Detecting Hidden Cameras through a Smart Watch

Authors

  • N Bhargav Krishna Assistant Professor, CSE(AI&ML),Vignan's Institute of Management and Technology for Women, Hyderabad, India. Author
  • P. M. Archana Devi B.Tech 3rd year Student, CSE (AI&ML), Vignan's Institute of Management and Technology for Women, Hyderabad, India. Author
  • ReddyShetty Bhavana B.Tech 3rd year Student, CSE (AI&ML), Vignan's Institute of Management and Technology for Women, Hyderabad, India. Author
  • Sambari Ranitha B.Tech 3rd year Student, CSE (AI&ML), Vignan's Institute of Management and Technology for Women, Hyderabad, India. Author
  • Malipeddi Akshitha B.Tech 3rd year Student, CSE (AI&ML), Vignan's Institute of Management and Technology for Women, Hyderabad, India. Author
  • Kannamataneni Krishna Pravalika B.Tech 3rd year Student, CSE (AI&ML), Vignan's Institute of Management and Technology for Women, Hyderabad, India. Author
  • Dr.M Thejovathi B.Tech 3rd year Student, CSE (AI&ML), Vignan's Institute of Management and Technology for Women, Hyderabad, India. Author

Keywords:

Hidden Camera Detection, Smartwatch, ESP32, Infrared Reflection, RF Signal Detection, Magnetic field sensing, Thermal detection, Privacy Protection, Wearable Technology.

Abstract

Hidden cameras are a growing threat to privacy, making it important to detect them easily. This project introduces a smartwatch-based hidden camera detector that provides a wearable and real-time solution for finding hidden cameras. ESP32 chips power this smartwatch and use Infrared reflection, RF signal detection, magnetic field sensing, and thermal detection. When a hidden camera is detected, the smartwatch instantly alerts the user with vibrations and screen notifications. This device is small, easy to use, energy-efficient, wearable, and cost-efficient. The solution provides a practical tool for enhancing personal wearable devices and is cost-efficient. The solution offers a practical tool for enhancing personal development.

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References

A. Pravin, T. P. Jacob, K. Mohana Prasad, T. Judgi, and N. Srinivasan, "Efficient Framework for Hidden Camera Detection & Jamming using IoT," in Proceedings of the 6th International Conference on Trends in Electronics and Informatics (ICOEI 2022), Chennai, India, 2022, pp. 634–637. doi:10.1109/ICOEI53556.2022.9776943.

2. D. Dao, M. Salman, and Y. Noh, "DeepDeSpy: A Deep Learning-Based Wireless Spy Camera Detection System," IEEE Access, vol. 9, pp. 145486–145497, 2021, doi: 10.1109/ACCESS.2021.3121254

3. Thejovathi, Murari, and M. V. P. Chandra Sekhara Rao. 2024. “An Integrated Approach for Time Series Forecasting of High-Demand Haircare Products in Rural and Urban Areas Using Machine Learning and Statistical Techniques”. International Journal of Intelligent Systems and Applications in Engineering 12 (3):154-63. https://ijisae.org/index.php/IJISAE/article/view/5233.

4. Das, Bappaditya, Thejovathi Murari, Chandan Das, and P. Rajeswari. "Big Data Mining And Clustering Using Distributed Bayesian Matrix Decomposition." In 2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT), pp. 1-6. IEEE, 2023.

5. Thejovathi, Murari, M. V. P. ChandraSekharaRao, E. J. Priyadharsini, Someshwar Siddi, B. Karthik, and Syed Hauider Abbas. "Optimizing Product Demand Forecasting with Hybrid Machine Learning and Time Series Models: A Comparative Analysis of XGBoost and SARIMA." EJ and Siddi, Someshwar and Karthik, B. and Abbas, Syed Hauider, Optimizing Product Demand Forecasting with Hybrid Machine Learning and Time Series Models: A Comparative Analysis of XGBoost and SARIMA (November 15, 2024) (2024).

6. T. Shah and M. Sharma, "Spy Cam Detection," GitHub repository.

https://github.com/tanishq396/Spy_Cam_Detection

7. D. Dharva, "Spy Camera Dataset," Roboflow Universe, Dec. 2022. https://universe.roboflow.com/dharva/spy-camera

8. A. Pravin, T. P. Jacob, K. Mohana Prasad, T. Judgi, and N. Srinivasan, "Efficient Framework for Hidden Camera Detection & Jamming using IoT," in Proceedings of the 6th International Conference on Trends in Electronics and Informatics (ICOEI 2022), Chennai, India, 2022, pp. 634–637. doi:10.1109/ICOEI53556.2022.9776943.

9. A. S. Gaikwad and P. S. Walia, "ESPÍA: A Review of Application to Detect Spy Camera Implementation," Int. Res.J. Mod. Eng. Technol. Sci., vol. 5, no 6, pp. 1–6, Jun. 2023. https://www.irjmets.com/uploadedfiles/paper/issue_6_june_20 23/42296/final/fin_irjmets1687328741.pdf

10. Thejovathi, MURARI, and M. C. Rao. "Evaluating the performance of xgboost and gradient boost models with feature extraction in fmcg demand forecasting: A feature-enriched comparative study." J. Theor. Appl. Inf. Technol 102 (2024): 4158-4163.

11. D Shanthi, Smart Healthcare for Pregnant Women in Rural Areas, Medical Imaging and Health Informatics, Wiley Publishers,ch-17, pg.no:317-334, 2022, https://doi.org/10.1002/9781119819165.ch17

12. Shanthi, R. K. Mohanty and G. Narsimha, "Application of machine learning reliability data sets", Proc. 2nd Int. Conf. Intell. Comput. Control Syst. (ICICCS), pp. 1472-1474, 2018.

13. D Shanthi, N Swapna, Ajmeera Kiran and A Anoosha, "Ensemble Approach Of GPACOTPSOAnd SNN For Predicting Software Reliability", International Journal Of Engineering Systems Modelling And Simulation, 2022.

14. Shanthi, "Ensemble Approach of ACOT and PSO for Predicting Software Reliability", 2021 Sixth International Conference on Image Information Processing (ICIIP), pp. 202-207, 2021.

15. D Shanthi, CH Sankeerthana and R Usha Rani, "Spiking Neural Networks for Predicting Software Reliability", ICICNIS 2020, January 2021, [online] Available: https://ssrn.com/abstract=3769088.

16. Shanthi, D. (2023). Smart Water Bottle with Smart Technology. In Handbook of Artificial Intelligence (pp. 204-219). Bentham Science Publishers.

17. Shanthi, P. Kuncha, M. S. M. Dhar, A. Jamshed, H. Pallathadka and A. L. K. J E, "The Blue Brain Technology using Machine Learning," 2021 6th International Conference on Communication and Electronics Systems (ICCES), Coimbatre, India, 2021, pp. 1370-1375, doi: 10.1109/ICCES51350.2021.9489075.

18. Shanthi, D., Aryan, S. R., Harshitha, K., & Malgireddy, S. (2023, December). Smart Helmet. In International Conference on Advances in Computational Intelligence (pp. 1-17). Cham: Springer Nature Switzerland.

19. Babu, Mr. Suryavamshi Sandeep, S.V. Suryanarayana, M. Sruthi, P. Bhagya Lakshmi, T. Sravanthi, and M. Spandana. 2025. “Enhancing Sentiment Analysis With Emotion And Sarcasm Detection: A Transformer-Based Approach”. Metallurgical and Materials Engineering, May, 794-803. https://metall-mater-eng.com/index.php/home/article/view/1634.

20. Narmada, J., Dr.A.C.Priya Ranjani, K. Sruthi, P. Harshitha, D. Suchitha, and D.Veera Reddy. 2025. “Ai-Powered Chacha Chaudhary Mascot For Ganga Conservation Awareness”. Metallurgical and Materials Engineering, May, 761-66. https://metall-mater-eng.com/index.php/home/article/view/1631.

21. Geetha, Mrs. D., Mrs.G. Haritha, B. Pavani, Ch. Srivalli, P. Chervitha, and Syed. Ishrath. 2025. “Eco Earn: E-Waste Facility Locator”. Metallurgical and Materials Engineering, May, 767-73. https://metall-mater-eng.com/index.php/home/article/view/1632.

22. P. Shilpasri PS, C.Mounika C, Akella P, N.Shreya N, Nandini M, Yadav PK. Rescuenet: An Integrated Emergency Coordination And Alert System. J Neonatal Surg [Internet]. 2025May13 [cited

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Published

2025-06-01

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How to Cite

Detecting Hidden Cameras through a Smart Watch. (2025). International Journal of Multidisciplinary Engineering In Current Research, 10(6), 413-421. https://ijmec.com/index.php/multidisciplinary/article/view/818