A Machine Learning based location recording and activity detection framework for iOS. Combined, simplified Core Location and Core Motion recording. Filtered, smoothed, and simplified location and motion data. Near real-time stationary / moving state detection. Automatic energy use management, enabling all-day recording. Automatic stopping and restarting of recording, to avoid wasteful battery use. Machine Learning-based activity type detection. Improved detection of Core Motion activity types (stationary, walking, running, cycling, automotive). Distinguish between specific transport types (car, train, bus, motorcycle, airplane, boat). Optionally produce high level Path and Visit timeline items, to represent the recording session at human level. Similar to Core Location's CLVisit, but with much higher accuracy, much more detail, and with the addition of Paths (ie the trips between Visits).

Features

  • Combined, simplified Core Location and Core Motion recording
  • Filtered, smoothed, and simplified location and motion data
  • Near real time stationary / moving state detection
  • Automatic energy use management, enabling all day recording
  • Automatic stopping and restarting of recording, to avoid wasteful battery use
  • Location recording and activity detection framework for iOS

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License

GNU Library or Lesser General Public License version 3.0 (LGPLv3)

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Additional Project Details

Programming Language

Swift

Related Categories

Swift Frameworks

Registered

2022-11-25