Abstract
The advances in multiple types of sensing technology, wireless communication, and context-aware services increase interest in the design and development of pedestrian behavior for hazard detection. This paper focuses on research of the hybrid sensing fusion approach that identifies behavior activities and provides behavior-aware alerts for safety to pedestrians. Hybrid sensing techniques use to integrate data gathered from several sensors and increase the reliability of the algorithm for identifying various activities. The main purpose of this paper is to present the overview of hybrid sensing and behavior-aware to apply for the pedestrian hazard detection.
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References
Tong, L., Song, Q., Ge, Y., Liu, M.: HMM-based human fall detection and prediction method using tri-axial accelerometer. IEEE Sens. J. 13(5), 1849–1856 (2013)
Aziza, O., Parkc, E.J., Morid, G., Robinovitch, S.N.: Distinguishing the causes of falls in humans using an array of wearable tri-axial accelerometers. Gait Posture 39, 506–512 (2014)
Bogomolov, A., Lepri, B., Pianesi, F.: Happiness recognition from mobile phone data. In: BioMedCom 2013 (2013)
LiKamWa, R., Liu, Y., Lane, N.D., Zhong, L.: Can your smartphone infer your mood? In: PhoneSense Workshop (2011)
Chittaranjan, G., Blom, J., Gatica-Perez, D.: Mining large-scale smartphone data for personality studies. Pers. Ubiquitous Comput. 17(3), 433–450 (2013)
Singh, V.K., Freeman, L., Lepri, B., Pentland, A.: Predicting spending behavior using socio-mobile features. In: BioMedCom 2013 (2013)
Faetti, T., Paradiso, R.: A novel wearable system for elderly monitoring. Adv. Sci. Technol. 85, 17–22 (2013)
Pierleoni, P., Pernini, L., Belli, A., Palma, L.: An android-based heart monitoring system for the elderly and for patients with heart disease. Int. J. Telemed. Appl. 2014, 11 (2014)
Zhou, P., Zheng, Y., Li, M.: How long to wait? Predicting bus arrival time with mobile phone based participatory sensing. In: MobiSys 2012 Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services (2012)
Hoang, T., Nguyen, T., Luong, C., Do, S., Deokjai, C.: Adaptive cross-device gait recognition using a mobile accelerometer. J. Inf. Process. Syst. 9(2), 333 (2013)
Hall, L., Llinas, J.: An introduction to multisensor data fusion. Proc. IEEE 85, 6–23 (1997)
Pohl, C., Van Genderen, J.L.: Multisensor image fusion in remote sensing: concepts, methods and applications. Int. J. Remote Sens. 19, 823–854 (1998)
Ayu, M., Mantoro, T., Fariadi, A., Basamh, S.: Recognizing user activity based on accelerometer data from a mobile phone. In: 2011 IEEE Symposium on Computers & Informatics (ISCI), Kuala Lumpur (2011)
Galvan-Tejada, C., Carrasco-Jimenez, J., Branea, R.: Location identification using a magnetic-field-based FFT signature. In: The 4th International Conference on Ambient Systems, Networks and Technologies (2013)
Enzweiler, M., Gavrila, D.M.: Monocular pedestrian detection: survey and experiments. IEEE Trans. Pattern Anal. Mach. Intell. 31(12), 2179–2195 (2009)
Geronimo, D., Lopez, A.M., Sappa, A.D., Graf, T.: Survey of pedestrian detection for advanced driver assistance systems. IEEE Trans. Pattern Anal. Mach. Intell. 32(7), 1239–1258 (2010)
https://developer.android.com/guide/topics/sensors/sensors_overview.html
Acknowledgments
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (2017-0-00336, Platform Development of Multi-log based Multi-Modal Data Convergence Analysis and Situational Response). This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2017-2016-0-00311) supervised by the IITP(Institute for Information & communications Technology Promotion).
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Kim, S., Yoon, Y. (2018). Hybrid Sensing and Behavior-Aware in Pedestrian Hazard Detection. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_178
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DOI: https://doi.org/10.1007/978-981-10-7605-3_178
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