Safe Security System Using Face Recognition Based on IoT

Authors

  • Ondra Eka Putra Universitas Putra Indonesia YPTK Padang, Indonesia
  • Retno Devita Universitas Putra Indonesia YPTK Padang, Indonesia
  • Niko Wahyudi Universitas Putra Indonesia YPTK Padang, Indonesia

DOI:

10.33395/sinkron.v8i2.12231

Keywords:

Safe Security, Face Recognition, PCA, IoT, Raspberry Pi 3B

Abstract

Face recognition is widely used in various applications, especially in the field of surveillance and security systems. This study aims to design and build a safe security system using face recognition via camera based on internet of things. This system uses the Raspberry Pi 3B and the OpenCV library as face recognition data processing which produces output on the Selenoid to open and close the safe, LCD 16x2 to display system status, IoT-based email delivery when smugglers occur. This study performs face recognition through the face detection stage using the Viola Jones method, feature extraction using the PCA (Principal Component Analysis) method and face recognition, then matched with the existing profile data in the directory. The results of this study indicate that the safe is open when a face is detected and will send a face capture to the e-mail address of the owner’s safe if the detected face is not recognized. Tests carried out on the safe security system using face recognition based on IoT build reach validity 90,25%.

GS Cited Analysis

Downloads

Download data is not yet available.

References

Aydin, I., & Othman, N. A. (2017). A new IoT combined face detection of people by using computer vision for security application. IDAP 2017 - International Artificial Intelligence and Data Processing Symposium, 0–5. https://doi.org/10.1109/IDAP.2017.8090171

Cavas, M., & Ahmad, M. B. (2019). A REVIEW ADVANCEMENT OF SECURITY ALARM SYSTEM USING INTERNET OF THINGS (IoT). International Journal of New Computer Architectures and Their Applications, 9(2), 38–49. https://doi.org/10.17781/p002617

Ejaz, M. S., Islam, M. R., Sifatullah, M., & Sarker, A. (2019). Implementation of Principal Component Analysis on Masked and Non-masked Face Recognition. 1st International Conference on Advances in Science, Engineering and Robotics Technology 2019, ICASERT 2019, 2019(Icasert), 1–5. https://doi.org/10.1109/ICASERT.2019.8934543

Elngar, A. A., & Kayed, M. (2020). Vehicle Security Systems using Face Recognition based on Internet of Things. Open Computer Science, 10(1), 17–29. https://doi.org/10.1515/comp-2020-0003

Faisal, F., & Hossain, S. A. (2019). Smart security system using face recognition on raspberry Pi. 2019 13th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2019. https://doi.org/10.1109/SKIMA47702.2019.8982466

Harikrishnan, J., Sudarsan, A., Sadashiv, A., & Remya Ajai, A. S. (2019). Vision-Face Recognition Attendance Monitoring System for Surveillance using Deep Learning Technology and Computer Vision. Proceedings - International Conference on Vision Towards Emerging Trends in Communication and Networking, ViTECoN 2019, 1–5. https://doi.org/10.1109/ViTECoN.2019.8899418

Khattar, S., Sachdeva, A., Kumar, R., & Gupta, R. (2019). Smart home with virtual assistant using raspberry pi. Proceedings of the 9th International Conference On Cloud Computing, Data Science and Engineering, Confluence 2019, 576–579. https://doi.org/10.1109/CONFLUENCE.2019.8776918

Kim, J., Yun, S. S., Kang, B. N., Kim, D., & Choi, J. (2017). Reliable multi-person identification using DCNN-based face recognition algorithm and scale-ratio method. 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017, 97–101. https://doi.org/10.1109/URAI.2017.7992895

Kortli, Y., Jridi, M., Al Falou, A., & Atri, M. (2020). Face recognition systems: A survey. Sensors (Switzerland), 20(2). https://doi.org/10.3390/s20020342

Kumar, P. M., Gandhi, U., Varatharajan, R., Manogaran, G., R, J., & Vadivel, T. (2019). Intelligent face recognition and navigation system using neural learning for smart security in Internet of Things. Cluster Computing, 22, 7733–7744. https://doi.org/10.1007/s10586-017-1323-4

Mantoro, T., Ayu, M. A., & Suhendi. (2018). Multi-Faces Recognition Process Using Haar Cascades and Eigenface Methods. International Conference on Multimedia Computing and Systems -Proceedings, 2018-May, 1–5. https://doi.org/10.1109/ICMCS.2018.8525935

Munir, A., Kashif Ehsan, S., Mohsin Raza, S. M., & Mudassir, M. (2019). Face and speech recognition based smart home. 2019 International Conference on Engineering and Emerging Technologies, ICEET 2019, 1–5. https://doi.org/10.1109/CEET1.2019.8711849

Nguyen, T., Lakshmanan, B., & Sheng, W. (2018). A Smart Security System with Face Recognition. ArXiv. http://arxiv.org/abs/1812.09127

Othman, N. A., & Aydin, I. (2018a). A face recognition method in the Internet of Things for security applications in smart homes and cities. Proceedings - 2018 6th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2018, 20–24. https://doi.org/10.1109/SGCF.2018.8408934

Othman, N. A., & Aydin, I. (2018b). A new IoT combined body detection of people by using computer vision for security application. Proceedings - 9th International Conference on Computational Intelligence and Communication Networks, CICN 2017, 2018-Janua, 108–112. https://doi.org/10.1109/CICN.2017.8319366

Qezavati, H., Majidi, B., & Manzuri, M. T. (2019). Partially Covered Face Detection in Presence of Headscarf for Surveillance Applications. 4th International Conference on Pattern Recognition and Image Analysis, IPRIA 2019, 195–199. https://doi.org/10.1109/PRIA.2019.8786004

Ramana, L., Choi, W., & Cha, Y. J. (2019). Fully automated vision-based loosened bolt detection using the Viola–Jones algorithm. Structural Health Monitoring, 18(2), 422–434. https://doi.org/10.1177/1475921718757459

Surve, M., Joshi, P., Jamadar, S., & Vharkate, M. M. N. (2020). Automatic Attendance System using Face Recognition Technique. International Journal of Recent Technology and Engineering (IJRTE), 9(1), 2134–2138. https://doi.org/10.35940/ijrte.a2644.059120

Zafaruddin, G. M., & Fadewar, H. S. (2018). Face recognition using eigenfaces. In Advances in Intelligent Systems and Computing (Vol. 810). Springer Singapore. https://doi.org/10.1007/978-981-13-1513-8_87

Downloads


Crossmark Updates

How to Cite

Putra, O. E., Devita, R. ., & Wahyudi, N. (2023). Safe Security System Using Face Recognition Based on IoT. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 7(2), 1021-1030. https://doi.org/10.33395/sinkron.v8i2.12231

Issue

Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023

Section

Articles

License

Copyright (c) 2023 Ondra Eka Putra, Retno Devita, Niko Wahyudi

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Crossref
Scopus
Google Scholar
Europe PMC