Camera Based Occupancy Detection and Lighting Control

  • Authors

    • Vedavyasa Kamath
    • Suprabha Padiyar U.
    • Sudipto Bhattacharjee
    • Sai Charan Reddy Nayini
    2018-12-19
    https://doi.org/10.14419/ijet.v7i4.41.24530
  • Computer vision, lighting control, MATLAB, occupancy detection, raspberry pi, wireless control
  • Artificial lighting accounts for a substantial percentage of total electricity consumption in commercial and residential complexes. It is prudent to make lighting systems as efficient as possible in order to reduce consumption of electricity, which, being largely dependent on fast-depleting fossil fuel reserves, severely impacts the availability and security of resources available to future generations. One aspect of energy conservation involves developing efficient luminaires. However, the untapped potential lies in better methods of lighting control. It is necessary to shift from traditional switch-based control to intelligent controls, which minimizes human effort, while improving accuracy and savings. This paper presents a camera based lighting control system, which detects human occupancy in the control zones and controls the luminaires accordingly.

     

     

     
  • References

    1. [1] Yong Sam Kim, Jin II Park, Dae Jong Lee, Myung Geun Chun, “Real time detection of moving human based on digital image processingâ€, SICE Annual Conference 2007, pages 2030-2-33, September 2007

      [2] Chakravartula Raghavachari, V. Aparna, S. Chithira, Vidhya Balasubramanian, “A comparative study of vision based human detection techniques in people counting applicationsâ€, Procedia Computer Science, Vol. 58, pages 461-169, August 2015

      [3] Manoranjan Paul, Shah M. E. Haque, Subrata Chakraborty, “Human detection in surveillance videos and its applications – a reviewâ€, EURASIP Journal on Advances in Signal Processing, 2013: 176, November 2013

      [4] M. Hussein, W. Abd-almageed, Yang Ran, L. Davis, “Real-Time Human Detection, Tracking, and Verification in Uncontrolled Camera Motion Environmentsâ€, 4th IEEE International Conference on Computer Vision Systems (ICVS 06), March 2006

      [5] Alok K. Singh Kushwaha, Chandra Mani Sharma, Manish Khare, Rajneesh Kumar Srivastava, Ashish Khare, "Automatic multiple human detection and tracking for visual surveillance system", 2012 International Conference on Informatics, Electronics & Vision (ICIEV), pages 326-331, May 2012

      [6] Susan G. Varghese, Ciji Pearl Kurian, V. I. George, “Image based wireless networked lighting control for daylight-artificial light integrated schemeâ€, International Journal of Computer Science and Electronics Engineering (IJCSEE), Vol. 1, Issue 2, 2013

      [7] Panth Shah, Tithi Vyas, “­Interfacing of MATLAB with Arduino for Object Detection Algorithm Implementation using Serial Communicationâ€, International Journal of Engineering Research & Technology (IJERT), Vol. 3, Issue 10, October 2014

      [8] Yan-Fang Li, S. Harari, Hong Wong, and V. Kapila, “MATLAB-based graphical user interface development for Basic Stamp 2 microcontroller projectsâ€, Proceedings of the 2004 American Control Conference, vol. 4, pages 3233-3238, June 2004

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  • How to Cite

    Kamath, V., Padiyar U., S., Bhattacharjee, S., & Charan Reddy Nayini, S. (2018). Camera Based Occupancy Detection and Lighting Control. International Journal of Engineering & Technology, 7(4.41), 211-214. https://doi.org/10.14419/ijet.v7i4.41.24530