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Machine Learning Recognition Mechanism Based on WI-FI Signal Optimization in the Detection of Driver’s Emotional Fluctuations

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Proceedings of International Conference on Recent Innovations in Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1001))

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Abstract

With the development of the automobile industry, the use of vehicles has become the most basic means of transportation in people’s daily life. However, due to the rapid increase in the number of vehicles, more and more drivers are causing traffic accidents due to emotional fluctuations during driving. In order to reduce the occurrence of this problem, the artificial intelligence machine learning mechanism under Industry 4.0 technology can currently capture and detect the instantaneous facial emotions of drivers during driving. Through the literature survey, it is found that in the machine learning mode, the existing mechanism mainly relies on human vision and biological signals sensors to identify the driver’s emotional fluctuations during driving. However, due to the frequent distortion of visual detection methods and the problems of invasiveness and privacy invasion of biological signals, the investment cost is relatively high. In order to solve the problems under the existing algorithm, this paper firstly formulates the corresponding emotional fluctuation recognition model according to the existing WI-FI signal detection principle and designs the antenna position according to the Fresnel zone to achieve the best signal acquisition effect. In addition, the driver’s action status while using the brake and accelerator is collected. The emotion recognition coefficient is calculated by the collected data, and the fluctuation recognition is performed by using the recognition wash and LSTM emotion discriminator. Finally, according to the evaluation data, the recognition rate of about 85% in the real scene is achieved.

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Authors and Affiliations

  1. Nanchang Institute of Science & Technology, Nanchang, China

    Zhu Jinnuo

  2. City University, Petaling Jaya, Malaysia

    Zhu Jinnuo & S. B. Goyal

Authors
  1. Zhu Jinnuo
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  2. S. B. Goyal
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Corresponding author

Correspondence to S. B. Goyal .

Editor information

Editors and Affiliations

  1. Computer Science and IT Department, Central University of Jammu, Jammu, Jammu and Kashmir, India

    Yashwant Singh

  2. Department of Computer Science, KIET Group of Institutions, Ghaziabad, Uttar Pradesh, India

    Pradeep Kumar Singh

  3. Department of Electrical Engineering, Indian Institute of Technology Patna, Patna, Bihar, India

    Maheshkumar H. Kolekar

  4. School of Artificial Intelligence, Indian Institute of Technology Delhi, New Delhi, Delhi, India

    Arpan Kumar Kar

  5. IDMEC, Polytechnic Institute of Castelo Branco, Castelo Branco, Portugal

    Paulo J. Sequeira Gonçalves

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Jinnuo, Z., Goyal, S.B. (2023). Machine Learning Recognition Mechanism Based on WI-FI Signal Optimization in the Detection of Driver’s Emotional Fluctuations. In: Singh, Y., Singh, P.K., Kolekar, M.H., Kar, A.K., Gonçalves, P.J.S. (eds) Proceedings of International Conference on Recent Innovations in Computing. Lecture Notes in Electrical Engineering, vol 1001. Springer, Singapore. https://doi.org/10.1007/978-981-19-9876-8_32

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