GoDiary
Autonomous Fitness Activity Tracking with Machine Learning

What is GoDiary?

GoDiary revolutionizes fitness tracking through its innovative Autonomous Fitness Detection Engine (AFDE), which combines GPS technology with proprietary machine learning algorithms to automatically track workouts without user intervention. The app specializes in detecting runs, walks, and rides with impressive accuracy while maintaining optimal battery efficiency.

The platform offers comprehensive fitness monitoring capabilities, including detailed time-series analysis, personalized goal tracking, and seamless integration with Apple Health for iOS users. GoDiary's sophisticated technology ensures accurate start and stop detection of activities, while also providing options for manual tracking when needed.

Features

  • Autonomous Detection: Proprietary machine learning algorithms for automatic workout tracking
  • Battery Efficiency: Optimized power consumption during activity monitoring
  • Historical Analysis: Time-series graphs with weekly, monthly, and yearly views
  • Goal Tracking: Customizable time-based and distance-based fitness goals
  • Apple Health Integration: Seamless data syncing for iOS users

Use Cases

  • Tracking daily running sessions
  • Monitoring walking activities
  • Recording cycling workouts
  • Analyzing fitness progress over time
  • Setting and achieving fitness goals

FAQs

  • What happens when AFDE is turned off?
    When AFDE is turned off, GoDiary will no longer automatically detect walks, runs, or rides. The app will operate as a standard fitness tracker requiring manual intervention, and there will be reduced battery drain.
  • Why does GoDiary need location 'Always Allow' authorization?
    Location services are required to accurately track workout locations, measure speed, and calculate distance during activities. This permission is essential for the auto-detection features to function properly.

Related Queries

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GoDiary Uptime Monitor

Average Uptime

100%

Average Response Time

296.03 ms

Last 30 Days

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