Abstract
The current Coronavirus (Covid-19) pandemic caused by the upcoming SARS-CoV-2 category has terrified human health worldwide. It has resulted in millions of demises, threatening the elderly and people with chronic diseases. Most healthcare institutions are facing congestion and the lack of resources during this period, and it has also become an unbearable issue to have no accommodation capacity in hospitals, where patients can no longer be accommodated. This paper proposes a cost-effective intelligent patient monitoring system for the Covid-19 patients’ wards in Sri Lankan Hospitals using IoT and Cloud Computing technologies which helps identify high-priority patients based on their health conditions. Continuous monitoring of the ward's environmental factors helps to ensure that it is a safe environment for Covid-19 patients. Moreover, it ensures safeguarding medical staff by reducing interactions with patients and enforcing safety measures in the hospital environment by face mask detection. The research was performed by implementing a proof of concept with systematic testing and qualitative analysis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
WHO Coronavirus Disease (COVID-19) Dashboard. https://covid19.who.int/. Accessed 20 Oct 2020
Chamola, V., Hassija, V., Gupta, V., Guizani, M.: A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact. IEEE Access 8, 90225–90265 (2020)
Athira, A., Devika, T.D., Varsha, K.R., Bose, S.S.: Design and development of IOT based multi-parameter patient monitoring system. In: 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, pp. 862–866 (2020)
Wang, B., Sun, Y., Duong, T.Q., Nguyen, L.D., Hanzo, L.: Risk-aware identification of highly suspected COVID-19 cases in social IoT: a joint graph theory and reinforcement learning approach. IEEE Access 8, 115655–115661 (2020)
Anbarasi, M.S., SarathaDevi, K.: Patient healthcare monitoring system incorporating internet of things. Int. J. Adv. Eng. Res. Dev. Pondicherry Eng. Coll. India 5(2), (2018)
Gope, P., Hwang, T.: BSN-care: a secure IoT-based modern healthcare system using body sensor network. IEEE Sensors J. 16(5), 1368–1376 (2016)
Ingole, A., Ambatkar, S., Kakde, S.: Implementation of health-care monitoring system using Raspberry Pi. In: 2015 International Conference on Communications and Signal Processing (ICCSP), Melmaruvathur, pp. 1083–1086, IEEE (2015)
Ibhaze, A.E., Eleanor, E.C., Idachaba, F.E.: E-health monitoring system for the aged. In: 2016 IEEE International Conference on Emerging Technologies and Innovative Business Practices for the Transformation of Societies (EmergiTech), Balaclava, pp. 298–299 (2016). https://doi.org/10.1109/EmergiTech.2016.7737355
COVID-19 vs. Raspberry Pi: Researchers bring IoT technology to disease detection (2020). https://www.networkworld.com/article/3534101/covid-19-vs-raspberry-piresearchers-bring-iot-technology-to-disease-detection.html/. Accessed 20 Oct 2020
Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M.: Internet of things: a survey on enabling tech-nologies, protocols, and applications. IEEE Commun. Surv. Tutor. 17(4,), 2347–2376 (2015)
Yassein, M.B., Shatnawi, M.Q., Al-zoubi, D.: Application layer protocols for the Internet of Things: a survey. In: 2016 International Conference on Engineering & MIS (ICEMIS), Agadir, pp. 1–4 (2016). https://doi.org/10.1109/ICEMIS.2016.7745303
Liu, B.: Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Springer, Berlin/Heidelberg, Germany (2011)
Ravish, et al.: IoT Based road travel time detection. In: International Conference on Advances in Computing, Communications and Informatics (ICACCI) (2018). https://doi.org/10.1109/ICACCI.2018.8554804. Accessed 3 Nov 2020
Akbar, M.S., Yu, H., Cang, S.: TMP: Tele-medicine protocol for slotted 802.15.4 with duty-cycle optimization in wireless body area sensor networks. IEEE Sensors J. 17(6), 1925–1936 (2017). https://doi.org/10.1109/JSEN.2016.2645612
Dhadge, A., Tilekar, G.: Severity monitoring device for COVID-19 positive patients. In: 2020 3rd International Conference on Control and Robots (ICCR), pp. 25–29 (2020). https://doi.org/10.1109/ICCR51572.2020.9344386
Bella, A., Latif, R., Saddik, A., Jamad, L.: Review and evaluation of heart rate monitoring based vital signs, a case study: Covid-19 pandemic. In: 2020 6th IEEE Congress on Information Science and Technology (CiSt), pp. 79–83 (2020). https://doi.org/10.1109/CiSt49399.2021.9357302
Nachiar, C.C., Ambika, N., Moulika, R., Poovendran, R.: Design of cost-effective wearable sensors with integrated health monitoring system. In: 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), pp. 1289–1292 (2020). https://doi.org/10.1109/I-SMAC49090.2020.9243462
Muthusinghe, M.R.S., Palliyaguru, S.T., Weerakkody, W.A.N.D., Hashini Saranga, A.M., Rankothge, W.H.: Towards smart farming: accurate prediction of paddy harvest and rice demand”, R10-HTC (2018)
Perera, D., Rathnayaka, C., Dilan, S., Siriweera, L., Rankothge, W.H.: Sustainable tourism: application of optimization algorithms to schedule tour plans. R10-HTC (2018)
Jayasuriya, M.C., Galappaththi, K.T., Sampath, D., Nipunika, N., Rankothge, W.: Experimental study on an efficient dengue disease management system: planning and optimizing hospital staff allocation. Int. J. Adv. Comput. Sci. Appl. (2018)
Thiranjaya, C., Rushan, R., Udayanga, P.: Towards a smart city: application of optimization for a smart transportation management system. In: ICIAfS (2019)
Perera, S., Dissanayake, S., Fernando, D.: Supply and demand planning of electricity power: a comprehensive solution. In: CICT (2019)
Fernando, W.D.I., Rankothge, W.H.: Optimization of customer-friendly manual load shedding system. In: ICAC (2019)
Senarath, S.M.M.M., Perera, M.T.K.: Smart platform for film shooting management. In: CICT (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Rankothge, W.H., Serasinghe, C., Jayakody, C., Bandara, O., Kehelella, P. (2022). IoT Based Remote COVID-19 Patients Monitoring System for Local Hospitals in Sri Lanka. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2021, Volume 2. FTC 2021. Lecture Notes in Networks and Systems, vol 359. Springer, Cham. https://doi.org/10.1007/978-3-030-89880-9_52
Download citation
DOI: https://doi.org/10.1007/978-3-030-89880-9_52
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-89879-3
Online ISBN: 978-3-030-89880-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)