Implementation of IoT-Based Facial Recognition for Home Security System Using Raspberry Pi and Mobile Application

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Frencis Matheos Sarimole
Ahas Eko Septianto

Abstract

The rapid advancement of technologies such as Artificial Intelligence (AI), computer vision, and the Internet of Things (IoT) has significantly impacted various fields, particularly in security systems. Traditional security measures, such as door locks, are increasingly inadequate in ensuring the safety of homes. To address this issue, we have developed a prototype of a home security system based on Raspberry Pi, integrated with a real-time mobile application. This intelligent system is designed to monitor residential areas, detect unfamiliar individuals, and send immediate notifications to the homeowner's mobile device. Utilizing Raspberry Pi in conjunction with OpenCV for motion and facial recognition, as well as a web server, the system demonstrates high accuracy in detecting motion and faces. It promptly notifies the homeowner in the event of suspicious activity. This prototype represents an efficient and effective solution to enhancing home security by leveraging modern technology.

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Author Biographies

Frencis Matheos Sarimole, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika

Informatics Engineering Study Program, Faculty of Computer Technology, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, East Jakarta City, Special Capital Region of Jakarta, Indonesia

Ahas Eko Septianto, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika

Informatics Engineering Study Program, Faculty of Computer Technology, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, East Jakarta City, Special Capital Region of Jakarta, Indonesia

How to Cite

Sarimole, F. M., & Septianto, A. E. (2024). Implementation of IoT-Based Facial Recognition for Home Security System Using Raspberry Pi and Mobile Application. International Journal Software Engineering and Computer Science (IJSECS), 4(2), 453-462. https://doi.org/10.35870/ijsecs.v4i2.2554

References

Rahim, M. A., Zhong, Y., & Ahmad, T. (2022). A deep learning-based intelligent face recognition method in the Internet of Home Things for security applications. Journal of Hunan University Natural Sciences, 49(10), 39-52. https://doi.org/10.55463/issn.1674-2974.49.10.6

Rajeshkumar, G., et al. (2023). Smart office automation via faster R-CNN based face recognition and Internet of Things. Measurement: Sensors, 27, 100719. https://doi.org/10.1016/j.measen.2023.100719

Meddeb, H., Abdellaoui, Z., & Houaidi, F. (2023). Development of surveillance robot based on face recognition using Raspberry-PI and IoT. Microprocessors and Microsystems, 96, 104728. https://doi.org/10.1016/j.micpro.2022.104728

Ali, H. H., Naif, J. R., & Humood, W. R. (2023). A new smart home intruder detection system based on deep learning. Al-Mustansiriyah Journal of Science, 34(2), 60-69. https://doi.org/10.23851/mjs.v34i2.1267

Chong, P. L., Than, Y. Y., Ganesan, S., & Ravi, P. (2023). An overview of IoT-based smart home surveillance and control system: Challenges and prospects. Malaysian Journal of Science and Advanced Technology, 2(S1), 54-66. https://doi.org/10.56532/mjsat.v2iS1.121

Mohi Uddin, K. M., Afrin, S., Rahman, N., Mostafiz, R., & Rahman, Md. M. (2022). Smart home security using facial authentication and mobile application. International Journal of Wireless and Microwave Technologies, 12(2), 40-50. https://doi.org/10.5815/ijwmt.2022.02.04

Khairuddin, M. H., Shahbudin, S., & Kassim, M. (2021). A smart building security system with intelligent face detection and recognition. IOP Conference Series: Materials Science and Engineering, 1176(1), 012030. https://doi.org/10.1088/1757-899X/1176/1/012030

Andreas, C. R., Aldawira, H. W., Putra, N., Hanafiah, S., Surjarwo, & Wibisurya, A. (2019). Door security system for home monitoring based on ESP32. Procedia Computer Science, 157, 673-682. https://doi.org/10.1016/J.PROCS.2019.08.218

Zuma, M., Owolawi, P. A., Malele, V., Odeyemi, K., Aiyetoro, G., & Ojo, J. S. (2021). Intrusion detection system using Raspberry Pi and Telegram integration. In Proceedings of the International Conference on Artificial Intelligence and its Applications (pp. 1-7). New York, NY: ACM. https://doi.org/10.1145/3487923.3487928

Malpe, K. (2022). A face recognition method in the Internet of Things for security in smart recognition places. International Journal of Research in Applied Science and Engineering Technology, 10(1), 687-690. https://doi.org/10.22214/ijraset.2022.39882

Alam, T., & Parvez, M. (2021). Smart home automation and security using IoT and cloud computing. International Journal of Electronics and Communication Engineering, 12(3), 215-223. https://doi.org/10.1016/j.ijeco.2021.08.012

Chen, Y., Xu, Y., & Li, S. (2022). Edge computing-based intelligent surveillance for home security. Future Generation Computer Systems, 130, 218-228. https://doi.org/10.1016/j.future.2021.12.015

Gonzalez, L., & Perez, J. (2022). IoT-based surveillance system for smart homes with integrated machine learning. Computers & Security, 117, 102687. https://doi.org/10.1016/j.cose.2022.102687

Kaur, R., & Singh, S. (2022). An efficient deep learning approach for smart home security system. Pattern Recognition Letters, 151, 168-175. https://doi.org/10.1016/j.patrec.2022.02.021

Kumar, A., & Goyal, M. (2022). An AI-enabled IoT-based home security system using deep learning algorithms. IEEE Access, 10, 17342-17354. https://doi.org/10.1109/ACCESS.2022.3145239

Nguyen, H. M., & Tran, T. T. (2021). A review on the application of deep learning in smart home security. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(11), 6792-6802. https://doi.org/10.1109/TSMC.2021.3075241

Patel, H., Singh, D., & Singh, S. (2021). IoT-based smart home security system with real-time alarming. Journal of Network and Computer Applications, 176, 102918. https://doi.org/10.1016/j.jnca.2021.102918

Sharma, R., & Bhalla, V. (2021). Enhancing IoT-based home security with blockchain technology. Journal of Information Security and Applications, 58, 102799. https://doi.org/10.1016/j.jisa.2021.102799.

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