A Framework for Enhancing the Security of Motorbike Riders in Real Time

Khandelwal, Yash; Anwar, Sajid; Agarwal, Sudhir; Tripathi, Vikas; Pandey, Priyank

doi:10.1007/978-981-15-2780-7_32

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…While meeting real-time criteria, challenges persist in deployment on embedded platforms. Proposing a methodology for motorbike rider detection with and without helmets, the paper [24] trains two models using Faster R-CNN with the Inception V2 model, achieving 93.37% accuracy overall. However, the fps is not discussed, suggesting potential difficulties in real-time operation and deployment on embedded platforms.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Motorbike Detection: AI on the Edge Perspective

Akhtar,

Ahmed,

Yousaf

et al. 2024

Mathematics

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Motorbikes are an integral part of transportation in emerging countries, but unfortunately, motorbike users are also one the most vulnerable road users (VRUs) and are engaged in a large number of yearly accidents. So, motorbike detection is very important for proper traffic surveillance, road safety, and security. Most of the work related to bike detection has been carried out to improve accuracy. If this task is not performed in real-time then it loses practical significance, but little to none has been reported for its real-time implementation. In this work, we have looked at multiple real-time deployable cost-efficient solutions for motorbike detection using various state-of-the-art embedded edge devices. This paper discusses an investigation of a proposed methodology on five different embedded devices that include Jetson Nano, Jetson TX2, Jetson Xavier, Intel Compute Stick, and Coral Dev Board. Running the highly compute-intensive object detection model on edge devices (in real-time) is made possible by optimization. As a result, we have achieved inference rates on different devices that are twice as high as GPUs, with only a marginal drop in accuracy. Secondly, the baseline accuracy of motorbike detection has been improved by developing a custom network based on YoloV5 by introducing sparsity and depth reduction. Dataset augmentation has been applied at both image and object levels to enhance robustness of detection. We have achieved 99% accuracy as compared to the previously reported 97% accuracy, with better FPS. Additionally, we have provided a performance comparison of motorbike detection on the different embedded edge devices, for practical implementation.

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Section: Related Workmentioning

confidence: 99%

Real-Time Motorbike Detection: AI on the Edge Perspective

Akhtar,

Ahmed,

Yousaf

et al. 2024

Mathematics

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“…Most motorized vehicles in Indonesia today are two-wheeled vehicles, which account for 82% of the total population (bps.go.id). The high number of motorbike users is often not conducted by awareness to maintain motorbike [1]. We frequently encounter motorbikes by their ages that strike on the streets [2].…”

Section: Introductionmentioning

confidence: 99%

Prototype Development of Motorbike Towing Hook Towards Authorized Mechanic Perception and Investigation

Hakim¹,

Albana²,

Widodo³

et al. 2021

Atlantis Highlights in Engineering

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The research aims to find the authorized mechanic perception of the towing hook's development to lay at the motorbike's front section. A prototype invention of a motorbike towing hook was found in 2018. However, it has never been tested for function by an official motorbike dealer in Batam. The research method used is quantitative research by analyzing questionnaire data, which is processed by SPSS. The mechanical data population was 18 people with Slovin's method, a proportional random sample of 17 samples. The analysis method for testing the validity (Bivariate Pearson) and reliability (Alpha Cronbach) was carried out to obtain the desired questionnaire data. Based on the calculation data, the validity value of rpearson = 0.701 is valid. In contrast, the calculation results of the reliability test are the results of rac = 0.864 with a sufficient level of reliability. The investigation data based on the perception method are valid and reliable. Therefore, this invention still requires improvements from design to manufacture before being mass-produced.

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A Framework for Enhancing the Security of Motorbike Riders in Real Time

Cited by 2 publications

References 11 publications

Real-Time Motorbike Detection: AI on the Edge Perspective

Real-Time Motorbike Detection: AI on the Edge Perspective

Prototype Development of Motorbike Towing Hook Towards Authorized Mechanic Perception and Investigation

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