Published Paper Details:

The main objective of this project is to designand implement a user-friendly and accessible mobile application capable of detecting hidden spy cameras in sensitive environments such as hotels, rental properties, and changing rooms. Our system leverages advanced artificial intelligence (AI) models, deep learning, and computer vision techniques to identify camera lenses through reflection analysis. Using a smartphone's camera, the system captures live video frames, applies preprocessing, and employs a Convolutional Neural Network (CNN) to classify whether reflections correspond to spy cameras or harmless objects. The platform provides real-time alerts through sound or vibration, making it practical for non-technical users. Additionally, in its second phase, the system incorporates Wi-Fi signal analysis to identify active hidden cameras within a range of up to 30 meters, further strengthening detection accuracy. By combining optical reflection analysis with wireless signal monitoring, this project presents an innovative and portable solution to counteract privacy invasion. Ultimately, the application aims to enhance personal safety, encourage responsible use of surveillance technology, and contribute to a more secure and trustworthy digital society. Future extensions may include improved detection in poor lighting conditions and support for deployment across multiple device platforms.