RYE: A NodeMCU - Based Spy Camera Detector for Enhancing Personal Privacy Dr. K. Vinuthna Reddy Department of CSE(AI&ML) Neil Gogte Institute of Technology, (Affiliated to Osmania University) Hyderabad, India vinuthnareddy@gmail.com Ravipati Rohi Mouktik Department of CSE(AI&ML) Neil Gogte Institute of Technology (Affiliated to Osmania University) A.Jayakrishna Department of CSE(AI&ML) Neil Gogte Institute of Technology (Affiliated to Osmania University) Hyderabad, India jayakrishna85200 @gmail.com Akavaram Aashish Reddy Department of CSE(AI&ML) Neil Gogte Institute of Technology (Affiliated to Osmania University) Hyderabad, India aashish.avk@gmail.com Hyderabad, India rohimouktikravipati @gmail.com Abstract — Hidden surveillance devices are becoming a serious concern in both public and private spaces. This paper introduces RYE, a compact and affordable spy camera detector built using the NodeMCU ESP32 microcontroller. It uses an infrared (IR) sensor to detect a ctive camera lenses and an MH Hall effect sensor to identify hidden electronic devices through their magnetic fields. When a device is detected, a buzzer alerts the user, and the event is logged with a timestamp using a Real - Time Clock (RTC) module. RYE al so creates a Wi - Fi hotspot and hosts a local web server, allowing users to access detection logs via a browser without needing internet access. This system provides a practical solution for enhancing personal privacy through real - time detection and logging of hidden surveillance threats. Keywords — Spy Camera Detector, Privacy, Counter - Surveillance, ESP32, NodeMCU, Infrared (IR) Sensor, Hall Effect Sensor, RTC, Local Web Server, IoT. I. I NTRODUCTION The proliferation of miniaturized and easily disguised surveillance cameras poses a significant and growing threat to individual privacy. These devices can be hidden in seemingly innocuous objects, making visual searches unreliable. The primary purpose of the RYE project is to enhance personal safety , with a special focus on protecting individuals in vulnerable environments such as changing rooms, hostels, and public washrooms. Existing solutions often present challenges, as professional - grade tools are expensive and complex, while affordable detector s often rely on a single, less effective detection method. RYE aims to address these gaps by providing an accessible, affordable, and multi - modal detection tool that empowers non - technical users to identify potential threats. II. LITERATURE REVIEW The paper [1] by Mohammad Shaik et al. provides a framework for detecting and jamming hidden cameras using IoT and RF signal scanning. It explores how to identify active wireless cameras by their radio transmissions. While RF scanning was not implemented in th e final RYE prototype to maintain low cost and a focus on passive devices, this research provided foundational knowledge on counter - surveillance techniques against transmitting devices. In the paper [2] authored by N. Safira et al., the use of infrared (IR ) light reflection for privacy protection using an Arduino is discussed. The paper highlights a practical method for creating a hardware module to detect the unique reflections from a camera's lens, regardless of whether the camera is active or powered off . This work was invaluable and directly guided the development of RYE’s core IR detection module. Paper [3], written by Xiaodong Yang et al., explores the interpretation of signature waveform characteristics for magnetic target detection. This research pro vided the scientific basis for using a Hall effect sensor in our project. It demonstrated that active electronic devices emit a distinct magnetic signature, which informed our decision to incorporate a Hall sensor into RYE to "sniff out" powered - on cameras , adding a crucial second layer to its detection capabilities. In paper [4], authored by T. Sravani et al., a straightforward implementation of an Arduino - based spy camera detector using IR sensors and a buzzer is presented. This paper demonstrated a simpl e and user - friendly approach to detection and alerts. The inclusion of an immediate, audible alert via a buzzer directly inspired the intuitive feedback and alarm system built into the RYE prototype. The paper [5] by Sun Bangjie et al. focuses on using sma rtphone Time - of - Flight (ToF) sensors for hidden camera detection. It explores how to leverage sensors already present in modern phones for privacy applications. This paper was reviewed to understand alternative and mobile - centric detection methods, which h ave informed the potential future scope for a mobile version of RYE. The study in paper [6] by Aleksey Bychkov et al. examines the use of an active laser detection system for recognizing surveillance devices with high precision. This research, while more a dvanced than the scope of our project, provided insights into professional - grade detection methods and informed the design considerations for future, more sophisticated versions of RYE. Finally, paper [7] by Sang - Yoon Lee et al. discusses AI - aided hidden camera detection based on analyzing raw IoT network traffic. This paper showed how Artificial Intelligence can be leveraged for network - level surveillance detection. This cutting - edge app roach was instrumental in shaping the long - term vision and future scope for the RYE project, pointing toward a more intelligent and automated prototype. Refere nce Author s Detecti on Method Key Contribut ion Influene on RYE Project [1] Moham mad Shaik et al. RF Signal Scannin g & Jammin g Provides a framework for detecting and jamming active wireless cameras using IoT. Provided foundatio nal knowled ge, but the method was not impleme nted to maintain low cost. [2] N. Safira et al. Infrared (IR) Light Reflecti on D emonstra tes a practical method to detect camera lenses with an Arduino, regardless of power state Directly guided the develop ment of the core IR detection module. [3] Xiaodon g Yang et al. Magneti c Field Explores the interpretati Provided the scientific Detectio n on of unique magnetic signatures from electronic devices. basis for incorpora ting a Hall effect sensor. [4] T. Sravani et al. IR Sensor with Buzzer Presents a simple, user - friendly detector implement ation with an immediate audible alert. Inspired the intuitive feedback and alarm system. [5] Sun Bangjie et al. Smartph one Time - of - Flight (ToF) Sensors Explores leveraging built - in smartphon e sensors for privacy application s. Informed the potential future scope for a mobile version. [6] Aleksey Bychko v et al. Active Laser Detectio n Examines a high - precision laser system for recognizin g surveillanc e devices. Provided insights for future, more sophistic ated versions. [7] Sang - Yoon Lee et al. AI - aided Networ k Traffic Analysi Shows how AI ca n be used to detect cameras by analyzing raw network traffic. Shaped the long - term vision for a more intelligen t prototype Table 2.1 Comparison of existing systems how it helped us to build RYE. III. PROPOSED METHODOLOGY The proposed system, RYE, is designed to be a portable, multi - modal spy camera detector. The methodology is centered on integrating two different low - cost sensors to identify potential surveillance threats based on distinct physical properties. The system employs an infrared (IR) sensor to detect the unique reflections from camera lenses or the IR light emitted by night - vision cameras. Simultaneously, a Hall effect sensor is used to detect the magnetic fields produced by active electronic components within hidden devices. When a threat is detected, the system provides an immediate audible alert and logs the event with a precise timestamp. The user can access these logs via a secure, local web server hosted on the device itself, ensuring privacy and accessibi lity without needing an internet connection IV. FEASIBILITY STUDY A feasibility study concluded that the RYE project is viable across technical, economic, and operational domains. • Technical Feasibility : The project is technically sound, utilizing readily available and well - documented components like the ESP32 microcontroller and common sensors (IR, Hall effect), all programmable within the standard Arduino IDE. • Economic Feasibility : The use of low - cost, off - the - shelf components makes the device hig hly affordable, aligning with the project's goal of providing an accessible privacy tool. • Operational Feasibility : The device addresses a clear and growing need for personal privacy protection. Its simple operation (power on, connect, and scan) makes it su itable for non - technical users in various environments. V. SYSTEM ARCHITECTURE Figure 5. 1: Architectur e of RYE System The "RYE Spy Camera Detector" employs a centralized architecture with the ESP32 NodeMCU microcontroller serving as the core processing unit, orchestrating sensor data acquisition, event processing, and alert generation. Input Layer: This layer consists of the sensors that gather environmentral data and time information. IR (Infrared) Sensor: A Passive Infrared (PIR) type sensor responsible for detecting motion by sensing changes in infrared radiation indicative of human presence. It typically provides a digital HIGH/LOW signal to the ESP32. Hall Effect Sensor: Detects the presence or absence of a magnetic field. It can be used to monitor the status of an enclosure (e.g., door/drawer open/closed) or detect the proximity of a magnetic object. It provides a digital or analog signal to the ESP32. RTC (Real - Time Clock) Module (e.g., DS3231): An independent timekeeping chip that maintains accurate date and time, communicating with the ESP32 via the I2C (Inter - Integrated Circuit) protocol. It ensures precise timestamping of events even if the ESP32 loses power. Processing Layer: This is the brain of the system. ESP32 NodeMCU: This powerful microcontroller performs the following tasks: Reads input signals from the IR and Hall effect sensors. Retrieves the current date and time from the RTC module. Executes the core firmware logic, which includes algorithms to analyze sensor data against predefined rules and time - based conditions to ide ntify potentially suspicious events. Manages the logging of detected events with their timestamps. Controls the output alert mechanism (buzzer). Output Layer: This layer provides feedback to the user. Buzzer: An active buzzer that generates an immediat e, audible alarm when triggered by the ESP32 upon detection of a suspicious event. Serial Monitor Interface: During development and for diagnostic purposes, the ESP32's serial output (viewed via a connected computer) is used to display detailed logs of se nsor readings, detected events, system status messages, and timestamps. Power Supply Unit (PSU): Provides the necessary regulated DC power to the ESP32 NodeMCU and, through it or directly, to all connected sensors and modules. VI. IMPLEMENTATION Component Pin ESP32 Pin Function MH Hall Sensor VCC 3.3V Power GND GND Ground OUT GPIO35 Digital Input IR Sensor VCC 3.3V Shared Power GND GND Shared Ground OUT GPIO34 Digital Input Active Buzzer (+) GPIO13 Control (−) GND Ground RTC (DS3231) VCC 3.3V Shared Power GND GND Shared Ground SDA GPIO18 I²C Data SCL GPIO19 I²C Clock Table 6.1 Showing Connection Wiring This table details the wiring connections for the RYE (Spy Camera Detector) project, explaining how each hardware component is connected to the ESP32 microcontroller. Here’s a breakdown of the connections: Sensor Connections • MH Hall Effect Sensor : This sensor detects magnetic fields. It's powered by the ESP32's 3.3V pin, and its data output (OUT) pin is connected to the ESP32's GPIO35 to send a digital input signal. • IR Sensor : This sensor detects infrared light. It shares the same 3.3V power and ground l ines as the Hall sensor. Its data output (OUT) pin is connected to GPIO34, also as a digital input. Output and Module Connections • Active Buzzer : This component produces an audible alert. Its positive pin (+) is connected to GPIO13, which acts as a control pin to turn the buzzer on or off. The negative pin ( - ) is connected to ground. • RTC (DS3231 Real - Time Clock) : This module keeps track of the time. It is connected to the ESP32 via the I²C communication protocol. The SDA (Data) pin connects to GPIO18, and th e SCL (Clock) pin connects to GPIO19. Like the other sensors, it is powered by the 3.3V pin. Figure 6.1.2 Showing Real Connections of the circuit Fig 6.1.3 Uploading sketch to the device Uploading Process 1.Compile the Sketch o Open your Arduino IDE. Load your .ino sketch file. Select the correct board: Tools → Board → ESP32 Dev Module Select the correct port: Tools → Port → [Your ESP32 Port] Click the Verify button to compile the code. 2.Upload the Sketch Click the Upload button in the IDE. During “Connecting...” phase, if uploading doesn’t start: Press and hold the BOOT button on the ESP32. Release it after upload starts. 3.Open Serial Monitor o Click Tools → Serial Monitor or use the shortcut Ctrl+Shift+M. Set the baud rate to match your sketch (usually 9600 or 115200). 4.Press the Reset Button Press the EN (Reset) button on the ESP32 once upload is complete. The ESP32 will reboot and start running your program. VII. RESULTS To validate the system's performance in a practical setting, the RYE prototype was tested on real - world covert surveillance devices. Specifically, we tested it on a real spy pen camera and a spy camera adapter. The system was successful in identifying both devices, with the dual - sensor approach proving effective. Upon detection, the device correctly triggered the audible buzzer alert and created a timestamped entry in the detection log, confirming the functionality of the complete alert and logging system. Figure 7.1.1 Testing on Real Spy Pen Camera and Spy Camera Adapter Fig 7.1.2 Showing actual result we got while we tested on Real Devices Fig 7 .1.3 Login User Interface of RYE It is a simple login system,Where Admin and user can login or register Fig 7 .1.4 Admin User Interface of RYE Admin has a special feature that they can view users or delete users.It will help in monitoring data Fig 7 .1.5 Showing Detection Logs It is a special feature o f RYE where users can download detection logs ,including timestamps with the exact detection logs occurred. VIII. CONCLUSION The RYE Spy Camera Detector project successfully developed an accessible, affordable, and user - friendly tool to address the growing concern of privacy violations from hidden surveillance devices. The functional prototype, built on the NodeMCU ESP32, effect ively integrates a dual - sensor approach, using an infrared (IR) sensor and a Hall effect sensor to identify a range of potential threats. Key achievements of the project include the implementation of an immediate audible alert, accurate timestamped event l ogging via an RTC module, and a secure, local Wi - Fi web server for viewing logs without needing internet access. The project's merits lie in its affordability, portability, and its unique local logging feature that enhances user privacy. While the prototyp e proved viable, it has limitations, primarily the absence of Radio Frequency (RF) detection, meaning it cannot identify all types of wireless transmitting devices. Despite this, the RYE detector represents a valuable contribution to personal security, pro viding a tangible means for individuals to proactively safeguard their privacy. IX. ACKNOWLEDGEMENT We would like to express our sincere gratitude to our project guide, Dr. K. Vinuthna Reddy. Her invaluable guidance, constant encouragement, and insightfu l feedback were instrumental in the successful completion of this project X. REFERENCES 1. Shaik, Mohammad & Fathima, Syeda & Kounte , M. (2022). "Efficient Framework for Hidden Camera Detection and Jamming Using IoT." International Journal of Research in Engineering and Science (IJRES) 2. Safira, N. & Aprilia, S. & Handayani, A. & Bachtiar , M. (2020). "Infrared Camera Detector for Privacy Protection using Arduino." International Journal of Engineering Research and Technology (IJERT) 3. Yang, Xiaodong & Zhang, Xiaoyu & Zhang, Lei & Liu, Shen. (2019). "Interpretation of Signature Waveform Chara cteristics for Magnetic Target Detection." 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