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Sensor Pen Documentation.md

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Documentation: Accelerometer-based Deviation Detection System

Overview:

The Accelerometer-based Deviation Detection System is a hardware and software solution designed to detect deviations in the Z-axis using an ADXL345 accelerometer. It provides real-time monitoring and feedback through an LED indicator. The system calculates the position change based on integrated acceleration readings, allowing for accurate detection of deviations.

Hardware Components:

  • Arduino board
  • ADXL345 accelerometer
  • Push button
  • LED
  • Resistors and wiring connections

Libraries:

  • Wire.h: Allows communication with I2C devices.
  • Adafruit_Sensor.h: Provides the sensor event structure.
  • Adafruit_ADXL345_U.h: Enables interaction with the ADXL345 accelerometer.

Constants:

  • ledPin: The pin connected to the LED indicator.
  • buttonPin: The pin connected to the push button.

Variables:

  • zPos: Represents the calculated Z-axis position coordinate.
  • prevTime: Tracks the previous time for calculating the time difference.
  • deviationOccurred: A flag that indicates if a deviation has occurred.
  • isPowerOn: A flag to track the power state of the system.

Functions:

  • setup(): Initializes the Serial Monitor, LED pin, push button pin, and the ADXL345 sensor.
  • loop(): Contains the main operations of the program. It reads accelerometer values, calculates the position change, detects deviations, and updates the LED and position variables accordingly.

Usage:

The provided code can be utilized in various real-life applications, including:

  1. Motion detection: The system can detect deviations or abnormal movements in a specific direction, enabling applications like intrusion detection or monitoring of sensitive equipment.
  2. Posture monitoring: By attaching the accelerometer to a wearable device, the system can track and alert users about incorrect posture or body movements.
  3. Fitness tracking: The system can monitor body movements during workouts, ensuring proper form and providing feedback on exercise effectiveness.
  4. Industrial safety: By attaching the system to machinery or equipment, it can detect deviations in movement patterns that may indicate potential malfunctions or safety hazards.
  5. Data collection: The system can be used to collect data on motion patterns in various scenarios, enabling further analysis and insights.

To adapt the code for specific applications, consider the following modifications:

  • Adjust the threshold value (4.0) in the if (abs(accelZ) > 4.0) statement to set the deviation detection sensitivity.
  • Customize the actions taken when a deviation occurs, such as sending notifications, triggering alarms, or logging data.
  • Integrate additional sensors or devices to enhance the functionality and broaden the scope of applications.

Note: This documentation provides a general overview of the code and its potential applications. Further modifications and integration may be necessary to adapt it to specific use cases and requirements.