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Third-Eye Two Wheeler for Accident Detection with Micro Electro Mechanical System (MEMS) Enabled in Smart Helmet
V. Vani1, M. Mohana2, S. Haritha Meenashi3, G. Jeevitha4, A. Keerthika5
1Dr. V. Vani, Associate Professor, Department of Information Technology, Easwari Engineering College, Ramapuram, Chennai, India.
2Dr.M.Mohana, Associate Professor, Department of Information Technology, Easwari Engineering College, Ramapuram, Chennai, India.
3S.Haritha Meenashi, B.Tech Information Technology , Easwari Engineering College, Ramapuram, Chennai, India.
4G.Jeevitha, B.Tech Information Technology , Easwari Engineering College, Ramapuram, Chennai, India.
5A.Keerthika, B.Tech Information Technology , Easwari Engineering College, Ramapuram, Chennai, India.

Manuscript received on November 11, 2019. | Revised Manuscript received on November 20 2019. | Manuscript published on 30 November, 2019. | PP: 10744-10747 | Volume-8 Issue-4, November 2019. | Retrieval Number: D4342118419/2019©BEIESP | DOI: 10.35940/ijrte.D4342.118419

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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: There are many accidents occurring in the world today. By wearing helmet and driving properly we can control or reduce the impact of these accidents. Thus, arises the need of Smart helmet which will protect the riders as well as help them to drive in a secure way. The Smart helmet consists of a ZigBee device through which the rider can start a bike only if he wears his helmet. It consists of various sensors which helps to detect the level of alcohol consumed by the vehicle rider, vibration sensor which detects the hit percentage when the rider meets with an accident and immediately report it to the nearby ambulance and the rider’s family members and friends. There is a capacity sensor with which only two people allowed to travel in the bike as it can detects the weight of the persons. All the sensors are interfaced through PIC board and it uses Internet Of Things through which if the rider travel at over speed, then automatically fine is debited from their account. For tracking the closest nearby ambulance we use KNN (K-Nearest Neighbour) Algorithm.
Keywords: KNN,PIC Board, IOT, Zig Bee, Sensors.
Scope of the Article: Network Performance; Protocols; Sensors.