Multimodal Sensor Fusion for Indoor Occupancy Determination

Abstract:

Pyroelectric infrared (PIR) sensors can detect the presence of human without the need to carry any device, which are widely used for human presence detection in home/office automation systems in order to improve energy efficiency. However, PIR detection is based on the movement of occupants. For occupancy detection, PIR sensors have inherent limitation when occupants remain relatively still. Multisensor fusion technology takes advantage of redundant, complementary, or more timely information from different modal sensors, which is considered an effective approach for solving the uncertainty and unreliability problems of sensing. In this paper, we proposed a simple multimodal sensor fusion algorithm, which is very suitable to be manipulated by the sensor nodes of wireless sensor networks. The inference algorithm was evaluated for the sensor detection accuracy and compared to the multisensor fusion using dynamic Bayesian networks. The experimental results showed that a detection accuracy of 97% in room occupancy can be achieved. The accuracy of occupancy detection is very close to that of the dynamic Bayesian networks.

• Periodical: Applied Mechanics and Materials (Volumes 764-765)
• Pages: 1319-1323
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.764-765.1319
• Online since: May 2015
• Authors: Rong Shue Hsiao*, Ding Bing Lin, Hsin Piao Lin, Jin Wang Zhou
• Keywords: Occupancy Detection, Sensor Fusion, Wireless Sensor Network (WSN)

References

[1] S. Lee, K.N. Ha and K.C. Lee: IEEE Trans. Consum. Electron. Vol. 52 (2006), p.1311.

[2] K. Cram: IBA Supplement to EngineerIT (2009), p.22.

[3] X. Guo, D. Tiller, G. Henze and C. Waters: Lighting Research and Technology Vol. 42 (2010), p.415.

[4] R.S. Hsiao, D.B. Lin, H.P. Lin, S.C. Cheng and C.H. Chung: Applied Mechanics and Materials Vol. 284-287 (2013), p. (2015).

[5] D.L. Hall and J. Llinas: Proc. of the IEEE Vol. 85 (1997), p.6.

[6] R.C. Luo, C. Yih and K.L. Su: IEEE Sensors J. Vol. 2 (2002), p.107.

[7] N. Xiong and P. Svensson: Information Fusion Vol. 3 (2002), p.163.

[8] E.F. Nakamura, A.A.F. Loureiro and A.C. Frery: ACM Computing Surveys Vol. 39 (2007), Article 9.

[9] E. Waltz and J. Llinas: Multisensor data fusion (Artech House, Boston 1990).

[10] Y. Zhang and Q. Ji: IEEE Trans. Syst., Man, Cybern. B, Cybern. Vol. 36 (2006), p.467.

[11] T. Dean and K. Kanazawa: Comput. Intell. Vol. 5 (1989), p.142.

[12] A. Singhal and C.R. Brown, in: Sensor Fusion and Decentralized Control in Autonomous Robotic Systems, edited by P.S. Schenker and G.T. McKee, volume 3209, SPIE (1997).

DOI: 10.1117/12.287628

[13] T. Damarla, in: Sensor Fusion and its Application, edited by C. Thomas, chapter, 8, Sciyo (2010).