PhotoBot: An Automated Smart Photography Robot Using Computer Vision and Servo-Controlled Camera Mechanism | IJCT Volume 13 – Issue 3 | IJCT-V13I3P95

International Journal of Computer Techniques
ISSN 2394-2231
Volume 13, Issue 3  |  Published: May – June 2026

Author

Yadnesh Wagaskar, Sarthak Adhapure, Anushka Patil, Tanmay Patil

Abstract

Group photography at tourist locations presents a long- standing challenge at least one mem-ber of the group must step out to operate the cam-era, thereby being excluded from the photograph. Pho-toBot addresses this problem by integrating computer vision-based person detection, servo motor-driven cam-era alignment, and digital zoom control into a compact, portable, and fully autonomous photography robot. The system runs a Python-based application on a Mini PC, -time face detection. Detected face positions are used to compute angular offsets, which drive PWM servo sig-nals to physically orient the camera toward the group. Digital zoom is applied dynamically based on subject distance. A simulated GPIO interface enables software-only testing without physical hardware. The prototype demonstrated accurate face tracking and reliable au-tomated photo capture across all test scenarios, con-firming the feasibility of an affordable and portable au-tonomous photography solution.

Keywords

Computer Vision, OpenCV, Face Detec- tion, Servo Motor, Automated Photography, Raspberry Pi, Python, Digital Zoom, IoT.

Conclusion

PhotoBot successfully demonstrates an integrated ap- proach to autonomous group photography using low-cost commodity hardware and open-source computer vision software. By combining OpenCV-based face detection, servo motor-driven camera alignment, and adaptive digi- tal zoom, the system eliminates the perennial problem of group member exclusion from photographs without requir- ing cloud services, specialized sensors, or costly hardware. All defined objectives were met during prototype testing, and the FakeGPIO simulation architecture proves that the complete control pipeline can be validated independently of physical hardware. The project establishes a credible foundation for a commercially viable tourist photography kiosk that is safe, fast, portable, and accessible.

References

[1]A. Sharma, R. Singh, and P. Gupta, Using Int. J. Computer Applications, vol. 12, no. 4, pp. 23 29, 2022. [2]R. Patel, M. Shah, and K. Joshi, Recognition Based Attendance Proc. Int. Conf. on Machine Learn-ing, pp. 88 94, 2023. [3]S. Kumar, A. Rao, and -dance Journal of Mobile Comput-ing, vol. 8, no. 2, pp. 45 51, 2021. [4]R. Smith, J. Brown, and K. Lee, Photography Using Computer Int. J. Computer Science, vol. 10, no. 3, pp. 45 52, 2022. [5] – Proc. Int. Conf. on Embedded Systems, pp. 200 207, 2023. [6]G. Bradski and A. Kaehler, Learning OpenCV: Computer Vision with the OpenCV Library, 2nd ed. Sebastopol, CA: Media, 2013. [7] Available: https://docs.opencv.org, 2024. [8]R. C. Gonzalez and R. E. Woods, Digital Image Process-ing, 4th ed. New York, NY: Pearson, 2018. [9] -able: https://pypi.org/project/RPi.GPIO/,2024

How to Cite This Paper

Yadnesh Wagaskar, Sarthak Adhapure, Anushka Patil, Tanmay Patil (2026). PhotoBot: An Automated Smart Photography Robot Using Computer Vision and Servo-Controlled Camera Mechanism. International Journal of Computer Techniques, 13(3). ISSN: 2394-2231.

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