Dynamic Vision Sensor Based High Efficiency Device Control
B. Praveena1, H. Shravani2, A. Shivani3
1B. Praveena, Assistant Professor, Department of Computer Science and Engineering, RMK Engineering College, Chennai (Tamil Nadu), India.
2H. Shravani, Department of Computer Science and Engineering, RMK Engineering College, Chennai (Tamil Nadu), India.
3A. Shivani, Department of Computer Science and Engineering, RMK Engineering College, Chennai (Tamil Nadu), India.
Manuscript received on 24 November 2019 | Revised Manuscript received on 05 December 2019 | Manuscript Published on 14 December 2019 | PP: 245-248 | Volume-9 Issue-1S November 2019 | Retrieval Number: A10501191S19/2019©BEIESP | DOI: 10.35940/ijitee.A1050.1191S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: To control a specific device hardware switches and gesture based controls are usually used. There are some inconveniences involved in these controlling mechanism aging problem, safety related issues, high replacement cost in hardware switches and the impact of external noise in case of gesture based control. And in order to overcome these issues a new device control mechanism is brought up using two dimensional hologram and dynamic vision sensor. This involves reduced hardware usage and if needed, the controlling unit can be replaced easily. It possesses high processing efficiency and speed. The light source used in hologram processing unit is LED and it contributes less power consumption. The conventional proximity sensors are replaced by Dynamic vision sensor because the conventional sensors process series of frames continuously which is inefficient because it contains redundant information, wasting energy computational power and time. This drawback is eliminated by using DVS which starts to process the frames only when any change is sensed only at the time the change occurs. Proximity sensors are more prone to external noise whereas DVS is not. It has high signal to noise ratio.
Keywords: DVS; FDAPA; UART; CSMA; PSNR; Human Machine Interface; S-MAC.
Scope of the Article: Computer Vision