Integrated computer model of AmI-IoT-DA for care of elderly people living alone
Keywords:
Internet of Things, Environmental intelligence, Data analytics, Adult care, Welfare
Abstract
Elderly people suffer physical and mental deterioration, which they prevent and / or hinder the control of household chores, the loss of their dependence and autonomy, affecting their quality of life and well-being. This paper presents an AmI-IoT-DA integrated layered model integrating functionalities of the Internet of Things (IoT), Ambient Intelligence (AmI) and Data Analytics (DA). The model is applied to the monitoring and assistance of elderly people living alone. The model proposes four segments responsible for automating housing, supervising the user, taking decisions, supervise events, identify habits, and access AmI, IoT and Data Analytics services
References
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Gómez García, C. A., & Velasco Medina, J. (2014). Sistema de pulsioximetría y capnografía para dispositivos móviles Android. Ingeniería Biomédica, 8(15), 36–44. https://doi.org/10.24050/19099762.n15.2014.593
González, F., Villegas, O., Ramírez, D., Sánchez, V., & Domínguez, H. (2014). Smart Multi-Level Tool for Remote Patient Monitoring Based on a Wireless Sensor Network and Mobile Augmented Reality. Sensors, 14(9), 17212–17234. https://doi.org/10.3390/s140917212
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Mileo, A., Merico, D., & Bisiani, R. (2008). Wireless sensor networks supporting context-aware reasoning in assisted living. In Proceedings of the 1st ACM international conference on PErvasive Technologies Related to Assistive Environments - PETRA ’08 (p. 1). New York, USA: ACM Press. https://doi.org/10.1145/1389586.1389651
Morelos Ramírez, R., Ramírez Pérez, M., Sánchez Dorantes, G., Chavarín Rivera, C., & Meléndez-Herrada, E. (2014). El trabajador de la salud y el riesgo de enfermedades infecciosas adquiridas. Las precauciones estándar y de bioseguridad. Revista de La Facultad de Medicina UNAM, 57(4), 34–42. Retrieved from http://www.medigraphic.com/cgi-bin/new/resumen.cgi?IDARTICULO=51020
ORACLE. (2017). Oracle Advanced Analytics’ Machine Learning Algorithms SQL Functions. Retrieved November 28, 2017, from https://www.oracle.com/technetwork/database/enterprise-edition/odm-techniques-algorithms-097163.html
Organización de la Naciones Unidas. (2006). Convención sobre los derechos de las personas con discapacidad. Retrieved April 5, 2016, from http://www.un.org/spanish/disabilities/default.asp?id=497
Organización Mundial de la Salud. (2015). Informe Mundial sobre el envejecimiento y la salud. Retrieved from https://www.who.int/ageing/publications/world-report-2015/es/
Parra-Henao, G. J. (2010). Sistemas de información geográfica y sensores remotos. Aplicaciones en enfermedades transmitidas por vectores. CES Medicina, 24(2), 75–89.
Parra Alba, W. E. (2016). Modelo y sistema de análisis, generación y entrega de información, para apoyar la toma de decisiones a partir de datos obtenidos de pacientes remotos de la tercera edad con Neumonía Adquirida en la Comunidad (NAC). Pontificia Universidad Javeriana. Retrieved from https://repository.javeriana.edu.co/handle/10554/21196
Rajkomar, A., Mayer, A., & Blandford, A. (2015). Understanding safety–critical interactions with a home medical device through Distributed Cognition. Journal of Biomedical Informatics, 56, 179–194. https://doi.org/10.1016/j.jbi.2015.06.002
Sánchez, A., González, E., & Barreto, L. (2018). Integrated Model AmI-IoT-DA for Care of Elderly People. In Advances in Computing (pp. 487–497). https://doi.org/10.1007/978-3-319-98998-3_37
Silva, J. M., Mouttham, A., & El Saddik, A. (2009). UbiMeds: a mobile application to improve accessibility and support medication adherence. In Proceedings of the 1st ACM SIGMM international workshop on Media studies and implementations that help improving access to disabled users - MSIADU ’09 (p. 71). New York, USA: ACM Press. https://doi.org/10.1145/1631097.1631109
Skubic, M., Guevara, R. D., & Rantz, M. (2015). Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment. IEEE Journal of Translational Engineering in Health and Medicine, 3, 1–11. https://doi.org/10.1109/JTEHM.2015.2421499
Sommerville, I. (1995). Software engineering. Retrieved from https://dl.acm.org/citation.cfm?id=211474
Villar-Montini, A. (2009). Remote wireless monitoring. Archivos de Cardiologia de Mexico, 79(2), 75–78.
Zamora-Izquierdo, M. A., Santa, J., & Gomez-Skarmeta, A. F. (2010). An Integral and Networked Home Automation Solution for Indoor Ambient Intelligence. IEEE Pervasive Computing, 9(4), 66–77. https://doi.org/10.1109/MPRV.2010.20
Campaña Bastidas, S. E., & Londoño Peláez, J. M. (2013). Estudio de redes de sensores y aplicaciones orientadas a la recolección y análisis de señales biomédicas. Revista Gerencia Tecnológica Informática, 12(33), 85–99.
Celler, B. G., & Sparks, R. S. (2015). Home Telemonitoring of Vital Signs—Technical Challenges and Future Directions. IEEE Journal of Biomedical and Health Informatics, 19(1), 82–91. https://doi.org/10.1109/JBHI.2014.2351413
Chandler, D. L. (2014). Tomorrow’s Hospital: How technology will be transforming both inpatient and at-home care. IEEE Pulse, 5(6), 16–21. https://doi.org/10.1109/MPUL.2014.2355298
Chang, W. L., & Grady, N. (2018). NIST Big Data Interoperability Framework: Volume 1, Big Data Definitions [Version 2]. Retrieved December 12, 2018, from https://www.nist.gov/publications/nist-big-data-interoperability-framework
CISCO. (2015). Fog Computing and the Internet of Things: Extend the Cloud to Where the Things Are. Retrieved from https://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-overview.pdf
Doğali Çetin, G., Çetin, Ö., & Bayimiş, C. (2015). A real-time life-care monitoring framework: WarnRed hardware and software design. Turkish Journal of Electrical Engineering & Computer Sciences, 23, 1040–1050. https://doi.org/10.3906/elk-1304-178
Fanucci, L., Saponara, S., Bacchillone, T., Donati, M., Barba, P., Sanchez-Tato, I., & Carmona, C. (2013). Sensing Devices and Sensor Signal Processing for Remote Monitoring of Vital Signs in CHF Patients. IEEE Transactions on Instrumentation and Measurement, 62(3), 553–569. https://doi.org/10.1109/TIM.2012.2218681
Felipe Salech, M., Rafael Jara, L., & Luis Michea, A. (2012). Cambios fisiológicos asociados al envejecimiento. Revista Médica Clínica Las Condes, 23(1), 19–29. https://doi.org/10.1016/S0716-8640(12)70269-9
Gómez García, C. A., & Velasco Medina, J. (2014). Sistema de pulsioximetría y capnografía para dispositivos móviles Android. Ingeniería Biomédica, 8(15), 36–44. https://doi.org/10.24050/19099762.n15.2014.593
González, F., Villegas, O., Ramírez, D., Sánchez, V., & Domínguez, H. (2014). Smart Multi-Level Tool for Remote Patient Monitoring Based on a Wireless Sensor Network and Mobile Augmented Reality. Sensors, 14(9), 17212–17234. https://doi.org/10.3390/s140917212
González Palacio, L., & Urrego Giraldo, G. (2010). Modelo de contexto y de dominio para la ingeniería de requisitos de sistemas ubicuos. Revista Ingenierías Universidad de Medellín, 9(17), 151–164. Retrieved from https://repository.udem.edu.co/handle/11407/779
Guevara Valdivia, M. E., Echegaray-Trelles, A., Hernández, J., Cordero-Pérez, L. de J., Valderrama de León, R., Santos, M. A., & Huarte-Hernández, Y. (2011). Monitoreo remoto y seguimiento del paciente con desfibrilador automático implantable y terapia de resincronización cardiaca. Archivos de Cardiología de México, 81(2), 93–99.
Hassanalieragh, M., Page, A., Soyata, T., Sharma, G., Aktas, M., Mateos, G., … Andreescu, S. (2015). Health Monitoring and Management Using Internet-of-Things (IoT) Sensing with Cloud-Based Processing: Opportunities and Challenges. In 2015 IEEE International Conference on Services Computing (pp. 285–292). IEEE. https://doi.org/10.1109/SCC.2015.47
Lopardo, G., Basombrío, A., Clara, L., Desse, J., De Vedia, L., Di Libero, E., … Scapellato, P. (2015). Neumonia adquirida de la comunidad en adultos. Recomendaciones sobre su atención. Medicina, 75(4), 245–257.
Mileo, A., Merico, D., & Bisiani, R. (2008). Wireless sensor networks supporting context-aware reasoning in assisted living. In Proceedings of the 1st ACM international conference on PErvasive Technologies Related to Assistive Environments - PETRA ’08 (p. 1). New York, USA: ACM Press. https://doi.org/10.1145/1389586.1389651
Morelos Ramírez, R., Ramírez Pérez, M., Sánchez Dorantes, G., Chavarín Rivera, C., & Meléndez-Herrada, E. (2014). El trabajador de la salud y el riesgo de enfermedades infecciosas adquiridas. Las precauciones estándar y de bioseguridad. Revista de La Facultad de Medicina UNAM, 57(4), 34–42. Retrieved from http://www.medigraphic.com/cgi-bin/new/resumen.cgi?IDARTICULO=51020
ORACLE. (2017). Oracle Advanced Analytics’ Machine Learning Algorithms SQL Functions. Retrieved November 28, 2017, from https://www.oracle.com/technetwork/database/enterprise-edition/odm-techniques-algorithms-097163.html
Organización de la Naciones Unidas. (2006). Convención sobre los derechos de las personas con discapacidad. Retrieved April 5, 2016, from http://www.un.org/spanish/disabilities/default.asp?id=497
Organización Mundial de la Salud. (2015). Informe Mundial sobre el envejecimiento y la salud. Retrieved from https://www.who.int/ageing/publications/world-report-2015/es/
Parra-Henao, G. J. (2010). Sistemas de información geográfica y sensores remotos. Aplicaciones en enfermedades transmitidas por vectores. CES Medicina, 24(2), 75–89.
Parra Alba, W. E. (2016). Modelo y sistema de análisis, generación y entrega de información, para apoyar la toma de decisiones a partir de datos obtenidos de pacientes remotos de la tercera edad con Neumonía Adquirida en la Comunidad (NAC). Pontificia Universidad Javeriana. Retrieved from https://repository.javeriana.edu.co/handle/10554/21196
Rajkomar, A., Mayer, A., & Blandford, A. (2015). Understanding safety–critical interactions with a home medical device through Distributed Cognition. Journal of Biomedical Informatics, 56, 179–194. https://doi.org/10.1016/j.jbi.2015.06.002
Sánchez, A., González, E., & Barreto, L. (2018). Integrated Model AmI-IoT-DA for Care of Elderly People. In Advances in Computing (pp. 487–497). https://doi.org/10.1007/978-3-319-98998-3_37
Silva, J. M., Mouttham, A., & El Saddik, A. (2009). UbiMeds: a mobile application to improve accessibility and support medication adherence. In Proceedings of the 1st ACM SIGMM international workshop on Media studies and implementations that help improving access to disabled users - MSIADU ’09 (p. 71). New York, USA: ACM Press. https://doi.org/10.1145/1631097.1631109
Skubic, M., Guevara, R. D., & Rantz, M. (2015). Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment. IEEE Journal of Translational Engineering in Health and Medicine, 3, 1–11. https://doi.org/10.1109/JTEHM.2015.2421499
Sommerville, I. (1995). Software engineering. Retrieved from https://dl.acm.org/citation.cfm?id=211474
Villar-Montini, A. (2009). Remote wireless monitoring. Archivos de Cardiologia de Mexico, 79(2), 75–78.
Zamora-Izquierdo, M. A., Santa, J., & Gomez-Skarmeta, A. F. (2010). An Integral and Networked Home Automation Solution for Indoor Ambient Intelligence. IEEE Pervasive Computing, 9(4), 66–77. https://doi.org/10.1109/MPRV.2010.20
How to Cite
Sánchez, A. A., González Guerrero, E., & Barreto, L. E. (2019). Integrated computer model of AmI-IoT-DA for care of elderly people living alone. Revista Colombiana De Computación, 20(1), 59–71. https://doi.org/10.29375/25392115.3607
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Published
2019-05-28
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Article of scientific and technological research
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