ASAPe: uma Arquitetura para Sensoriamento Preditivo em Computação Vestível
Resumo
Dentre os vários conceitos associados à Internet das Coisas (IoT), destacamos a computação vestível, a qual envolve sensoriamento corporal para captar dados das pessoas que estiverem ”vestindo”o sensor. Este artigo apresenta ASAPe, uma arquitetura para sensoriamento preditivo em computação vestível. Técnicas e estratégias de implementação da nossa proposta são discutidas e avaliadas nesta proposta. Os resultados alcançados até o presente momento indicam que a ASAPe pode ser muito útil tanto em contextos de coleta de dados em tempo real como também em quantidade massiva de dados. A principal contribuição é fornecer um novo paradigma para trabalhar componentes e predição em Computação Vestível.
Referências
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Spelmezan, D. (2012). An investigation into the use of tactile instructions in snowboarding. In Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services, pages 417–426. ACM.
Uddin, M., Salem, A., Nam, I., and Nadeem, T. (2015). Wearable sensing framework for human activity monitoring. In Proceedings of the 2015 workshop on Wearable Systems and Applications, pages 21–26. ACM.
Wang, K., Wang, Y., Sun, Y., Guo, S., and Wu, J. (2016). Green industrial internet of things architecture: an energy-efficient perspective. IEEE Communications Magazine, 49.
Chen, M., Zhang, Y., Li, Y., Hassan, M. M., and Alamri, A. (2015). Aiwac: Affective interaction through wearable computing and cloud technology. IEEE Wireless Communications, 22(1):20–27.
Conjeti, S., Singh, R. R., and Banerjee, R. (2012). Bio-inspired wearable computing architecture and physiological signal processing for on-road stress monitoring. In Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics, pages 479–482. IEEE.
Forkan, A. R. M. and Khalil, I. (2016). A probabilistic model for early prediction of abnormal clinical events using vital sign correlations in home-based monitoring. In Pervasive Computing and Communications (PerCom), 2016 IEEE International Conference on, pages 1–9. IEEE.
Galzarano, S., Giannantonio, R., Liotta, A., and Fortino, G. (2016). A task-oriented framework for networked wearable computing. IEEE Transactions on Automation Science and Engineering, 13(2):621–638.
Gheith, A., Rajamony, R., Bohrer, P., Agarwal, K., Kistler, M., Eagle, B. W., Hambridge, C., Carter, J., and Kaplinger, T. (2016). Ibm bluemix mobile cloud services. IBM Journal of Research and Development, 60(2-3):7–1.
Glass, L., Hunter, P., and McCulloch, A. (2012). Theory of heart: biomechanics, biophysics, and nonlinear dynamics of cardiac function. Springer Science & Business Media.
Gope, P. and Hwang, T. (2016). Bsn-care: A secure iot-based modern healthcare system using body sensor network. IEEE Sensors Journal, 16(5):1368–1376.
Hiremath, S., Yang, G., and Mankodiya, K. (2014). Wearable internet of things: Concept, architectural components and promises for person-centered healthcare. In Wireless Mobile Communication and Healthcare (Mobihealth), 2014 EAI 4th International Conference on, pages 304–307. IEEE.
Hyndman, R. J., Khandakar, Y., et al. (2007). Automatic time series for forecasting: the forecast package for R. Number 6/07. Monash University, Department of Econometrics and Business Statistics.
Jaimes, L. G., Gagneja, K., Akbaş, M. İ., and Vergara-Laurens, I. J. (2017). Future stress, forecasting physiological signals. In Computing and Communication Workshop and Conference (CCWC), 2017 IEEE 7th Annual, pages 1–5. IEEE.
Kan, V., Fujii, K., Amores, J., Zhu Jin, C. L., Maes, P., and Ishii, H. (2015). Social textiles: Social affordances and icebreaking interactions through wearable social messaging. In Proceedings of the Ninth International Conference on Tangible, Embedded, and Embodied Interaction, pages 619–624. ACM.
Kang, J. J., Adibi, S., Larkin, H., and Luan, T. (2015). Predictive data mining for converged internet of things: A mobile health perspective. In Telecommunication Networks and Applications Conference (ITNAC), 2015 International, pages 5–10. IEEE.
Liu, Y. and Zhou, G. (2012). Key technologies and applications of internet of things. pages 197 – 200, Zhangjiajie, Hunan, China. IEEE.
Molina-Markham, A., Peterson, R., Skinner, J., Yun, T., Golla, B., Freeman, K., Peters, T., Sorber, J., Halter, R., and Kotz, D. (2014). Amulet: a secure architecture for mhealth applications for low-power wearable devices. In Proceedings of the 1st Workshop on Mobile Medical Applications, pages 16–21. ACM.
Nguyen, L. N. N., Rodríguez-Martín, D., Català, A., Pérez-López, C., Samà, A., and Cavallaro, A. (2015). Basketball activity recognition using wearable inertial measurement units. In Proceedings of the XVI International Conference on Human Computer Interaction, page 60. ACM.
Pels, T., Kao, C., and Goel, S. (2014). Fatbelt: motivating behavior change through isomorphic feedback. In Proceedings of the adjunct publication of the 27th annual ACM symposium on User interface software and technology, pages 123–124. ACM.
Rocha, U., Oliveira, D., Carvalho, L., Moreira, L., and Viana, W. (2015). Heart wars: um exergame de batalha controlado por dispositivos vestıveis. In Anais do XV Workshop de Informática Médica (WIM), pages 1–10, Porto Alegre, RS, Brasil. SBC.
Salehizadeh, S., Noh, Y., and Chon, K. (2016). Heart rate monitoring during intense physical activities using a motion artifact corrupted signal reconstruction algorithm in wearable electrocardiogram sensor. In Connected Health: Applications, Systems and Engineering Technologies (CHASE), 2016 IEEE First International Conference on, pages 157–162. IEEE.
Spelmezan, D. (2012). An investigation into the use of tactile instructions in snowboarding. In Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services, pages 417–426. ACM.
Uddin, M., Salem, A., Nam, I., and Nadeem, T. (2015). Wearable sensing framework for human activity monitoring. In Proceedings of the 2015 workshop on Wearable Systems and Applications, pages 21–26. ACM.
Wang, K., Wang, Y., Sun, Y., Guo, S., and Wu, J. (2016). Green industrial internet of things architecture: an energy-efficient perspective. IEEE Communications Magazine, 49.
Publicado
22/07/2018
Como Citar
CACAIS, Michelle G.; MOREIRA, Leonardo O.; CALDAS, Weslley L.; GOMES, Danielo G..
ASAPe: uma Arquitetura para Sensoriamento Preditivo em Computação Vestível. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO UBÍQUA E PERVASIVA (SBCUP), 10. , 2018, Natal.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 151-160.
ISSN 2595-6183.
DOI: https://doi.org/10.5753/sbcup.2018.3297.
