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Role of Internet of Things (IoT) in Preventing and Controlling Disease Outbreak: A Snapshot of Existing Scenario

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Proceedings of the International Conference on Intelligent Computing, Communication and Information Security (ICICCIS 2022)

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

The Internet of Things (IoT) has the potential in preventing the spread of infectious diseases, remote patient monitoring, telemedicine, and the growing old age population. In today’s era, a pandemic (COVID-19) has been witnessed on such a scale that has shaken mankind. This pandemic affected billions of lives economically, socially, mentally, and physically. IoT is a measure that can convincingly and effectively help in the containment of epidemics. In this systematic literature review, our goal is to provide researchers with a more focused and detailed knowledge about the applications of IoT to predict, prevent, control, and monitor disease outbreaks. The importance of IoT is discussed, as well as how the COVID-19 outbreak is being controlled. We offer insights into the framework for managing disease outbreaks based on empirical and non-empirical investigations. Additionally, evaluation strategies and datasets utilized in the developed frameworks are also presented. After thoroughly examining the architecture, the flaws of current systems are discussed to give researchers new directions as they create IoT-based applications for disease outbreak. Finally, taking into account the shortcomings of the research studies that have been conducted so far, a hybrid framework has also been presented that is based on wearable sensors data.

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References

  1. Cheng J, Chen W, Tao F, Lin CL (2018) Industrial IoT in 5G environment towards smart manufacturing. J Ind Inf Integr 10:10–19. https://doi.org/10.1016/J.JII.2018.04.001

    Article  Google Scholar 

  2. Zhao JC, Zhang JF, Feng Y, Guo JX (2010) The study and application of the IOT technology in agriculture. In: Proceeding—2010 3rd IEEE international conference computing science information technology ICCSIT 2010. 2:462–465. https://doi.org/10.1109/ICCSIT.2010.5565120

  3. Sharma R (2017) Internet of Things: an approach for advancement in educational institution. In: India International Conference Information Processing IICIP 2016—Proceeding. https://doi.org/10.1109/IICIP.2016.7975351

  4. Srinivasan A (2018) IoT cloud based real time automobile monitoring system. In: 2018 3rd IEEE International Conference Intelligent Transportation Engineering ICITE 2018. pp 231–235. https://doi.org/10.1109/ICITE.2018.8492706

  5. What Is the Internet of Things (IoT)? https://www.oracle.com/internet-of-things/what-is-iot/. Last accessed Dec 08 2022

  6. Ebola virus disease. https://www.who.int/health-topics/ebola#tab=tab_1. Last accessed Nov 26 2021

  7. How do SARS and MERS compare with COVID-19? https://www.medicalnewstoday.com/articles/how-do-sars-and-mers-compare-with-covid-19#MERS. Last accessed 01 Dec 2022

  8. Chikungunya virus and prospects for a vaccine. https://www.medscape.com/viewarticle/774865_9. Last accessed 03 Mar 2022

  9. Valsalan P, Baomar TAB, Baabood AHO (2020) IoT based health monitoring system. J Crit Rev 7:739–743. https://doi.org/10.31838/jcr.07.04.137

  10. Ani R, Krishna S, Anju N, Sona AM, Deepa OS (2017) IoT based patient monitoring and diagnostic prediction tool using ensemble classifier. In: 2017 international conference on advances in computing, communications and informatics, ICACCI 2017. pp. 1588–1593. https://doi.org/10.1109/ICACCI.2017.8126068

  11. Box IM, Yang G, Xie L, Mäntysalo M, Zhou X, Pang Z, Xu LD, Member S (2014) A health-IoT platform based on the integration of intelligent packaging. Unobtrusive 10:2180–2191. https://doi.org/10.1109/TII.2014.2307795

    Article  Google Scholar 

  12. Chamola V, Hassija V, Gupta V, Guizani M (2020) 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. https://doi.org/10.1109/ACCESS.2020.2992341

    Article  Google Scholar 

  13. Singh RP, Javaid M, Haleem A, Suman R (2020) Internet of things (IoT) applications to fight against COVID-19 pandemic. Diabetes Metab Syndr 14:521–524. https://doi.org/10.1016/J.DSX.2020.04.041

    Article  Google Scholar 

  14. Mohd Aman AH, Hassan WH, Sameen S, Attarbashi ZS, Alizadeh M, Latiff LA (2021) IoMT amid COVID-19 pandemic: application, architecture, technology, and security, /pmc/articles/PMC7605812/. https://doi.org/10.1016/j.jnca.2020.102886

  15. Swayamsiddha S, Mohanty C (2020) Application of cognitive internet of medical things for COVID-19 pandemic. Diabetes Metab Syndr Clin Res Rev

    Google Scholar 

  16. Mohammed MN, Syamsudin H, Al-Zubaidi S, Sairah AK, Ramli R, Yusuf E (2020) Novel covid-19 detection and diagnosis system using iot based smart helmet. Int J Psychosoc Rehabil 24:2296–2303. https://doi.org/10.37200/IJPR/V24I7/PR270221

  17. Mohammed MN, Hazairin NA, Syamsudin H (2019) Novel coronavirus disease ( Covid-19 ): detection and diagnosis system using IoT based smart glasses. 29:954–960

    Google Scholar 

  18. Singh V, Chandna H, Kumar A, Kumar S, Upadhyay N, Utkarsh K (2020) IoT-Q-Band: a low cost internet of things based wearable band to detect and track absconding COVID-19 quarantine subjects. EAI Endorsed Trans Internet Things 6:163997. https://doi.org/10.4108/eai.13-7-2018.163997

    Article  Google Scholar 

  19. Tripathy AK, Mohapatra AG, Mohanty SP, Kougianos E, Joshi AM, Das G (2020) EasyBand: a wearable for safety-aware mobility during pandemic outbreak. IEEE Consum Electron Mag 9:57–61. https://doi.org/10.1109/MCE.2020.2992034

    Article  Google Scholar 

  20. Morais IDE, Filho B, Aquino G, Malaquias R, Girão G, Melo S (2021) An IoT-based healthcare platform for patients in ICU beds during the COVID-19 outbreak. 1–171. https://doi.org/10.1109/ACCESS.2021.3058448

  21. GSMA | IoT applications in the fight against COVID-19 | Mobile for development, https://www.gsma.com/mobilefordevelopment/blog/iot-applications-in-the-fight-against-covid-19/. Last accessed 01 Dec 2022.

  22. Improving vaccination systems—eVIN | UNDP in India, https://www.in.undp.org/content/india/en/home/projects/gavi1.html. Last accessed 03 Mar 2022

  23. China’s IoT response against coronavirus outbreak Shenzhen Jimi IoT Co., Ltd., https://www.jimilab.com/bolg/iot-against-coronavirus.html. Last accessed 03 Mar 2022

  24. Sareen S, Sood SK, Kumar S (2018) IoT-based cloud framework to control Ebola virus outbreak. J Ambient Intell Humaniz Comput 9:459–476. https://doi.org/10.1007/s12652-016-0427-7

    Article  Google Scholar 

  25. Sood SK, Mahajan I (2017) Computers in Industry Wearable IoT sensor based healthcare system for identifying and controlling Chikungunya virus. Comput Ind 91:33–44. https://doi.org/10.1016/j.compind.2017.05.006

    Article  Google Scholar 

  26. Thakur P, Kaur S (2018) An intelligent system for predicting and preventing Chikungunya virus. In: 2017 International conference on energy, communication, data analytics and soft computing. ICECDS 2017, Institute of electrical and electronics engineers inc., pp 3483–3492. https://doi.org/10.1109/ICECDS.2017.8390109

  27. Mahalakshmi B, Suseendran G (2018) Zika virus: A secure system usinf nbn classifier for predicting and preventing zika in cloud. Int J Recent Technol Eng 7:28–32

    Google Scholar 

  28. Internet S, Cloud OFT, To F, Zika C (2017) Methods secure internet of things-based cloud framework to control Zika virus. 1. https://doi.org/10.1017/S0266462317000113

  29. Sareen S, Gupta SK, Sood SK (2017) An intelligent and secure system for predicting and preventing Zika virus outbreak using Fog computing. Enterp Inf Syst 11:1436–1456. https://doi.org/10.1080/17517575.2016.1277558

    Article  Google Scholar 

  30. Al-Turaiki I, Alshahrani M, Almutairi T (2016) Building predictive models for MERS-CoV infections using data mining techniques. J Infect Public Health 9:744–748. https://doi.org/10.1016/j.jiph.2016.09.007

    Article  Google Scholar 

  31. Sandhu R, Sood SK, Kaur G (2016) An intelligent system for predicting and preventing MERS-CoV infection outbreak. J Supercomput 72:3033–3056. https://doi.org/10.1007/s11227-015-1474-0

    Article  Google Scholar 

  32. Sandhu R, Gill HK, Sood SK (2016) Smart monitoring and controlling of pandemic influenza a (H1N1) using social network analysis and cloud computing. J Comput Sci 12:11–22. https://doi.org/10.1016/j.jocs.2015.11.001

    Article  Google Scholar 

  33. Ketu S, Mishra PK (2021) Enhanced Gaussian process regression-based forecasting model for COVID-19 outbreak and significance of IoT for its detection. Appl Intell 51:1492–1512. https://doi.org/10.1007/s10489-020-01889-9

    Article  Google Scholar 

  34. Otoom M, Otoum N, Alzubaidi MA, Etoom Y, Banihani R (2020) An IoT-based framework for early identification and monitoring of COVID-19 cases. Biomed. Signal Process Control 62:102149. https://doi.org/10.1016/J.BSPC.2020.102149

  35. Wang B, Sun Y, Duong TQ, Member S, Nguyen LD (2020) Risk-aware identification of highly suspected COVID-19 cases in social IoT : A joint graph theory and reinforcement learning approach. 115655–115661. https://doi.org/10.1109/ACCESS.2020.3003750

  36. Ahanger TA, Tariq U, Nusir M, Aldaej A, Ullah I, Sulman A (2022) A novel IoT–fog–cloud-based healthcare system for monitoring and predicting COVID-19 outspread. J Supercomput 78:1783–1806. https://doi.org/10.1007/s11227-021-03935-w

    Article  Google Scholar 

  37. Aljumah A (2021) Assessment of machine learning techniques in IoT-based architecture for the monitoring and prediction of COVID-19. Electronics 10:1834. https://doi.org/10.3390/ELECTRONICS10151834

  38. Vijayakumar V, Malathi D, Subramaniyaswamy V, Saravanan P, Logesh R (2019) Fog computing-based intelligent healthcare system for the detection and prevention of mosquito-borne diseases. Comput Human Behav 100:275–285. https://doi.org/10.1016/j.chb.2018.12.009

    Article  Google Scholar 

  39. Hassan NH, Salwana E, Drus SM, Maarop N, Samy GN, Ahmad NA (2018) Proposed conceptual Iot-based patient monitoring sensor for predicting and controlling dengue. Int J Grid Distrib Comput 11:127–134. https://doi.org/10.14257/ijgdc.2018.11.4.11

  40. Navin K, Krishnan MBM, Lavanya S, Shanthini A (2017) A mobile health based smart hybrid epidemic surveillance system to support epidemic control programme in public health informatics. In: IEEE International conference on IoT and its Applications, ICIOT 2017. https://doi.org/10.1109/ICIOTA.2017.8073606

  41. Maghded HS, Ghafoor KZ, Sadiq AS, Curran K, Rawat DB, Rabie K (2020) A novel AI-enabled framework to diagnose coronavirus COVID-19 using smartphone embedded sensors: design study. In: Proceedings—2020 IEEE 21st international conference on information reuse and integration for data science, IRI 2020, pp 180–187. https://doi.org/10.1109/IRI49571.2020.00033

  42. Pravin A, Jacob TP, Nagarajan G (2020) An intelligent and secure healthcare framework for the prediction and prevention of Dengue virus outbreak using fog computing. Health Technol (Berl) 10:303–311. https://doi.org/10.1007/s12553-019-00308-5

    Article  Google Scholar 

  43. Pal A, Banerjee S, Banerjee R, Bandyopadhyay S, Deshpande P, Dasgupta R (2016) A novel approach to unify robotics, sensors, and cloud computing through IoT for a smarter healthcare. 536–542. https://doi.org/10.1007/978-3-319-47063-4.

  44. Rani S, Ahmed SH, Shah SC (2019) Smart health: a novel paradigm to control the Chickungunya virus. IEEE Internet Things J 6:1306–1311. https://doi.org/10.1109/JIOT.2018.2802898

    Article  Google Scholar 

  45. Bai L, Yang D, Wang X, Tong L, Zhu X, Zhong N, Bai C, Powell CA, Chen R, Zhou J, Song Y, Zhou X, Zhu H, Han B, Li Q, Shi G, Li S, Wang C, Qiu Z, Zhang Y, Xu Y, Liu J, Zhang D, Wu C, Li J, Yu J, Wang J, Dong C, Wang Y, Wang Q, Zhang L, Zhang M, Ma X, Zhao L, Yu W, Xu T, Jin Y, Wang X, Wang Y, Jiang Y, Chen H, Xiao K, Zhang X, Song Z, Zhang Z, Wu X, Sun J, Shen Y, Ye M, Tu C, Jiang J, Yu H, Tan F (2020) Chinese experts’ consensus on the Internet of Things-aided diagnosis and treatment of coronavirus disease 2019 (COVID-19). Clin eHealth 3:7–15. https://doi.org/10.1016/j.ceh.2020.03.001

  46. Andreas A, Mavromoustakis CX, Mastorakis G, Mongay Batalla J, Sahalos JN, Pallis E, Markakis E (2021) IoT cloud-based framework using of smart integration to control the spread of COVID-19. In: IEEE International conference on communications. IEEE, pp. 1–5. https://doi.org/10.1109/ICC42927.2021.9500528

  47. Iyda A, Elkind P, Miranda P, Branco A, Alencar P, Cowan D, Endler M, Pelegrini P (2021) A conceptual IoT-based early-warning architecture for remote monitoring of COVID-19 patients in wards and at home. Internet of Things. 100399. https://doi.org/10.1016/j.iot.2021.100399

  48. Saha R, Kumar G, Kumar N, Kim TH, Devgun T, Thomas R, Barnawi A (2021) Internet-of-things framework for oxygen saturation monitoring in COVID-19 environment. IEEE Internet Things J 1–11. https://doi.org/10.1109/JIOT.2021.3098158.

  49. Mukhtar H, Rubaiee S, Krichen M, Alroobaea R (2021) An iot framework for screening of covid-19 using real-time data from wearable sensors. Int J Environ Res Public Health 18. https://doi.org/10.3390/ijerph18084022.

  50. Deep P, Kaur R, Deep K, Dhiman G, Soni M (2021) Informatics in medicine unlocked fog-centric IoT based smart healthcare support service for monitoring and controlling an epidemic of Swine Flu virus. Inf Med Unlocked 26:100636. https://doi.org/10.1016/j.imu.2021.100636

    Article  Google Scholar 

  51. Mishra T, Wang M, Metwally AA, Bogu GK, Brooks AW, Bahmani A, Alavi A, Celli A, Higgs E, Dagan-rosenfeld O, Fay B, Kirkpatrick S, Kellogg R, Gibson M, Wang T, Hunting EM, Mamic P, Ganz AB, Rolnik B, Li X, Snyder MP (2020) Smartwatch data. Nat Biomed Eng 4. https://doi.org/10.1038/s41551-020-00640-6

  52. Quer G, Radin JM, Gadaleta M, Baca-motes K, Ariniello L, Ramos E, Kheterpal V, Topol EJ, Steinhubl SR (2021) Wearable sensor data and self-reported symptoms for COVID-19 detection. Nat Med 27. https://doi.org/10.1038/s41591-020-1123-x

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Authors and Affiliations

  1. Department of Computer Science and Applications, Panjab University, Chandigarh, India

    Manpreet Kaur Dhaliwal & Rohini Sharma

  2. Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Naveen Bindra

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  1. Manpreet Kaur Dhaliwal
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  2. Rohini Sharma
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  3. Naveen Bindra
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Correspondence to Manpreet Kaur Dhaliwal .

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Editors and Affiliations

  1. Serbian Academy of Sciences and Arts, Belgrade, Serbia

    Vladan Devedzic

  2. Department of Computer Science and Engineering, Central University of Rajasthan, Ajmer, Rajasthan, India

    Basant Agarwal

  3. Department of Computer Science and Engineering, Swami Keshvanand Institute of Technology Management and Gramothan, Jaipur, Rajasthan, India

    Mukesh Kumar Gupta

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Dhaliwal, M.K., Sharma, R., Bindra, N. (2023). Role of Internet of Things (IoT) in Preventing and Controlling Disease Outbreak: A Snapshot of Existing Scenario. In: Devedzic, V., Agarwal, B., Gupta, M.K. (eds) Proceedings of the International Conference on Intelligent Computing, Communication and Information Security. ICICCIS 2022. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-1373-2_28

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