Hidden Device Detector

Abstract-With the rise in unauthorized surveillance and privacy breaches, detecting hidden devices such as cameras and microphones has become a necessity. This project presents a *software-based mobile application* designed to detect hidden devices using multiple techniques, including *AI-driven image recognition, infrared detection, RF signal analysis and network scanning. Unlike conventional hardware-based detectors, this app leverages smartphone sensors, machine learning, and wireless network analysis to **locate hidden cameras, microphones, and unauthorized recording devices* in various environments. A unique feature of this application is the *SOS functionality, allowing users to report their findings to the nearest authorities anonymously. The app also includes a **jamming feature, which disrupts unauthorized recordings to protect user privacy. This is particularly beneficial for individuals who fear filing complaints in person. Additionally, the app can **analyze network traffic* to detect unusual device behavior, ensuring comprehensive security.By integrating multiple detection methods, the app provides *enhanced accuracy compared to traditional detection tools. It is designed to be lightweight, user-friendly, and compatible with most modern smartphones. This project aims to **empower users with an accessible, software-driven solution* for personal security and privacy protection in an increasingly surveillance-prone world. Keywords Hidden device detection, AI-based anomaly detection, RF scanning, infrared camera analysis, privacy protection, SOS emergency feature, mobile security, surveillance jamming, unauthorized recording prevention.