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Paper ID:IJSREM68251

VISION-BASED TRACKING TURRET USING ESP32-CAM AND YOLO WITH A DECOUPLED HOST-PC ARCHITECTURE

Stream/Area:

-

Subject:

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Paper ID:

IJSREM68251

Volume:

10 |

10 |

Oct 2026

Pages:

1-3

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM68251

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Rudra Sridatta

Rudra Sridatta

Department of ECE

CMR Technical Campus

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DDS

Dr D Sreekanth

Department of ECE

CMR Technical Campus

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AT

Angoth Tharun

Department of ECE

CMR Technical Campus

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BS

Beesa Sanjana

Department of ECE

CMR Technical Campus

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MP

Manda Pushpachandana

Department of ECE

CMR Technical Campus

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Abstract

Commercial pan-tilt-zoom (PTZ) tracking cameras run detection and servo control on one embedded processor, which delays the response to a moving target and limits them to simple motion-based detection. This paper presents a Vision-Based Tracking Turret that separates the two tasks. An ESP32-CAM streams video over Wi-Fi to a host PC, where a YOLOv5/YOLOv8 model detects the target and computes the angle the turret must move. The angles are sent over a USB serial link to an ESP32 board, which drives two SG90 servos for pan and tilt and switches a laser indicator when the target is locked. The prototype was tested indoors with a single person as the target. In well-lit conditions at 0.5 to 1.5 m the average detection confidence was 0.92 and the detection rate was 98%. The end-to-end delay from capture to servo command was about 80 to 150 ms. The detector, not the actuator, is the main source of delay, so it can be improved by moving inference to a GPU. The hardware costs about INR 1,940 and the design is easy to extend.

KEYWORDS

Object Detection YOLO ESP32-CAM Pan-Tilt Turret OpenCV Servo Control Embedded Systems Computer Vision.

Cite This Article

Rudra Sridatta, Dr D Sreekanth, Angoth Tharun, Beesa Sanjana, Manda Pushpachandana, "VISION-BASED TRACKING TURRET USING ESP32-CAM AND YOLO WITH A DECOUPLED HOST-PC ARCHITECTURE," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 10, pp. 1-3, Oct 2026. https://doi.org/10.55041/IJSREM68251

Full Article/Conclusion

This paper presented a Vision-Based Tracking Turret in which a host PC runs YOLO detection and an ESP32 board drives the pan-tilt servos and a laser indicator, with an ESP32-CAM as the wireless camera. Splitting detection from actuation avoids the processor contention found in single-processor trackers. The prototype tracked a person indoors with an average confidence of 0.92 at close range and a delay of about 80 to 150 ms, at a hardware cost of about INR 1,940. Future work will add a thermal sensor for dark scenes, Kalman filter prediction to bridge missed detections, GPU or edge-AI inference to remove the PC, multi-target tracking and a web dashboard for remote monitoring.

References

1)    P. Viola and M. J. Jones, "Robust Real-Time Face Detection," Int. J. Computer Vision, vol. 57, no. 2, pp. 137-154, May 2004. 2)    N. Dalal and B. Triggs, "Histograms of Oriented Gradients for Human Detection," in Proc. IEEE CVPR, 2005, vol. 1, pp. 886-893. 3)    W. Liu et al., "SSD: Single Shot MultiBox Detector," in Eur. Conf. Computer Vision (ECCV), Springer, 2016, pp. 21-37. 4)    J. Redmon, S. Divvala, R. Girshick and A. Farhadi, "You Only Look Once: Unified, Real-Time Object Detection," in Proc. IEEE CVPR, 2016, pp. 779-788. 5)    Raza et al., Raspberry Pi 4 face-tracking turret using an OpenCV Haar cascade, 2019. [Full citation to be added.] 6)    Jain and Kumar, Raspberry Pi 4 tracking turret using MobileNet-SSD, 2021. [Full citation to be added.] 7)    Ultralytics, "YOLOv8 Documentation." [Online]. Available: https://docs.ultralytics.com 8)    PySerial Development Team, "PySerial Documentation." [Online]. Available: https://pyserial.readthedocs.io 9)    Arduino, "ESP32Servo Library Documentation." [Online]. Available: https://madhephaestus.github.io/ESP32Servo/annotated.html

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Publication Date

10/24/2026

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Review Rounds: 2

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