Evaluación de la criticidad de los componentes de un sistema IoT en salud, utilizando el método AHP

Autores/as

DOI:

https://doi.org/10.33448/rsd-v10i2.12917

Palabras clave:

Internet de las cosas; IoT; Analytic Hierarchy process; AHP; Risgo; Salud.

Resumen

El Internet de las Cosas (IoT) en el área de la salud ofrece muchas facilidades o comodidades, ya que permite la comunicación entre máquinas, como monitorear el desarrollo de enfermedades crónicas, difundir el control de enfermedades, monitorear la caída de los ancianos. Sin embargo, esta comunicación puede traer algunos riesgos asociados, como violación de la privacidad y seguridad, pérdida de la integridad de los datos. Así, en este contexto, este estudio identificó los componentes de la red que interfieren con la ocurrencia del riesgo y su respectiva jerarquía dentro del sistema IoT utilizado en el área de salud. Se identificaron 8 (ocho) factores en la literatura y fueron validados por 2 (dos) académicos expertos con conocimiento en el tema. El uso del método Analytic Hierarchy Process (AHP) permitió identificar los componentes más críticos relacionados con el estudio aquí propuesto.

Citas

Albahri, O. S., Albahri, A. S., Zaidan, A. A., Zaidan, B. B., Alsalem, M. A., Mohsin, A. H., Mohammed, K. I., Alamoodi, A. H., Nidhal, S., Enaizan, O., Chyad, M. A., Abdulkareem, K. H., Almahdi, E. M., Al Shafeey, G. A., Baqer, M. J., Jasim, A. N., Jalood, N. S., & Shareef, A. H. (2019). Fault-Tolerant mHealth Framework in the Context of IoT Based Real-Time Wearable Health Data Sensors. IEEE Access. 7. 50052-50080. 10.1109/access.2019.2910411

Ali, F., Khand, P., Kwak, D., Islam, S. M., Ullahe, N., Yoo, S., & Kwak, K. S. (2018). Type-2 fuzzy ontology-aided recommendation systems for IoT-based healthcare. Computer Communications. 119. 138-155. 10.1016/j.comcom.2017.10.005.

Azimi, I., Pahikkala, T., Rahmani, A. M.., Niela-Vilén, H. Axelin, A., & Liljeberg, P. (2019). Missing data resilient decision-making for healthcare IoT through personalization: A case study on maternal health. Future Generation Computer Systems. 96. 297-308. 10.1016/j.future.2019.02.015

Ben-Daya, M., Hassini., E., & Bahroun, Z. (2017). Internet of things and supply chain management: a literature review. International Journal of Production Research. 57. (15-16). 4719-4742. 10.1080/00207543.2017.1402140

Biswas, A, & Giaffreda. R. (2014) IoT and cloud convergence: Opportunities and challenges. IEEE World Forum on Internet of Things (WF-IoT). 375-376.

Bento, A., Gomes, J., & Melo de Souza, E., (2019) An IoT Experiment with Screen Development Using Nextion and ESP8266e + Motorshield. 10th International Conference on Computing. Communication and Networking Technologies (ICCCNT).

Creswell. J. W., (2010). Projeto de pesquisa: Métodos qualitativo. Quantitativo e misto. Artmed.

Domingues, M. F., Alberto, N., Leitão, C. S. J., Tavares, C., De Lima, E. R., Radwan, A., Sucasas, V., Rodriguez, J., Andre, P. S. B., & Antunes, P. F. C. (2019). Insole Optical Fiber Sensor Architecture for Remote Gait Analysis-An e-Health Solution. IEEE Internet of Things Journal. 6 (1). 207-214. 10.1109/jiot.2017.2723263

Elsaadany, A., & Soliman, M. (2017). Experimental Evaluation of Internet of Things in the Educational Environment. International Journal of Engineering Pedagogy. 7 (3). 50-60. 10.3991/ijep.v7i3.7187

Gyamfi, K. S., Brusey, J., Gaura, E., & Wilkins, R. (2019). Heartbeat design for energy-aware IoT: Are your sensors alive?. Expert Systems with Applications. 128. 124-139. 10.1016/j.eswa.2019.03.022

Hu, Z. W., Bai Z. X., Yang, Y. Z., Zheng, Z. J., Bian, K. G., & Song L. Y. (2019). UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture. Technologies. and Implementation. IEEE Network. 33. 14-22. 10.1109/mnet.2019.1800214

Huang, Y. L., & Sun, W. L. (2018). An AHP-based Risk Assessment for an Industrial IoT Cloud. 18th IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). 637-638. 10.1109/qrs-c.2018.00112

Khan, T. A. Alam. M., Kadir. K. A Shahid. Z., & Mazliham. M. S. (2019). Artificial Intelligence based prediction of seizures for Epileptic Patients: IoT based Cost effective Solution. 7th International Conference on Information and Communication Technology (ICoICT). 10.1109/ICoICT.2019.8835350

Kumar, R. (2011). Research Methodology: a step-by-step guide for beginners. SAGE Publication.

Lomotey, R. K. Pry, J. & Sriramoju, S. (2017). Wearable IoT data stream traceability in a distributed health information system. Pervasive and Mobile Computing. 40. 692-707. 10.1016/j.pmcj.2017.06.020

Liao, Y. X., Deschamps, F., Loures. E., & Ramos, L. F. P. (2017) Past. present and future of Industry 4.0 - a systematic literature review and research agenda proposal. International Journal of Production Research. 55(12). 3609-3629. 10.1080/00207543.2017.1308576

Lin, Y. B., Lin, Y. W., Lin, J. Y., & Hung, H. N. (2019). SensorTalk: An IoT Device Failure Detection and Calibration Mechanism for Smart Farming. Sensors. 19 (21). 4788. 10.3390/s19214788

Mena, D. M., Papapanagiotou, I., & Yang, B. (2018). Internet of things: Survey on security. Information Security Journal: A Global Perspective. 27 (3). 162-182. 10.1080/19393555.2018.1458258

Mittelstadt, B. (2017). Ethics of the health-related internet of things: a narrative review. Ethics and Information Technology. 19 (3). 157-175. 10.1007/s10676-017-9426-4

Mittelstadt, B. (2017 [2]). Designing the health-related internet of things: Ethical principles and guidelines. Information (Switzerland). 8 (3). 10.3390/info8030077

Muhammed, T., Mehmood, R., Albeshri. A., & Katib, I. (2018). UbeHealth: A Personalized Ubiquitous Cloud and Edge-Enabled Networked Healthcare System for Smart Cities. IEEE ACCESS. 6. ‏ 32258-3285. 10.1109/ACCESS.2018.2846609

Mustafa, M. A., & Albahar, J. (1991). Project risk assessment using the analytic hierarchy process.IEEE Transactions on Engineering Management. 38(1):46-52.1991. 10.1109/17.65759

Pereira, A. S. Shitsuka, D. M., Parreira, F. J., & Shitsuka, R. (2018). Metodologia da Pesquisa Científica. Universidade Federal de Santa Maria. (pp. 65-74).

Radanliev, P., De Roure, D. Nurse, J. R. C. Montalvo, R., Cannady, S., Santos, O., Maddox, La’Treall Burnap. P., & Maple, C. (2020). Future developments in cyber risk assessment for the internet of things. SN Applied Sciences. 2. 10.1007/s42452-019-1931-0

Ray, P. P., (2017). Understanding the role of internet of things towards smart e- healthcare services. Biomed. Res. 28 (4).1604–1609.

Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences. 1(1). 83-98. 10.1504/ IJSSci.2008.01759.

Saaty, T. L. (2013). Theory and Applications of the Analytic Network Process: Decision Making with Benefits. Opportunities. Costs. and Risks. Pittsburgh: RWS Publications.

Sharma, S., Chen, K. & Sheth, A., (2018). Toward practical privacy-preserving analytics for IoT and cloud-based healthcare systems. IEEE Internet Computing. 22 (2). 42-51.

Sood, S. K. & Mahajan, I. (2017). Wearable IoT sensor based healthcare system for identifying and controlling chikungunya virus. Computers in Industry. 91. 33-44. 10.1016/j.compind.2017.05.006

Tan, E., & Halim, Z. (2019). Health care Monitoring System and Analytics Based on Internet of Things Framework. IETE JOURNAL OF RESEARCH. 65 (5). 653-660. 10.1080/03772063.2018.1447402

Tao, H., Bhuiyan, M. Abdalla, A. N, Hassan M. M., Zain, J. M., & Hayajneh, T. (2019). Secured Data Collection with Hardware-Based Ciphers for IoT-Based Healthcare. IEEE Internet of Things Journal. 6 (1). 410-420. 10.1109/JIOT.2018.2854714

Wang, L. (2018). Environment supervision system for chemical industry park based on IOT. Chemical Engineering Transactions. 67. 481-486. 10.3303/CET1867081

Wilkerson, G. B. Gupta, A., & Colston. M. A. (2018). Mitigating Sports Injury Risks Using Internet of Things and Analytics Approaches. Risk Analysis. 38 (7). 1348-1360. 10.1111/risa.12984

Yan, B., Wang, X. & Shi, P. (2017). Risk assessment and control of agricultural supply chains under Internet of Things. Agrekon - Agricultural Economics Research. Policy and Practice in Southern Africa. 56 (1). 1-12. https://doi.org/10.1080/03031853.2017.1284680.

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Publicado

28/02/2021

Cómo citar

KINJO, E. M.; LIBRANTZ, A. F. H. .; SOUZA, E. M. de .; GALDINO, M. Evaluación de la criticidad de los componentes de un sistema IoT en salud, utilizando el método AHP. Research, Society and Development, [S. l.], v. 10, n. 2, p. e57010212917, 2021. DOI: 10.33448/rsd-v10i2.12917. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/12917. Acesso em: 27 jul. 2024.

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