.
K. S. Naik and E. Sudarshan, ‘Smart Healthcare Monitoring System Using Raspberry Pi on IOT Platform’, vol. 14, no. 4, p. 5, 2019.
M. G. M. Prabha, ‘AUTOMATIC HEALTH MONITORING SYSTEM USING RASPBERRY PI’, p. 8.
C. K. R. Kirankumar and M. Prabhakaran, ‘Design and implementation of low cost web based human health monitoring system using Raspberry Pi 2’, in 2017 IEEE International Conference on Electrical, Instrumentation and Communication Engineering (ICEICE), Karur, Apr. 2017, pp. 1–5. doi: 10.1109/ICEICE.2017.8191881.
M. A. Muqeet and M. U. Quadri, ‘IoT based Patient Monitoring System Using Raspberry Pi’, vol. 7, no. 2, p. 6, 2019
M. A. Saip and A. S. Mohamed, ‘Smart Health Monitoring and Controlling using Raspberry Pi3’, Int. Innov. Res. J. Eng. Technol., vol. 4, no. 1, pp. 24–28, Sep. 2018, doi: 10.32595/iirjet.org/v4i1.2018.70.
Z. U. Ahmed, M. G. Mortuza, M. J. Uddin, Md. H. Kabir, Md. Mahiuddin, and MD. J. Hoque, ‘Internet of Things Based Patient Health Monitoring System Using Wearable Biomedical Device’, in 2018 International Conference on Innovation in Engineering and Technology (ICIET), Dhaka, Bangladesh, Dec. 2018, pp. 1–5. doi: 10.1109/CIET.2018.8660846.
E. N. Ganesh, ‘Health Monitoring System using Raspberry Pi and IOT’, Orient. J. Comput. Sci. Technol., vol. 12, no. 1, pp. 08–13, Apr. 2019, doi: 10.13005/ojcst12.01.03.
S. B. Baker, W. Xiang, and I. Atkinson, ‘Internet of Things for Smart Healthcare: Technologies, Challenges, and Opportunities’, IEEE Access, vol. 5, pp. 26521–26544, 2017, doi: 10.1109/ACCESS.2017.2775180.
S. Selvaraj and S. Sundaravaradhan, ‘Challenges and opportunities in IoT healthcare systems: a systematic review’, SN Appl. Sci., vol. 2, no. 1, p. 139, Jan. 2020, doi: 10.1007/s42452-019-1925-y.
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Copyright (c) 2022 Salini Pradhan, Ahmad Anwar Zainuddin, Rohilah Sahak, Muhammad Farhan Affendi Mohamad Yunos
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