sobri909/LocoKit

Health v2 · maintenance only

Adoption not part of the score

1541 stars · 104 forks observed · 2026-08-28

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

LocoKit is a Swift framework for iOS that combines Core Location and Core Motion recording with machine learning based activity type detection. It provides filtered location/motion data, stationary/moving state detection, battery-efficient all-day recording, and optional high-level Path and Visit timeline items with local persistence.

Use cases

• record gps location and motion data all day without draining the battery
• detect whether the user is walking, running, cycling, or driving
• distinguish transport modes like car, train, bus, or airplane
• build a timeline of visits and trips from raw location samples
• smooth and filter noisy core location data in an ios app
• persist location activity history locally between app sessions

When to choose

• you are building an iOS app that needs continuous background location and activity tracking
• you want ML-based transport mode detection beyond what Core Motion provides
• you need battery-efficient all-day recording with automatic start/stop
• you want human-level visit and path timeline items instead of raw GPS points

When to avoid

• you need location tracking on Android or cross-platform
• you only need simple one-shot location fixes without motion analysis
• your app is not on the iOS platform

Facets

framework · maturity active

machine-learning sdk geospatial mobile-development machine-learning corelocation coremotion gps-tracking activity-detection timeline battery-efficiency maps ios swift mobile

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markdown · JSON · MCP: product_card(name="sobri909/LocoKit")