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IJAT Vol.9 No.5 pp. 580-587
doi: 10.20965/ijat.2015.p0580
(2015)

Paper:

Detection of Human Position and Motion by Thermopile Infrared Sensor

Xipeng Zhang, Hiroaki Seki, and Masatoshi Hikizu

Graduate School of Natural Science and Technology, Kanazawa University
Kakuma-machi, Kanazawa, Ishikawa 920-1192, Japan

Received:
April 15, 2015
Accepted:
July 13, 2015
Published:
September 5, 2015
Keywords:
thermopile infrared sensor, human position, body orientation, steepest descent method
Abstract
Devices such as pyroelectric infrared sensors, ultrasonic sensors, cameras can be used to detect the presence of human-beings, but their systems have some problems related to low detection ability, low resolution, privacy, and high cost. We propose the use of thermopile infrared sensors without focus lenses and with high-gain amplifiers to detect the position and movement of human subjects. The system can detect even people that are not moving. This paper presents an approach that uses two thermopile sensors mounted on the ceiling to detect in 2D the position and orientation of human bodies. After each sensor takes measurements, we can build an approximate equation set that takes into account the output voltage, distance, and orientation of the human presence. The equation set can be solved, using the steepest descent method for the outputs of the two sensors, to obtain in real-time the position of a human-being in 2D. Body orientation can also be basically obtained by detecting slight changes in some positions while the human subject is moving. Tests are carried out to confirm that the proposed system works.
Cite this article as:
X. Zhang, H. Seki, and M. Hikizu, “Detection of Human Position and Motion by Thermopile Infrared Sensor,” Int. J. Automation Technol., Vol.9 No.5, pp. 580-587, 2015.
Data files:
References
  1. [1] H. K. Chan, W. Ye, T. L. Lam, Y. Ou, and Y. Xu, “Sensor system for a human-following robot,” Proc. of Int. Conf. on Automation, Control, and Applications, pp. 350-355, 2005.
  2. [2] S. Grange, E. Casanova, T. W. Fong, and C. Baur, “Vision-based sensor fusion for human-computer interaction,” Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2002.
  3. [3] A. Ohya, Y. Nagumo, and M. Takahata, “Intelligent escort robot moving together with Human-Human Following Behavior,” Proc. of 12th Int. Symp. On Measurement and Control in Robotics, 2002.
  4. [4] D. Cima, “Using Lithium Tantalate Pyroelectric Detectors in Robotics Applications,” Eltecdata #112, Eltec Instruments, Inc., 1984.
  5. [5] H. R. Everett, “Sensors for Mobile Robots, Theory and Application,” AK Peters, Ltd., 1995.
  6. [6] F. Bu and C. Y. Chan, “Pedestrian Detection in Transit Bus Application: Sensing Technology and Safety Solutions,” Proc. of IEEE Intelligent Vehicle Symp., pp. 100-105, 2005.
  7. [7] M. Shankar et al., “Human-tracking systems using pyroelectric infrared detectors,” Optical Engineering, Vol.45, No.10, pp. 106401-1-106401-10, 2006.
  8. [8] R. Bodor, B. Jackson, and N. Papanikolopoulos, “Vision-based human tracking and activity recognition,” Proc.11th Mediterranean Conf. on Control and Automation, 2003.
  9. [9] J. M. Holland, “An army of robots that roams the night,” Proc. of Int. Robot and Vision Automation Show, pp. 17.1-17.12, 1993.
  10. [10] C. Porras-Amores, F. R.Mazarr’on, and I. Cañas, “Using quantitative infrared thermography to determine indoor air temperature,” Energy and Buildings, Vol.65, pp. 292-298, 2013.
  11. [11] A. Püttmer, “New applications for ultrasonic sensors in process industries,” Ultrasonics, Vol.44, pp. 1379-1383, 2006.
  12. [12] J. Fraden, “Handbook of Modern Sensor: Physics, Designs, and Applications,” 3ed ed., American Institute of Physics, 2003.
  13. [13] L. F. Houlet et al., “Thermopile sensor devices for the catalytic detection of hydrogen gas,” Sensors and Actuators B: Chemical, Vol.130, Issue 1, pp. 200-206, 2008.
  14. [14] C. Leon et al., “Infrared ear thermometry in thecritically ill patient: An alternative to axillary thermometry,” J. of Critical Care, Vol.20, Issue 1, pp. 106-110, 2005.
  15. [15] S. O. AI-Mamory et al., “Intrusion detection alarms reduction using root cause analysis and clustering,” Computer Communications, Vol.32, Issue 2, pp. 419-430, 2009.
  16. [16] P. L. Schmidt et al., “Thermal measurements using ultrasonic acoustical pyrometry,” Ultrasonics, Vol.54, Issue 4, 2014.
  17. [17] J. Kemper and H. Linde, “Challenges of passive infrared indoor localization,” 5th Workshop on Positioning, Navigation and Communication, WPNC 2008, pp. 63-70, 2008.
  18. [18] J. Kemper and D. Hauschildt, “Passive infrared localization with a Probability Hypothesis Density filter,” IEEE 7th Workshop on Positioning Navigation and Communication, 2010.
  19. [19] D. Hauschildt and N. Kirchhof, “Improving indoor position estimation by combining active TDOA ultrasound and passive thermal infrared localization,” 8th Workshop on Positioning Navigation and Communication (WPNC), pp. 94-99, 2011.
  20. [20] D. Hauschildt and N. Kirchhof, “Advances in thermal infrared localization: Challenges and solutions,” IEEE Int. Conf. Indoor Positioning and Indoor Navigation, 2010.
  21. [21] T. J. Seebeck, “Magnetische Polarisation der Metalle und Erze durch Temperatur-Differenz,” Abh. D. pp. 265-373, 1822.
  22. [22] I. Montvay and E. Pietarinen, “The Stefan-Boltzmann law at high temperature for the gluon gas,” Physics Letters B, Vol.110, Issue 2, pp. 148-154, 1982.
  23. [23] L. M. G. Drummond and B. F. Svaiter, “A steepest descent method for vector optimization,” J. of Computational and Applied Mathematics, Vol.175, Issue 2, pp. 395-414, 2005.

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