Advanced Drowsiness Detection Systems Based on Human Activities and Videos
Garv Modwel1, Anu Mehra2, Nitin Rakesh3, K K Mishra4
1Garv Modwel, Department of CSE, Amity University, Noida (Uttar Pradesh), India.
2Anu Mehra, Department of ECE, Amity University, Noida (Uttar Pradesh), India.
3Nitin Rakesh, Department of CSE, Sharda University, G. Noida (Uttar Pradesh), India.
4K K Mishra, Department of CSE, MNNIT, Allahabad (Uttar Pradesh), India.
Manuscript received on 05 May 2019 | Revised Manuscript received on 12 May 2019 | Manuscript published on 30 May 2019 | PP: 563-575 | Volume-8 Issue-7, May 2019 | Retrieval Number: G5417058719/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Drowsiness and lack of attention in driving are main two reasons for any road accident. So far several approaches like face recognition, measurement of human body using wrist band, measuring heart beat and others are defined to detect these kinds of situations to avoid such accidents. All these approaches need some forceful/peripheral attachment with/on driver to do so other than these approaches other solutions are having various limitations in functionalities. In case of solutions using face detection, it is difficult to get the face impression during night or in dark/dull light when maximum chances of accidents are suggestive. On the other hand, with solutions using wristband, drivers have to wear wristband while driving, similarly there are several methods where drivers need to wear some headband or external device. In this manuscript, we have proposed a comprehensive and experimented solution for drowsiness problem. Our approach is sovereign of any device/external gadget dependency. Proposed approach introduces the algorithmic solution to detect the sleeping behavior of a driver with existing parameters and will generate alert for the driver and vehicles near the vehicle driver suffering from drowsiness or lack of attention. The proposed approach is tested over more than 180 test cases with efficacious results.
Keyword: Automotive Safety in Automotive, Drowsiness, Car-to-car Communication, Driver behavior Dissemination, Driver Fatigue Detection, Driver Inattention Monitoring, Wearable Devices.
Scope of the Article: Inattention Monitoring