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Smartphone-Based Intelligent Driver Assistant: Context Model and Dangerous State Recognition Scheme

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1038)

Abstract

The paper proposes the context model and the dangerous state recognition scheme for intelligent driver assistant system. The system is aimed at utilization of smartphone’s front-facing camera and other sensors for dangerous states reignition to prevent emergency and reduce the accidents probability. The proposed context model is divided into following types of contexts, driver context, vehicle context, road context, and environment context. The model shows how the smartphone front-facing camera and sensors as soon as accessible Internet services are used to support the proposed context types. Then, the context-based dangerous state recognition model is presented. The model calculates the computational power of the smartphone and based on this information implements the frame skipping algorithm to reduce the computation complexity for the smartphone processor. The implementation of the proposed frame skipping model shows that for the modern smartphones the complexity is decreased by three times in compare with usual scheme. The proposed context model and dangerous state recognition scheme has been implemented in Drive Safely system that is available in Google Play.

Keywords

  • Context-aware driver assistant
  • Dangerous state
  • Context
  • Smartphone
  • Vehicle
  • Driver

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  • DOI: 10.1007/978-3-030-29513-4_11
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Notes

  1. 1.

    https://play.google.com/store/apps/details?id=ru.igla.drivesafely.

  2. 2.

    https://kotlinlang.org/.

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Acknowledgments

The research is funded by the Russian Science Foundation (project # 18-71-10065).

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Correspondence to Igor Lashkov .

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Lashkov, I., Kashevnik, A. (2020). Smartphone-Based Intelligent Driver Assistant: Context Model and Dangerous State Recognition Scheme. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1038. Springer, Cham. https://doi.org/10.1007/978-3-030-29513-4_11

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