Abstract
With advances in technologies, environments and human habitats are all set to become smarter. Such environments, which include smart homes, hospitals, campuses, etc., are oriented towards human comfort and safety. Detecting the presence of a human being in spaces within such environment forms a major challenge. Though there are sensors that can perform this task, they are not without limitations. Using information derived from either single or multiple sensors separately is not sufficient to distinguish human beings from other objects within the environment. Reliable detection of human presence can be achieved only by fusing information obtained from multiple sensors. In this paper, we describe an approach to human presence detection using a combination of PIR and ultrasonic sensors. Analysis is performed based on the received raw signals from the PIR as well as an analog ultrasonic sensor. A voting based approach has been used to classify signals obtained from human beings and non-human objects, thereby facilitating human presence detection. Results obtained from indoor experiments performed using this approach substantiate the viability of its use in real environments.
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References
Akhoundi, M.A.A., Valavi, E.: Multi-sensor fuzzy data fusion using sensors with different characteristics. CoRR abs/1010.6096 (2010). http://arxiv.org/abs/1010.6096
Bai, Y.W., Cheng, C.C., Xie, Z.L.: Use of a time-variation ultrasonic signal and pir sensors to enhance the sensing reliability of an embedded surveillance system. In: 2013 26th Annual IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1–6, May 2013
Bai, Y.W., Cheng, C.C., Xie, Z.L.: Use of ultrasonic signal coding and pir sensors to enhance the sensing reliability of an embedded surveillance system. In: 2013 IEEE International Systems Conference (SysCon), pp. 287–291, April 2013
Can, G.N., akr, B., Naml, A.T., Dutaac, H.: Detection of humans from depth images. In: 2016 24th Signal Processing and Communication Application Conference (SIU), pp. 1477–1480, May 2016
Chen, Y., Rui, Y.: Real-time speaker tracking using particle filter sensor fusion. Proc. IEEE 92(3), 485–494 (2004)
Damarla, R., Ufford, D.: Personnel detection using ground sensors (2007). http://dx.doi.org/10.1117/12.723212
Dong, B., Andrews, B.: Sensor-based occupancy behavioral pattern recognition for energy and comfort management in intelligent buildings. In: Proceedings of Building Simulation, pp. 1444–1451 (2009)
Feng, G., Liu, M., Guo, X., Zhang, J., Wang, G.: Genetic algorithm based optimal placement of pir sensor arrays for human localization. In: 2011 IEEE International Conference on Mechatronics and Automation, pp. 1080–1084, August 2011
Flores, S., Gei, J., Vossiek, M.: An ultrasonic sensor network for high-quality range-bearing-based indoor positioning. In: 2016 IEEE/ION Position, Location and Navigation Symposium (PLANS), pp. 572–576, April 2016
Gao, G., Zhang, Y., Zhu, Y., Duan, G.: Data fusion and multi-fault classification based on support vector machines. Vectors 3(4), 5 (2006)
Georgescu, B., Shimshoni, I., Meer, P.: Mean shift based clustering in high dimensions: a texture classification example. In: Ninth IEEE International Conference on Computer Vision 2003, Proceedings, vol.1, pp. 456–463, October 2003
Gilmore, E.T., Frazier, P.D., Chouikha, M.: Improved human detection using image fusion. In: Proceedings of the IEEE ICRA 2009 Workshop on People Detection and Tracking, Kobe, Japan (2009)
Hondori, H.M., Khademi, M., Lopes, C.V.: Monitoring intake gestures using sensor fusion (microsoft kinect and inertial sensors) for smart home tele-rehab setting. In: 2012 1st Annual IEEE Healthcare Innovation Conference (2012)
Lim, M., Choi, J., Kim, D., Park, S.: A smart medication prompting system and context reasoning in home environments. In: Fourth International Conference on Networked Computing and Advanced Information Management, NCM 2008, vol. 1, pp. 115–118, September 2008
Machida, E., Cao, M., Murao, T., Hashimoto, H.: Human motion tracking of mobile robot with kinect 3D sensor. In: 2012 Proceedings of SICE Annual Conference (SICE), pp. 2207–2211, August 2012
Maslov, I.V., Gertner, I.: Multi-sensor fusion: an evolutionary algorithm approach. Inf. Fusion 7(3), 304–330 (2006)
Moghavvemi, M., Seng, L.C.: Pyroelectric infrared sensor for intruder detection. In: 2004 IEEE Region 10 Conference TENCON 2004, vol. D, pp. 656–659, November 2004. (vol. 4)
Murphy, R.R.: Dempster-shafer theory for sensor fusion in autonomous mobile robots. IEEE Trans. Robot. Autom. 14(2), 197–206 (1998)
Nadee, C., Chamnongthai, K.: Multi sensor system for automatic fall detection. In: 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), pp. 930–933, December 2015
Nakamura, K., Zhao, H., Shibasaki, R., Shao, X.: Human sensing in crowd using laser scanners. INTECH Open Access Publisher (2012)
Park, J.T., Song, J.B.: Sensor fusion-based exploration in home environments using information, driving and localization gains. Appl. Soft Comput. 36(C), 70–86 (2015). http://dx.doi.org/10.1016/j.asoc.2015.07.013
Politis, D.N., Romano, J.P.: Multivariate density estimation with general flat-top kernels of infinite order. J. Multivar. Anal. 68(1), 1–25 (1999)
Sasiadek, J.Z.: Sensor fusion. Ann. Rev. Control 26(2), 203–228 (2002)
Sidibe, Y., Druaux, F., Lefebvre, D., Leon, F., Maze, G.: Active fault diagnosis for immersed structure. In: 2013 International Conference on Control, Decision and Information Technologies (CoDIT), pp. 071–075, May 2013
Song, B., Choi, H., Lee, H.S.: Surveillance tracking system using passive infrared motion sensors in wireless sensor network. In: 2008 International Conference on Information Networking, pp. 1–5, January 2008
Sonia, T., A.M., Baruah, R.D., Nair, S.B.: Ultrasonic sensor-based human detector using one-class classifiers. In: 2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), pp. 1–6, December 2015
Soyer, E.B.: Pyroelectric infrared (PIR) sensor based event detection. Ph.D. thesis, bIlkent university (2009)
Teixeira, T., Dublon, G., Savvides, A.: A survey of human-sensing: methods for detecting presence, count, location, track, and identity. ENALAB Technical report (2011)
Xu, Y., Wang, J.Y., Cao, B.X., Yang, J.: Multi sensors based ultrasonic human face identification: experiment and analysis. In: IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pp. 257–261, September 2012
Yazar, A., Erden, F., Cetin, A.E.: Multi-sensor ambient assisted living system for fall detection. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP14), pp. 1–3. Citeseer (2014)
Zigel, Y., Litvak, D., Gannot, I.: A method for automatic fall detection of elderly people using floor vibrations and sound - proof of concept on human mimicking doll falls. IEEE Trans. Biomed. Eng. 56(12), 2858–2867 (2009)
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Sonia, Singh, M., Baruah, R.D., Nair, S.B. (2017). A Voting-Based Sensor Fusion Approach for Human Presence Detection. In: Basu, A., Das, S., Horain, P., Bhattacharya, S. (eds) Intelligent Human Computer Interaction. IHCI 2016. Lecture Notes in Computer Science(), vol 10127. Springer, Cham. https://doi.org/10.1007/978-3-319-52503-7_16
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DOI: https://doi.org/10.1007/978-3-319-52503-7_16
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