ArcKit

A machine learning based location and activity recording and detection framework for iOS.

Location and Motion Recording

• 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

Activity Type Detection

• 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)

Installation

pod 'ArcKit'

Record Location and Motion

// the recording manager singleton
let loco = LocomotionManager.highlander

// decide which Core Motion features to include
loco.recordPedometerEvents = true
loco.recordAccelerometerEvents = true
loco.recordCoreMotionActivityTypeEvents = true

// decide whether to use "sleep mode" to allow for all day recording 
loco.useLowPowerSleepModeWhileStationary = true

Note: The above settings are all on by default. The above snippets are unnecessary, and just here
to show you some of the available options.

// start recording 
loco.startRecording()

Watch For Location Updates

when(loco, does: .locomotionSampleUpdated) { _ in

    // the raw CLLocation
    print(loco.rawLocation)

    // a more usable, de-noised CLLocation
    print(loco.filteredLocation)

    // a smoothed, simplified, combined location and motion sample
    print(loco.locomotionSample())
}

Watch For Moving State Changes

when(loco, does: .movingStateChanged) { _ in
    if loco.movingState == .moving {
        print("started moving")
    }

    if loco.movingState == .stationary {
        print("stopped moving")
    }
}

Note: The above code snippets use SwiftNotes to make
the event observing code easier to read. If you're not using SwiftNotes, your observers should be
written something like this:

let noteCenter = NotificationCenter.default
let queue = OperationQueue.main 

// watch for updates
noteCenter.addObserver(forName: .locomotionSampleUpdated, object: loco, queue: queue) { _ in
    // do stuff
}

Detect Activity Types

// fetch a geographically relevant classifier
let classifier = ActivityTypeClassifier(coordinate: location.coordinate)

// classify a locomotion sample
let results = classifier.classify(sample)

// get the best match activity type
let bestMatch = results.first

// print the best match type's name ("walking", "car", etc)
print(bestMatch.name)

Examples and Screenshots

• Location filtering
  examples
• Activity type detection examples

Documentation

• ArcKit API reference

Try the Demo App

• To run the ArcKit Demo App:
  1. Download or clone this repository
  2. Run pod install in the project folder
  3. In Xcode, change the project's "Team" to match your Apple Developer Account
  4. Build and run!
  5. Go for a walk, cycle, drive, etc, and see the results :)

Try Arc App on the App Store

• To see the SDK in action in a live, production app, install
  Arc App
  from the App Store, our free life logging app based on ArcKit