matghazaryan/SOMotionDetector

Health v2 · maintenance only

Adoption not part of the score

1057 stars · 145 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

An Objective-C library for iOS that detects user motion type (not moving, walking, running, automotive) and counts steps using CoreLocation and CoreMotion data. It works on all iOS devices without requiring the M7 coprocessor chip.

Use cases

• detect whether the user is walking, running, or driving in an iOS app
• count user steps with a pedometer library
• track motion activity in the background and relaunch the app from killed state
• build a fitness tracking feature without needing the M7 chip
• get callbacks when motion type or location changes
• customize speed thresholds for walking, running, and automotive detection

When to choose

• you need motion type detection on older iOS devices without an M7 coprocessor
• you want a simple drop-in Objective-C library with block-based callbacks
• you need background location updates and app relaunch from killed state
• you want customizable speed thresholds for activity classification

When to avoid

• you are building for Android or cross-platform with a single codebase
• you need modern Swift-native APIs like CoreMotion's CMMotionActivityManager
• your minimum deployment target is above iOS 9 and you want actively maintained Swift alternatives
• you need highly accurate activity recognition that dedicated hardware sensors provide

Facets

library · maturity maintenance

machine-learning mobile-development motion-detection step-counting coremotion corelocation pedometer activity-recognition sensor-fusion ios objective-c

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markdown · JSON · MCP: product_card(name="matghazaryan/SOMotionDetector")