IoT and ML-Embedded sitting posture monitoring system.

  • Purpose Research and social awareness
  • Date 15 jan 2023
  • Services Help prevent discomfort or injuries associated with poor sitting positions.
  • Thanks BUBT, JU, Media, DU, BUET

Objective : Developed a visual system for a smart chair to detect and monitor sitting posture through mobile applications can have several potential benefits. It could promote better posture habits, provide feedback for ergonomic improvements, and potentially help prevent discomfort or injuries associated with poor sitting positions.

Here’s an overview of the steps involved:

  1. Define requirements: Determine the specific features and functionalities you want to incorporate into your smart chair. Consider posture monitoring, real-time feedback, alert generation, and mobile integration for notifications.

  2. Hardware selection: Choose the necessary hardware components for your smart chair, including sensors for posture detection (e.g., pressure sensors, accelerometers), a microcontroller or single-board computer (e.g., Arduino, Raspberry Pi), connectivity modules (e.g., Wi-Fi, Bluetooth), and a power source.

  3. Sensor integration: Install the posture detection sensors within the chair, ensuring optimal placement to capture accurate posture data. Connect the sensors to the microcontroller or single-board computer for data acquisition.

  4. Data acquisition and processing: Develop software to read data from the posture sensors connected to the microcontroller. Process the sensor data to analyze sitting posture using machine learning algorithms or rule-based approaches.

  5. Real-time feedback: Implement a mechanism to provide real-time feedback to the user about their sitting posture. This can involve visual indicators, sounds, or vibrations integrated into the chair. Use the analyzed data to determine correct and incorrect postures.

  6. Connectivity: Enable the smart chair to connect to a network or a mobile device. Implement connectivity modules such as Wi-Fi or Bluetooth to establish communication between the chair and the mobile device.

  7. Mobile app development: Create a mobile application that can receive posture data from the chair and send alerts to the user’s mobile device. The app should display real-time posture information, generate alerts for poor posture, and provide recommendations for posture correction.

  8. Alert generation: Determine the conditions for generating alerts based on poor posture detection. For example, if the user maintains an incorrect posture for a specified duration, trigger an alert to their mobile device, reminding them to change their position.

  9. Data storage and analysis: Set up a database or cloud storage to store the collected posture data. Perform further analysis on the data to identify long-term trends, generate insights, and potentially provide personalized recommendations for improving posture.

  10. Testing and refinement: Thoroughly test the smart chair’s functionality, accuracy of posture detection, alert generation, and mobile integration. Collect user feedback to identify areas for improvement and refine the system accordingly.

Ensure user privacy and data security throughout the development process, including encryption and secure communication between the chair, microcontroller, and mobile device.

Note: Developing an IoT and ML-based smart chair requires expertise in hardware integration, software development, and machine learning. Consider collaborating with experts or seeking guidance from communities specializing in IoT, ML, or hardware projects if needed.