IEEE Consumer Electronics Magazine - January/February 2023 - 86

Security, Trust and Privacy Solutions for Intelligent Internet of Vehicular Things
emotion. In Cases 3 and 4, we have analyzed the
speech corrupted by traffic noise and train noise,
respectively, which also provides enhanced recognition
rates compared to the conventional one.We
found that highest performance of ASR is reported
in anger noise about 98.5% followed by conventional
Paliwal's4 method 88.5%.
CONCLUSIONS
Considering the various aspects of human
stress detection and monitoring methodology in
our daily life, this article describes the significance
into CE aspects of secure technology with
various key points of real-time environment.
This article will be an essential step toward the
development of a ubiquitous human stress monitoring
system in the edge of secure IoV cloud
computing. In real-world applications, the influence
of noise is a major constrain in many of the
automatic speech recognition. The performance
of the proposed OMSS method is evaluated using
objective evaluation parameters such as SNR
seg. and PESQ. For the speech emotion type,
anger and happy (with different noise type and
input SNR) constructed by treatment type of the
proposed scheme greatly improved SNR seg. as
compared with the traditional ModSpecSub
method. The best recognized emotion for the
proposed OMSS is anger (98.5%), which is the
mostly confused with speech emotion happy in
conventional methods.
ACKNOWLEDGMENTS
This work was supported by King Saud University,
Riyadh, Saudi Arabia, under Researchers'
Supporting Project RSP-2020/250.
&REFERENCES
1. A. A. Penilla and A. S. Penilla, " Methods and vehicles
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" Consumer IoT: Security vulnerability case studies and
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Pavan D. Paikrao is currently an Associate Professor
with the Department of Electronics Telecommunication,
TPCT's College of Engineering, Osmanabad,
India. He received the M.Tech. and Ph.D. degrees
from Dr. Babasaheb Ambedkar Technological University,
Lonere, India, in 2011 and 2019, respectively.
Contact him at pavanpaikrao@coeosmanabad.ac.in.
Amrit Mukherjee is currently with the School of
Electronics and Information Engineering, Anhui University,
Hefei, China. He received the Ph.D. degree from
KIIT University, Bhubaneswar, India, in 2017. He is a
Member of IEEE. He is the corresponding author of this
article. Contact himat amrit1460@ieee.org.
Deepak Kumar Jain received the Ph.D. degree
from the University of Chinese Academy of Sciences,
Beijing, China. He is currently an Assistant Professor
with the University of Posts Telecommunications,
Chongqing, China. Contact him at dkj@ieee.org.
Pushpita Chatterjee received the Ph.D. degree
from IIT Kharagpur, Kharagpur, India, in 2013. She is
currently with Future Networking Research Group,
and with the Faculty of Electrical and Electronics
Engineering, Ton Duc Thang University, Ho Chi Minh
City, Vietnam. She was a Research Consultant with
Old Dominion University, Norfolk, VA, USA. Contact
her at puspitachatterjee@tdtu.edu.vn.
Waleed Alnumay is currently an Associate Professor
with King Saud University, Riyadh, Saudi Arabia.
Contact him at wnumay@ksu.edu.sa.
86
IEEE Consumer Electronics Magazine

http://dx.doi.org/10.1109/MCE.2020.2969195 http://dx.doi.org/10.1016/j.specom.2010.02.004 http://dx.doi.org/10.1109/89.928915 http://dx.doi.org/10.1007/s10579-008-9076-6 http://dx.doi.org/10.1007/s10579-008-9076-6 http://dx.doi.org/10.1109/MCE.2019.2953740

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