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Abstract
This research presents the development of an Internet of Things (IoT)-based automatic notification system integrated with conventional Closed-Circuit Television (CCTV) cameras using the pose estimation method to detect human presence in real-time. The method used in this research is BlazePose from the MediaPipe library, which is capable of detecting up to 33 key points of the human body. The system was developed using the Python programming language with the Flask framework for the backend and Vue.js for the frontend. Video streaming is captured via the Real-Time Streaming Protocol (RTSP) protocol from the CCTV DVR, then analysed using a body pose detection algorithm. If the system detects human presence based on distance, angle, and pose similarity thresholds (cosine similarity), the system will send an automatic notification via Telegram to the user. The test results show that the system successfully detects human poses with a good level of accuracy and can send notifications efficiently according to the specified schedule. The system also provides a web-based feature that displays activity statistics, the number of notifications, and log reports that simplify the monitoring process. This research shows that pose detection technology can be effectively implemented in conventional CCTV systems to improve security responses in real-time and cost-effectively.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
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- “Deep Learning-Based Pose Estimation for Dystonia Score Prediction.”
- Y. Xu, J. Zhang, Q. Zhang, dan D. Tao, “ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation.” [Daring]. Tersedia pada: https://github.com/ViTAE-Transformer/ViTPose.
- I. Grishchenko dkk., “BlazePose GHUM Holistic: Real-time 3D Human Landmarks and Pose Estimation,” Jun 2022, [Daring]. Tersedia pada: http://arxiv.org/abs/2206.11678
- V. Bazarevsky, I. Grishchenko, K. Raveendran, T. Zhu, F. Zhang, dan M. Grundmann, “BlazePose: On-device Real-time Body Pose tracking,” Jun 2020, [Daring]. Tersedia pada: http://arxiv.org/abs/2006.10204
- M. Iqbal, M. Firmansyah, N. Suharto, dan Y. H. Prasetyo, “RTSP and HTTP Protocol Analysis for Streaming Services on Manet Networks in State Polytechnic of Malang,” Journal of Telecommunication Network, vol. 12, no. 3, 2022.
- A. Darius Govindasamy, “GETTING RTSP TO WORK NATIVELY IN THE BROWSER,” 2022.
- “13.Optimalisasi Sistem Informasi Melalui Penambahan Fitur Notifikasi Sebagai Upaya Peningkatan Jumlah Kenaikan Pangkat Pegawai”.
- R. Parlika, H. Khariono, H. A. Kusuma, dan A. Setyawan, “JIP (Jurnal Informatika Polinema) PEMANFAATAN BOT TELEGRAM SEBAGAI E-LEARNING UJIAN BERBASIS FILE”.
- H. A. Kusuma, S. B. Wijaya, dan D. Nusyirwan, “SISTEM KEAMANAN RUMAH BERBASIS ESP32-CAM DAN TELEGRAM SEBAGAI NOTIFIKASI,” Infotronik : Jurnal Teknologi Informasi dan Elektronika, vol. 8, no. 1, hlm. 30, Jun 2023, doi: 10.32897/infotronik.2023.8.1.2291.
References
T. Astanta dkk., “PERAN CLOSED CIRCUIT TELEVISION (CCTV) DALAM MENINGKATKAN KEAMANAN DI KAMPUS STIE GANESHA,” 2023.
A. F. R. Nogueira, H. P. Oliveira, dan L. F. Teixeira, “Markerless Multi-view 3D Human Pose Estimation: a survey,” Jun 2025, doi: 10.1016/j.imavis.2025.105437.
B. Rachman, R. Suppa, dan A. A. H. Dani, “RANCANG BANGUN SMART LAMP MENGGUNAKAN NODEMCU BERBASIS INTERNET OF THINGS (IOT),” Jurnal Informatika dan Teknik Elektro Terapan, vol. 13, no. 1, Jan 2025, doi: 10.23960/jitet.v13i1.5591.
B. C. Welsh, E. L. Piza, A. L. Thomas, dan D. P. Farrington, “Private Security and Closed-Circuit Television (CCTV) Surveillance: A Systematic Review of Function and Performance,” J Contemp Crim Justice, vol. 36, no. 1, hlm. 56–69, Feb 2020, doi: 10.1177/1043986219890192.
R. A. Radouan Ait Mouha, “Internet of Things (IoT),” Journal of Data Analysis and Information Processing, vol. 09, no. 02, hlm. 77–101, 2021, doi: 10.4236/jdaip.2021.92006.
F. Susanto, N. Komang Prasiani, dan P. Darmawan, “IMPLEMENTASI INTERNET OF THINGS DALAM KEHIDUPAN SEHARI-HARI,” Online, 2022. [Daring]. Tersedia pada: https://jurnal.std-bali.ac.id/index.php/imagine
“Deep Learning-Based Pose Estimation for Dystonia Score Prediction.”
Y. Xu, J. Zhang, Q. Zhang, dan D. Tao, “ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation.” [Daring]. Tersedia pada: https://github.com/ViTAE-Transformer/ViTPose.
I. Grishchenko dkk., “BlazePose GHUM Holistic: Real-time 3D Human Landmarks and Pose Estimation,” Jun 2022, [Daring]. Tersedia pada: http://arxiv.org/abs/2206.11678
V. Bazarevsky, I. Grishchenko, K. Raveendran, T. Zhu, F. Zhang, dan M. Grundmann, “BlazePose: On-device Real-time Body Pose tracking,” Jun 2020, [Daring]. Tersedia pada: http://arxiv.org/abs/2006.10204
M. Iqbal, M. Firmansyah, N. Suharto, dan Y. H. Prasetyo, “RTSP and HTTP Protocol Analysis for Streaming Services on Manet Networks in State Polytechnic of Malang,” Journal of Telecommunication Network, vol. 12, no. 3, 2022.
A. Darius Govindasamy, “GETTING RTSP TO WORK NATIVELY IN THE BROWSER,” 2022.
“13.Optimalisasi Sistem Informasi Melalui Penambahan Fitur Notifikasi Sebagai Upaya Peningkatan Jumlah Kenaikan Pangkat Pegawai”.
R. Parlika, H. Khariono, H. A. Kusuma, dan A. Setyawan, “JIP (Jurnal Informatika Polinema) PEMANFAATAN BOT TELEGRAM SEBAGAI E-LEARNING UJIAN BERBASIS FILE”.
H. A. Kusuma, S. B. Wijaya, dan D. Nusyirwan, “SISTEM KEAMANAN RUMAH BERBASIS ESP32-CAM DAN TELEGRAM SEBAGAI NOTIFIKASI,” Infotronik : Jurnal Teknologi Informasi dan Elektronika, vol. 8, no. 1, hlm. 30, Jun 2023, doi: 10.32897/infotronik.2023.8.1.2291.