Smart LED lighting system implementation using human tracking US/IR sensor

Kim, Daeho; Lee, Junghoon; Jang, Yeong-Min; Cha, Jae-Sang

doi:10.1109/ictc.2011.6082600

Cited by 6 publications

(2 citation statements)

References 3 publications

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“…The optimal intensity and color are calculated by incorporating the illuminance feedback from a portable, photosensitive device [1]. The estimated human location using ultra sonic sensors or IR sensors is used to control the LED lighting ON/OFF cycle [3]. Although required lighting condition varies according to the activity [5], it is difficult to estimate accurate location, movement trajectories, and the number of people in the space under an illumination change.…”

Section: Introductionmentioning

confidence: 99%

Applications of Human Motion Tracking: Smart Lighting Control

Chun

Lee

2013

2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops

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This paper presents a smart lighting control system based on human motion tracking. Proper illumination and color temperature depend on human activities. A smart lighting system that provides automatic control of lighting illumination and color temperature needs to track human motion and understand human activities. Infrared and thermal spectrum provides useful information robust to the lighting condition. Depth information can be acquired independently of the lighting condition and it is relatively easy to detect humans independent of their clothing, and skin color. Commercial depth cameras or thermal cameras were used for accurate tracking and for estimating human behavior. The activity modes can be estimated using the human motion tracking results from depth cameras and from thermal cameras. Multiple depth cameras were used to detect human subject motion in a large area. The activity modes such as study mode and watching TV mode were estimated and the illumination and color temperature of the LED lighting system were controlled in real time according to the estimated activity.

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Section: Introductionmentioning

confidence: 99%