Published on: April 2026
SMART SECURITY SYSTEM WITH MOTION DETECTION
Maha Hema V Arthy Sree S
Dr. B. Azhagusundari
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Abstract
This paper presents a Smart Security System using motion detection that integrates Internet of Things (IoT) and Artificial Intelligence (AI) technologies to enhance real-time surveillance. The system utilizes an ESP32-CAM module and a PIR (Passive Infrared) sensor to detect motion and capture images only when necessary. The captured images are transmitted to a Python-based server, where an AI model (YOLOv8) analyzes them to identify human presence.Unlike traditional security systems that trigger alerts for all types of motion, the proposed system intelligently distinguishes between human and non-human objects, thereby significantly reducing false alarms. The system operates in real time with minimal human intervention and ensures efficient resource utilization by avoiding continuous recording.
How to Cite this Paper
V, M. H. & S, A. S. (2026). Smart Security System with Motion Detection. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.428
V, Maha, and Arthy S. "Smart Security System with Motion Detection." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.428.
V, Maha, and Arthy S. "Smart Security System with Motion Detection." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.428.
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References
[1] Redmon, J., Divvala, S., Girshick, R., & Farhadi, A., “You Only Look Once: Unified, Real-Time Object Detection,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 779–788, 2016.[2] Bochkovskiy, A., Wang, C. Y., & Liao, H. Y. M., “YOLOv4: Optimal Speed and Accuracy of Object Detection,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 746–755, 2020.
[3] Jocher, G., et al., “Ultralytics YOLOv8: Real-Time Object Detection Model,” Ultralytics Documentation and Technical Report, 2023.
[4] Bradski, G., & Kaehler, A., Learning OpenCV: Computer Vision with the OpenCV Library, O’Reilly Media, pp. 1–550, 2008.
[5] Espressif Systems, “ESP32 Series Datasheet,” Espressif Systems Technical Documentation, pp. 1–65, 2020.
[6] AI-Thinker, “ESP32-CAM WiFi + Bluetooth Camera Module Datasheet,” AI-Thinker Technical Documentation, pp. 1–20, 2019.
[7] OmniVision Technologies, “OV2640 CameraChip Sensor Datasheet,” OmniVision Semiconductor Technical Report, pp. 1–24, 2018.
[8] Patel, K. K., & Patel, S. M., “Internet of Things (IoT): Definition, Characteristics, Architecture, Enabling Technologies, Applications and Future Challenges,” International Journal of Engineering Science and Computing, vol. 6, no. 5, pp. 6122–6131, 2016.
[9] Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M., “Internet of Things for Smart Cities,” IEEE Internet of Things Journal, vol. 1, no. 1, pp. 22–32, 2014.
[10] Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M., “Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions,” Future Generation Computer Systems, vol. 29, no. 7, pp. 1645–1660, 2013.
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- •Published on: Apr 16 2026
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