Smart Mirror With Voice & Face Detection

Smart Mirror

Programming Languages / Tools Used

Introduction

The Smart Mirror project aims to seamlessly integrate daily information into a household setting while providing an interactive and convenient user interface. By leveraging the OpenCV library with Python, the smart mirror offers real-time facial detection and classification, enabling a personalized experience for each user. The custom user interface, developed using HTML, CSS, and JavaScript, displays essential widgets such as weather forecasts and calendar events. Voice control integration through the Amazon Alexa API allows users to access information and control smart home devices using simple voice commands. Essential hardware components, including a 27-inch display, Raspberry Pi 4, and PIR motion sensor, were selected and integrated to create an efficient and user-friendly device. This design not only enhances daily living but also reduces electricity running costs by 20%, demonstrating the potential of smart home technology in modern households.

Features and Functionality

  • Real-Time Facial Detection:

    • Utilized OpenCV library with Python for real-time facial detection and classification.
    • Personalized user experience based on facial recognition.
    • Developed widgets for a broader range of information and functionalities, such as news feeds, fitness tracking, and personalized reminders.
  • Custom User Interface:

    • Developed using HTML, CSS, and JavaScript.
    • Displays widgets such as weather forecasts, calendar events, and other relevant daily information.
    • Interactive and user-friendly design for seamless integration into household settings.
    • Developed a companion mobile app to allow remote control and customization of the smart mirror interface.
    • Enabled notifications and updates to be pushed from the mobile app to the smart mirror.
  • Voice Control Integration:

    • Integrated with Amazon Alexa API for voice control functionality.
    • Allows users to access information and control smart home devices using voice commands.
    • Enhances user convenience and interaction with the smart mirror.
  • Energy Efficiency:

    • Incorporated a PIR motion sensor to detect presence and reduce electricity running costs by 20%.
    • The display activates only when motion is detected, optimizing energy usage.

How it works

Smart Mirror Design Methodology:

The system starts and the monitor is on standby.

If motion is detected by the PIR sensor, the system checks if the face detected by the Pi camera is saved on file. If the face is recognized, the monitor displays all smart mirror modules (customized information for the user). If the face is not recognized, the monitor displays basic smart mirror modules (generic information).

After displaying the appropriate modules, the system allows for voice detection using the microphone. The logic of the smart mirror is implemented using Python and/or JavaScript, which runs on the Raspberry Pi.

Raspberry Pi components:

Raspberry Pi acts as the hub that processes input from the sensors and camera, runs the software, and controls the display on the monitor.

The integration of voice control through the Amazon Alexa API adds another layer of convenience, allowing users to access information and control smart home devices effortlessly. 

Pi camera allows features for multi-user support and security.

Enhance voice control capabilities with natural language processing to understand more complex commands and conversations.

Smart Mirror Remote Control:

The smart mirror can interact with a mobile device connected on the same or a different network, allowing for additional control or configuration.

PIR Sensor Energy Consumption:

Smart Mirror Final Year Project Presentation At Brunel University London

Future Improvements

 

  • Improve facial recognition accuracy and speed with advanced machine learning algorithms and an infrared camera to work in poorly lit scenarios.
  • Add video-playing functionality to the Smart Mirror to play Youtube videos.
  • Anti fog technology so that the smart mirror can be used in a bathroom without any issues in terms of viewing the display information.

Conclusion

 

The development of the Smart Mirror has been a transformative project, combining modern technology with daily convenience. By leveraging the OpenCV library with Python for real-time facial detection and creating a custom user interface with HTML, CSS, and JavaScript, the Smart Mirror provides a personalized and interactive experience. The integration of voice control through the Amazon Alexa API adds another layer of convenience, allowing users to access information and control smart home devices effortlessly. With the inclusion of essential hardware components and energy-efficient design, this project not only enhances daily living but also promotes sustainability. Moving forward, there are numerous opportunities for further enhancement, from improving facial recognition and expanding widget functionalities to integrating mobile app support and advanced energy management. This project highlights the potential of smart home technology in enriching everyday life and provides a solid foundation for continued innovation and improvement.

Smart Mirror Poster

Copyright © 2024 | Anish Patel

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