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Cited by 41Autonomous Vehicle Technology and SafetyIoT and GPS-based Vehicle Safety SystemsAdvanced Neural Network Applications

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A study on development of the blind spot detection system for the IoT-based smart connected car

Kwon, Donghwoon, Park, Suwoo, Baek, SunHee, Malaiya, Ritesh K., Yoon, Geumchae, Ryu, Jeong-Tak·2018·2018 IEEE International Conference on Consumer Electronics (ICCE)
DOI 10.1109/icce.2018.8326077
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Abstract

The Internet of things (IoT) is an emerging topic in a variety of industry fields such as manufacturing, engineering, automobile, etc. Especially, many automobile companies are competitively introducing a smart-connected car in conjunction with the IoT technology. For instance, some recent vehicles support autonomous driving using cameras and radar-based safety features such as pre-collision prevention system, lane departure alert with a steering assistant function, etc. Based on this example of the IoT-based smart connected car, we actually developed the camera-based blind spot assistance system. The power / serializer board and camera board consisting of a number of sensors, processors, and other hardware components were developed by our own system interface design, and we confirmed that the developed system successfully met quantitative evaluation criteria through testing. Furthermore, we are proposing improvement plans and an idea of object detection in the blind spot based on a deep learning methodology.

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Research works printed but not linked: 12

  1. 2016, The Internet of Things and connected cars: IoT on board, Hewlett Packard Enterprise, 1
  2. 10.1002/dac.2417 · DOI
  3. 10.7763/IJMLC.2014.V6.465 · DOI
  4. 10.1051/matecconf/20168102007 · DOI
  5. ba, 2015, Multiple Object Recognition with Visual Attention, International Conference on Learning Representations (ICLR), 1
  6. 10.1016/j.aap.2016.06.017 · DOI
  7. 10.1109/ICCVW.2013.77 · DOI
  8. 2017, 2015 Oddyssey Honda LaneWatch - Honda Owners, Honda Motor Co Ltd
  9. 2014, Evaluation of Blind Spot Monitoring and Blind Spot Intervention Technologies, AAA Automotive Engineering, 1
  10. porter, 2015, How Smart, Conncted Products Are Transforming Companies, Harvard Business Review, 1
  11. saboune, 2011, A visual blindspot monitoring system for safe lane changes, International Conference on Image Analysis and Processing (ICIAP), 6979, 1
  12. mohammed, 2017, Internet of Things Applications, Challenges and Related Future Technologies, World Scientific News, 67, 126

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Metadata

Authors
Kwon, D., Park, S., Baek, S., Malaiya, R. K., Yoon, G., & Ryu, J.-T.
Affiliations
East Texas A&M University (US)
ORCID
Venue
2018 IEEE International Conference on Consumer Electronics (ICCE)
Publisher
IEEE
Published
2018-01
Pages
1-4
DOI
10.1109/icce.2018.8326077
OpenAlex
W2795066257
Cited by
41
References
0
Citations by year
2026: 2 · 2025: 2 · 2024: 5 · 2023: 5 · 2022: 7 · 2021: 12 · 2020: 3 · 2019: 4 · 2018: 1
FWCI
5.13
Type
conference paper
Language
en
Open access
closed
Locations
International Conference on Consumer Electronics (publishedVersion)
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
  • Physical Sciences › Engineering › Automotive Engineering › IoT and GPS-based Vehicle Safety Systems
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
Keywords
blind spot detection, Internet of Things, vehicle safety, system interface design, object detection, deep learning

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CoChat. (2026). Citation check: A study on development of the blind spot detection system for the IoT-based smart connected car. https://app.cochat.ai/papers/10.1109/icce.2018.8326077
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Kwon, D., Park, S., Baek, S., Malaiya, R. K., Yoon, G., & Ryu, J.-T. (2018). A study on development of the blind spot detection system for the IoT-based smart connected car. 2018 IEEE International Conference on Consumer Electronics (ICCE). https://doi.org/10.1109/icce.2018.8326077