react-native-activity-recognition

React Native wrapper for the Android Activity Recognition API and CMMotionActivity. It attempts to determine the user activity such as driving, walking, running and cycling. Possible detected activities for android are listed here and for iOS are listed here.
Updated January 7th and tested with react-native v0.57.5

Installation

npm i -S react-native-activity-recognition

or with Yarn:

yarn add react-native-activity-recognition

Linking

Automatic

react-native link react-native-activity-recognition

IMPORTANT NOTE: You'll need to follow Step 4 for both iOS and Android of manual-linking

Manual

Make alterations to the following files in your project:

Android

Add following lines to android/settings.gradle

...
include ':react-native-activity-recognition'
project(':react-native-activity-recognition').projectDir = new File(rootProject.projectDir, '../node_modules/react-native-activity-recognition/android')
...

Add the compile line to dependencies in android/app/build.gradle

...
dependencies {
    ...
    compile project(':react-native-activity-recognition')
    ...
}

Add import and link the package in android/app/src/.../MainApplication.java

import com.xebia.activityrecognition.RNActivityRecognitionPackage;  // <--- add import

public class MainApplication extends Application implements ReactApplication {
    // ...
    @Override
    protected List<ReactPackage> getPackages() {
        return Arrays.<ReactPackage>asList(
            new MainReactPackage(),
            // ...
            new RNActivityRecognitionPackage()                      // <--- add package
        );
    }

Add activityrecognition service in android/app/src/main/AndroidManifest.xml

...
<application ...>
    ...
    <service android:name="com.xebia.activityrecognition.DetectionService"/>
    ...
</application>
...

iOS

In the XCode's "Project navigator", right click on your project's Libraries folder ➜ Add Files to <...>
Go to node_modules ➜ react-native-activity-recognition ➜ ios ➜ select RNActivityRecognition.xcodeproj
Add RNActivityRecognition.a to Build Phases -> Link Binary With Libraries
Add NSMotionUsageDescription key to your Info.plist with strings describing why your app needs this permission

Usage

import ActivityRecognition from 'react-native-activity-recognition'

...

// Subscribe to updates
this.unsubscribe = ActivityRecognition.subscribe(detectedActivities => {
  const mostProbableActivity = detectedActivities.sorted[0]
})

...

// Start activity detection
const detectionIntervalMillis = 1000
ActivityRecognition.start(detectionIntervalMillis)

...

// Stop activity detection and remove the listener
ActivityRecognition.stop()
this.unsubscribe()

Android

detectedActivities is an object with keys for each detected activity, each of which have an integer percentage (0-100) indicating the likelihood that the user is performing this activity. For example:

{
  ON_FOOT: 8,
  IN_VEHICLE: 15,
  WALKING: 8,
  STILL: 77
}

Additionally, the detectedActivities.sorted getter is provided which returns an array of activities, ordered by their confidence value:

[
  { type: 'STILL', confidence: 77 },
  { type: 'IN_VEHICLE', confidence: 15 },
  { type: 'ON_FOOT', confidence: 8 },
  { type: 'WALKING', confidence: 8 },
]

Because the activities are sorted by confidence level, the first value will be the one with the highest probability Note that ON_FOOT and WALKING are related but won't always have the same value. I have never seen WALKING with a higher confidence than ON_FOOT, but it may happen that WALKING comes before ON_FOOT in the array if they have the same value.

The following activity types are supported:

IN_VEHICLE
ON_BICYCLE
ON_FOOT
RUNNING
WALKING
STILL
TILTING
UNKNOWN

iOS

detectedActivities is an object with key to the detected activity with a confidence value for that activity given by CMMotionActivityManager. For example:

{
    WALKING: 2
}

detectedActivities.sorted getter will return it in the form of an array.

[
    {type: "WALKING", confidence: 2}
]

The following activity types are supported:

RUNNING
WALKING
STATIONARY
AUTOMOTIVE
CYCLING
UNKNOWN

Credits / prior art

The following projects were very helpful in developing this library: