IoT Based Real Time Road Traffic Monitoring and Tracking System for Hilly Regions
Harvinder Singh1, Dharani Kumar Talapula2, Alind3
1Harvinder Singh, Department of Virtualization, School of Computer Science, University of Petroleum and Energy Studies, Dehradun (Uttarakhand), India
2Dharani Kumar Talapula, Department of Virtualization, School of Computer Science, University of Petroleum and Energy Studies, Dehradun (Uttarakhand), India
3Alind, Department of Virtualization, School of Computer Science, University of Petroleum and Energy Studies, Dehradun (Uttarakhand), India
Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 2199-2205 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7447068519/19©BEIESP
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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: Nowadays, the occurrence of road accidents (typically two-wheeler) in hilly terrains is increasing at an alarming rate. Apart from the bad driving skills, the reason for accidents being terrain-based issues like the number of blind turns, elevated U-turns, poor lighting (absence of street lighting) and lack of supportive gear. Though the road conditions are conducive and modernized due to fast urbanization, population growth and development of various living spaces and reachability of transportation facilities for farthest corners, the serious issues of human loss due to accidents still happening has captured the attention of modern researchers and are coming up with technical solutions that can reduce or avoid the accident occurrences in these terrains. Hence, a system is required, which should be capable of addressing such situations. The paper proposes an IOT based accident prevention unit (APU), as a solution for the stated problem. The recommended APU is deployed and tested on the parameters like the number of accidents, helmet defaulters and average response time in hilly terrains of northern India. Over the period of two years, it is observed that the suggested unit in the paper has successfully assisted in reducing the accidents and reduction in helmet defaulters significantly.
Keywords: Raspberry Pi, Pir Movement Sensor, Accident Prevention Unit (Apu).
Scope of the Article: IoT