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WiFi-based Vehicle Security System for Future Intelligent Transportation Systems

Year 2024, , 493 - 505, 31.12.2024
https://doi.org/10.30939/ijastech..1431379

Abstract

With the rapid maturation in automotive industry, intelligent sensing has been emerged as a vital research field for fast paced future intelligent transportation system. After the progressive integration of advanced driver assistance system and the rapid growth in next generation Internet of Vehicles (IoV), diver’s identification constitutes an indispensable aspect for the authorization in next generation internet-connected smart vehicles. Real-time driver identification is crucial in next generation smart vehicles. The presented solution is based on channel state information (CSI) of WiFi signals. In this proposed framework, an innovative WiFi- based low cost driver identification system is proposed which can recognize driver with good accuracy and less computational burden. The core idea is based on analyzing the steering wheel maneuver, exploiting CSI of WiFi signal. In the era of advanced information and communication in intelligent transportation system, this driver identification system may incorporate various intelligent means that are beneficial in many applications including safety, security, fleet management, ride hailing, insurance telematics, and customized vehicles. The proposed framework can recognize the activities with an average accuracy of 92.5% and identification with an average accuracy of 91.8%.

References

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Year 2024, , 493 - 505, 31.12.2024
https://doi.org/10.30939/ijastech..1431379

Abstract

References

  • [1] Azadani MN, Boukerche A. Driverrep: Driver identification through driving behavior embeddings. Journal of Parallel and Distributed Computing. 2022;162:105-17. https://doi.org/10.1016/j.jpdc.2022.01.010
  • [2] Choi GH, Lim K, Pan SB. Identification system based on resolution adjusted 2D spectrogram of driver’s ECG for intelligent vehicle. Mobile Information Systems. 2022;2022(1):5404343. https://doi.org/10.1155/2022/5404343
  • [3] Ahmadian R, Ghatee M. Driver Identification by Neural Network on Extracted Statistical Features from Smartphone Data. arXiv preprint arXiv:200200764. 2020. http://doi.org/10.48550.arXiv.2002.00764
  • [4] Ezzini S, Berrada I, Ghogho M. Who is behind the wheel? Driver identification and fingerprinting. Journal of Big Data. 2018;5(1):1-15. https://doi.org/10.1186/s40537-018-0118-7
  • [5] Virojboonkiate N, Chanakitkarnchok A, Vateekul P, Rojviboonchai K. Public transport driver identification system using histogram of acceleration data. Journal of Advanced Transportation. 2019;2019(1):6372597. https://doi.org/10.1155/2019/6372597
  • [6] Rahim MA, Zhu L, Li X, Liu J, Zhang Z, Qin Z, et al. Zero-to-stable driver identification: A non-intrusive and scalable driver identification scheme. IEEE transactions on vehicular technology. 2020;69(1):163-71. 10.1109/TVT.2019.2954529
  • [7] Arshad S, Feng C, Elujide I, Zhou S, Liu Y, editors. SafeDrive-Fi: A multimodal and device free dangerous driving recognition system using WiFi. 2018 IEEE international conference on communications (ICC); 2018: IEEE. 10.1109/ICC.2018.8422431
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  • [19] Chen J, Wu Z, Zhang J. Driver identification based on hidden feature extraction by using adaptive nonnegativity-constrained autoencoder. Applied Soft Computing. 2019;74:1-9. https://doi.org/10.1016/j.asoc.2018.09.030
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  • [21] Zuo J, Zhu X, Peng Y, Zhao Z, Wei X, Wang X. A new method of posture recognition based on WiFi signal. IEEE Communications Letters. 2021;25(8):2564-8. 10.1109/LCOMM.2021.3081135
  • [22] Liu M, Zhang L, Yang P, Lu L, Gong L. Wi-Run: Device-free step estimation system with commodity Wi-Fi. Journal of Network and Computer Applications. 2019;143:77-88. https://doi.org/10.1016/j.jnca.2019.05.004
  • [23] Al-qaness MA. Device-free human micro-activity recognition method using WiFi signals. Geo-spatial Information Science. 2019;22(2):128-37. https://doi.org/10.1080/10095020.2019.1612600
  • [24] Lv J, Man D, Yang W, Gong L, Du X, Yu M. Robust device-free intrusion detection using physical layer information of WiFi signals. Applied Sciences. 2019;9(1):175. https://doi.org/10.3390/app9010175
  • [25] Wang T, Yang D, Zhang S, Wu Y, Xu S. Wi-Alarm: Low-cost passive intrusion detection using WiFi. Sensors. 2019;19(10):2335. https://doi.org/10.3390/s19102335
  • [26] Fu Z, Xu J, Zhu Z, Liu AX, Sun X. Writing in the air with WiFi signals for virtual reality devices. IEEE Transactions on Mobile Computing. 2018;18(2):473-84. 10.1109/TMC.2018.2831709
  • [27] He Y, Chen Y, Hu Y, Zeng B. WiFi vision: Sensing, recognition, and detection with commodity MIMO-OFDM WiFi. IEEE Internet of Things Journal. 2020;7(9):8296-317. 10.1109/JIOT.2020.2989426
  • [28] Fei H, Xiao F, Han J, Huang H, Sun L. Multi-variations activity based gaits recognition using commodity WiFi. IEEE Transactions on Vehicular Technology. 2019;69(2):2263-73. 10.1109/TVT.2019.2962803
  • [29] Wang F, Gong W, Liu J, Wu K. Channel selective activity recognition with WiFi: A deep learning approach exploring wideband information. IEEE Transactions on Network Science and Engineering. 2018;7(1):181-92. 10.1109/TNSE.2018.2825144
  • [30] Zhang J, Wu F, Wei B, Zhang Q, Huang H, Shah SW, et al. Data augmentation and dense-LSTM for human activity recognition using WiFi signal. IEEE Internet of Things Journal. 2020;8(6):4628-41. 10.1109/JIOT.2020.3026732
  • [31] Venkatnarayan RH, Mahmood S, Shahzad M. WiFi based multi-user gesture recognition. IEEE Transactions on Mobile Computing. 2021;20(3):1242-56. 10.1109/TMC.2019.2954891
  • [32] Guo Z, Xiao F, Sheng B, Fei H, Yu S. WiReader: Adaptive air handwriting recognition based on commercial WiFi signal. IEEE Internet of Things Journal. 2020;7(10):10483-94. 10.1109/JIOT.2020.2997053
  • [33] Yan H, Zhang Y, Wang Y, Xu K. WiAct: A passive WiFi-based human activity recognition system. IEEE Sensors Journal. 2020;20(1):296-305. 10.1109/JSEN.2019.2938245
  • [34] Xiao C, Lei Y, Ma Y, Zhou F, Qin Z. DeepSeg: Deep-learning-based activity segmentation framework for activity recognition using WiFi. IEEE Internet of Things Journal. 2021;8(7):5669-81. 10.1109/JIOT.2020.3033173
  • [35] Ding J, Wang Y, Fu X. Wihi: WiFi based human identity identification using deep learning. IEEE Access. 2020;8:129246-62. 10.1109/ACCESS.2020.3009123
  • [36] Shen X, Ni Z, Liu L, Yang J, Ahmed K. WiPass: 1D-CNN-based smartphone keystroke recognition using WiFi signals. Pervasive and Mobile Computing. 2021;73:101393. https://doi.org/10.1016/j.pmcj.2021.101393
  • [37] Li F, Valero M, Shahriar H, Khan RA, Ahamed SI. Wi-COVID: A COVID-19 symptom detection and patient monitoring framework using WiFi. Smart Health. 2021;19:100147. https://doi.org/10.1016/j.smhl.2020.100147
  • [38] Ahmed HFT, Ahmad H, Narasingamurthi K, Harkat H, Phang SK. DF-WiSLR: device-free Wi-Fi-based sign language recognition. Pervasive and Mobile Computing. 2020;69:101289. https://doi.org/10.1016/j.pmcj.2020.101289
  • [39] Wu Z, Wan Y, Li L, Pan X, Paul A, Gong S. WISDOM: WiFi Improved Safe Driver Operation Monitoring With CSI. IEEE Sensors Letters. 2023. 10.1109/lsens.2023.3334226
  • [40] Alizadeh R, Savaria Y, Nerguizian C. Characterization and Selection of WiFi Channel State Information Features for Human Activity Detection in a Smart Public Transportation System. IEEE Open Journal of Intelligent Transportation Systems. 2023. 10.1109/OJITS.2023.3336795
  • [41] Gong D, Liu K, Pei D, Zhang H, Zhang S, Chen M. Wi-Watch: WiFi-based Vigilant-Activity Recognition for Ship Bridge Watchkeeping Officers. IEEE Transactions on Instrumentation and Measurement. 2023. 10.1109/TIM.2023.3343802
  • [42] Ducca SV, Jordão A, Margi CB, editors. Detection and Classification of Animal Crossings on Roads Using IoT-Based WiFi Sensing. 2023 IEEE Latin-American Conference on Communications (LATINCOM); 2023: IEEE. 10.1109/LATINCOM59467.2023.10361871
  • [43] Akhtar ZUA, Wang H. Wifi-based driver’s activity monitoring with efficient computation of radio-image features. Sensors. 2020;20(5):1381. https://doi.org/10.3390/s20051381
  • [44] Akhtar ZUA, Wang H. WiFi-based driver’s activity recognition using multi-layer classification. Neurocomputing. 2020;405:12-25. https://doi.org/10.1016/j.neucom.2020.04.133
  • [45] Akhtar ZUA, Wang H. WiFi-based gesture recognition for vehicular infotainment system—an integrated approach. Applied Sciences. 2019;9(24):5268. https://doi.org/10.3390/app9245268
  • [46] Duan S, Yu T, He J. WiDriver: Driver activity recognition system based on WiFi CSI. International Journal of Wireless Information Networks. 2018;25:146-56. https://doi.org/10.1007/s10776-018-0389-0
  • [47] Wang J, Tong J, Gao Q, Wu Z, Bi S, Wang H. Device-free vehicle speed estimation with WiFi. IEEE Transactions on Vehicular Technology. 2018;67(9):8205-14. 10.1109/TVT.2018.2840052
  • [48] Jia W, Peng H, Ruan N, Tang Z, Zhao W. WiFind: Driver fatigue detection with fine-grained Wi-Fi signal features. IEEE Transactions on Big Data. 2018;6(2):269-82. 10.1109/TBDATA.2018.2848969
  • [49] Halperin D, Hu W, Sheth A, Wetherall D. Tool release: Gathering 802.11 n traces with channel state information. ACM SIGCOMM computer communication review. 2011;41(1):53-. https://doi.org/10.1145/1925861.1925870
  • [50] Zhao Y, Gao R, Liu S, Xie L, Wu J, Tu H, et al. Device-free secure interaction with hand gestures in WiFi-enabled IoT environment. IEEE Internet of Things Journal. 2020;8(7):5619-31. 10.1109/JIOT.2020.3032623
  • [51] Muhammad Y, Tahir M, Hayat M, Chong KT. Early and accurate detection and diagnosis of heart disease using intelligent computational model. Scientific reports. 2020;10(1):19747. https://doi.org/10.1038/s41598-020-76635-9
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There are 58 citations in total.

Details

Primary Language English
Subjects Automotive Engineering (Other)
Journal Section Articles
Authors

Zain Akhtar 0000-0002-5661-9107

Hafiz Faiz Rasool 0000-0002-7116-2109

Publication Date December 31, 2024
Submission Date February 4, 2024
Acceptance Date May 7, 2024
Published in Issue Year 2024

Cite

APA Akhtar, Z., & Rasool, H. F. (2024). WiFi-based Vehicle Security System for Future Intelligent Transportation Systems. International Journal of Automotive Science And Technology, 8(4), 493-505. https://doi.org/10.30939/ijastech..1431379
AMA Akhtar Z, Rasool HF. WiFi-based Vehicle Security System for Future Intelligent Transportation Systems. IJASTECH. December 2024;8(4):493-505. doi:10.30939/ijastech.1431379
Chicago Akhtar, Zain, and Hafiz Faiz Rasool. “WiFi-Based Vehicle Security System for Future Intelligent Transportation Systems”. International Journal of Automotive Science And Technology 8, no. 4 (December 2024): 493-505. https://doi.org/10.30939/ijastech. 1431379.
EndNote Akhtar Z, Rasool HF (December 1, 2024) WiFi-based Vehicle Security System for Future Intelligent Transportation Systems. International Journal of Automotive Science And Technology 8 4 493–505.
IEEE Z. Akhtar and H. F. Rasool, “WiFi-based Vehicle Security System for Future Intelligent Transportation Systems”, IJASTECH, vol. 8, no. 4, pp. 493–505, 2024, doi: 10.30939/ijastech..1431379.
ISNAD Akhtar, Zain - Rasool, Hafiz Faiz. “WiFi-Based Vehicle Security System for Future Intelligent Transportation Systems”. International Journal of Automotive Science And Technology 8/4 (December 2024), 493-505. https://doi.org/10.30939/ijastech. 1431379.
JAMA Akhtar Z, Rasool HF. WiFi-based Vehicle Security System for Future Intelligent Transportation Systems. IJASTECH. 2024;8:493–505.
MLA Akhtar, Zain and Hafiz Faiz Rasool. “WiFi-Based Vehicle Security System for Future Intelligent Transportation Systems”. International Journal of Automotive Science And Technology, vol. 8, no. 4, 2024, pp. 493-05, doi:10.30939/ijastech. 1431379.
Vancouver Akhtar Z, Rasool HF. WiFi-based Vehicle Security System for Future Intelligent Transportation Systems. IJASTECH. 2024;8(4):493-505.


International Journal of Automotive Science and Technology (IJASTECH) is published by Society of Automotive Engineers Turkey

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