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SafeLink Smartwatch Case Study

Abstract

The COVID-19 pandemic introduced challenges that called for innovative solutions to bridge physical and emotional gaps, especially for vulnerable populations. SafeLink is a smartwatch developed to monitor health metrics, detect falls, and transmit data to loved ones via a mobile app. This case study outlines the project’s goals, design methodology, system architecture, and testing outcomes. The results highlight SafeLink’s reliability and efficiency in providing essential health monitoring while ensuring ease of use and low power consumption.

Background

During the pandemic, health concerns and physical isolation exacerbated stress, especially for families of vulnerable individuals. SafeLink was conceived as a solution to address these challenges. The smartwatch provides continuous health monitoring, fall detection, and real-time data sharing with loved ones. The combination of a user-friendly mobile application and an efficient hardware platform ensures both usability and performance.

Project Goals and Design

Goals:

  1. Provide real-time health monitoring, including heart rate, blood oxygen levels, and temperature.
  2. Detect falls accurately and notify the user’s loved ones.
  3. Minimize power consumption to enable extended use.
  4. Integrate a companion mobile app for real-time data display and user account management.

Design Approach:
The project was broken down into three main components:

  1. Hardware Development: Selecting and integrating sensors and microcontrollers for reliable data collection.
  2. Software Development: Designing the mobile application for data visualization and user interaction.
  3. Power System Design: Optimizing the battery and circuit to achieve extended runtime.

System Designs and Requirements

  1. Microcontroller Requirements:
    • Measure health metrics (heart rate, blood oxygen, temperature) with high accuracy.
    • Implement fall detection and allow user response to avoid false positives.
    • Support connectivity via BLE or WiFi to transmit data to Firebase.
  2. Application Requirements:
    • Provide real-time visualization of health metrics.
    • Ensure secure user account management and authentication.
    • Be compatible with multiple platforms (iOS, Android).
  3. Power System Requirements:
    • Support low-power operation with deep sleep modes.
    • Provide stable power using a USB-C interface and voltage regulators.
    • Include protection circuits for charging safety.

System Architecture Design

Hardware Design:
The system is centered on a microcontroller connected to sensors:

  • MAX30102 BPM Sensor for heart rate and oxygen level.
  • ADT7410 Temperature Sensor for body temperature.
  • MPU6050 Accelerometer for fall detection.
  • DS3231 RTC module  for Date and Time Tracking
  • Vibration Motor for Notification

Software Design:
The software stack comprises:

  1. Firmware on the microcontroller to process sensor data and transmit it to Firebase.
  2. A mobile application built using Xamarin Studio and Visual Studio IDE, featuring:
    • Real-time data display.
    • User account management.
    • Notifications for critical health events.

Power Management:

  • A 3.7V, 1000mAh battery supports extended runtime.
  • USB-C interface for charging and programming.
  • Voltage regulators step down power for safe operation of the microcontroller and sensors.

Results and Testing

Testing Metrics:

  1. Health Metric Accuracy:
    • Heart rate and blood oxygen measured with ~85% accuracy compared to standard devices.
    • Temperature readings accurate to ±0.5°C.
  2. Fall Detection:
    • False positives reduced with a 30-second user acknowledgment mechanism.
    • Reliable fall detection observed in 90% of test scenarios.
  3. Power Consumption:
    • The system consumed less than 40mA during operation, enabling up to 25 hours of continuous use.
  4. Application Functionality:
    • Firebase integration allowed real-time data synchronization.
    • Authentication and user management systems performed without issues.

Performance Analysis

  • Health Monitoring:
    Data collected by the sensors was transmitted to Firebase with minimal latency, ensuring real-time updates in the application.
  • Battery Life:
    Deep sleep modes significantly extended battery life, achieving over 24 hours of operation on a single charge.
  • Fall Detection:
    The accelerometer, combined with software algorithms, achieved a high level of accuracy while maintaining low power usage.
  • Application:
    The use of Xamarin and Firebase provided a smooth user experience with minimal downtime and seamless multi-platform support.

Conclusion

SafeLink successfully addresses the challenges posed by the COVID-19 pandemic by offering a reliable, user-friendly smartwatch system. With accurate health monitoring, fall detection, and real-time data sharing, SafeLink alleviates the stress of physical separation for families of vulnerable individuals. The project demonstrates how thoughtful design and integration of hardware and software can result in a cost-effective, efficient, and impactful health monitoring solution. Future improvements could focus on further enhancing sensor accuracy and integrating advanced features such as ECG monitoring or AI-driven predictive analytics.

 

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