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http://dx.doi.org/10.9728/dcs.2018.19.9.1779

Error Correction of Real-time Situation Recognition using Smart Device  

Kim, Tae Ho (Database/Bioinformatics Lab, School of Electrical & Computer Engineering, Chungbuk National University)
Suh, Dong Hyeok (Department of Display Engineering, Dankook University)
Yoon, Shin Sook (Department of Electronic, Namseoul University)
Ryu, KeunHo (Database/Bioinformatics Lab, School of Electrical & Computer Engineering, Chungbuk National University)
Publication Information
Journal of Digital Contents Society / v.19, no.9, 2018 , pp. 1779-1785 More about this Journal
Abstract
In this paper, we propose an error correction method to improve the accuracy of human activity recognition using sensor event data obtained by smart devices such as wearable and smartphone. In the context awareness through the smart device, errors inevitably occur in sensing the necessary context information due to the characteristics of the device, which degrades the prediction performance. In order to solve this problem, we apply Kalman filter's error correction algorithm to compensate the signal values obtained from 3-axis acceleration sensor of smart device. As a result, it was possible to effectively eliminate the error generated in the process of the data which is detected and reported by the 3-axis acceleration sensor constituting the time series data through the Kalman filter. It is expected that this research will improve the performance of the real-time context-aware system to be developed in the future.
Keywords
Context Aware; Smart Device; IoT; Error Correction; Real-Time Situation Inference;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 C. C. Aggarwal, N. Ashish, and A. Sheth, "The Internet of Things: a survey from the data-centric perspective", In C. C. Aggarwal (Ed.), Managing and Mining Sensor Data. Springer, Boston, pp. 383-428, 2013.
2 J. Attard, S. Scerri, I. Rivera, and S. Handschuh,"Ontology-based Situation Recognition for Context-Aware Systems", In Proceedings of the International Conference on Semantic Systems. Graz, Austria, pp. 113-120, 2013.
3 W. Dargie, E. Eldora, J. Mendez, C. Mobius, K. Rybina, V. Thost, and A. Turhan, "Situation Recognition for Service Management Systems Using OWL 2 Reasoners", In Proceedings of the IEEE Workshop on Context Modeling and Reasoning. San Diego, USA, pp. 31-36, 2013.
4 Technology Focus, pp.64-71, 2018. https://arx.appi.keio.ac.jp/wp-content/uploads/2018/01/test.pdf
5 H. J. Kwon, J. H. Lee, Y. K. Lee, J. W. Lee, S. W. Jung, and J. Kim, "Seasonal Variations of Evapotranspiration Observed in a Mixed forest in the Seolmacheon Catchment", Korean Society of Agricultural and Forest Meteorology, Vol. 11, Issue 1, pp.39-47, 2009.   DOI
6 C. S. Yoo, J. H. Hwang, and J. H. Kim, "Use of the Extended Kalman Filter for the Real-Time Quality Improvement of Runoff Data: 1. Algorithm Construction and Application to One Station", Journal of Korea Water Resources Association, pp.697-711, July. 2012,
7 S. C. Oh, M. H. Kim, and Y. H. Baek, "Development of a Freeway Travel Time Estimating and Forecasting Model using Traffic Volume", The Journal of Korean Socity of Transportation, Vol. 21, No. 5, pp.83-95, 2003.
8 Y. S. Park, "Approaching Target above Ground Tracking Technique Based on Noise Covariance Estimation Method-Kalman Filter", The Journal of Korean Institute of Electromagnetic Engineering and Science, Vol. 28, No. 10, pp.810-818, Oct. 2017.   DOI
9 J. S. Ha, J. E. Roh, J. H. Choi, H. J. Lee, and Y. S. Park , "Study on the Compact K-Band Radar for Detecting the Approaching Target above Ground", The Journal of Korea Institute of Electromagnetic Engineering And Science, Vol. 28, No. 4, pp. 309-317, Apr. 2017.   DOI
10 T. H. Jang, Y. S. Kim, M. Y. Kyoung, H. B. Yi, and Y. D. Hwan, "Kalman Filter-based Sensor Fusion for Posture Stabilization of a Mobile Robot", Trans. Korean Soc. Mech. Eng. A, Vol. 40, No. 8, pp. 703-710, 2016   DOI
11 B. M. Kim, J. W. Kim, and K. H. Lee, "An Application of AdaBoost Learning Algorithm and Kalman Filter to Hand Detection and Tracking", Journal of the Korea Society of Computer and Information, Vol. 10, No. 4, pp.47-56, 2005.