App developers want to thoroughly test the happy path and exceptions in the product experience before shipping to customers. Developers need a way to mock user movement to test their live location features before releasing the app. This involves mocking user location and movement that is as close to real world behavior as possible. Both Android OS & iOS provide APIs and tools to simulate such location data but these tools are insufficient. They provide a stream of locations (latlongs) but do not provide varying activity data, location confidence, and other sensor data that power the awesome features of HyperTrack.
The HyperTrack SDK is active on thousands of devices through 100+ apps across the globe. Users represent all 6 inhabited continents, 2 major smartphone Operating Systems, several tracking use cases and markets, and a variety of network and GPS conditions. We implemented a way for the SDK to record overall battery consumption on the device during the time it was active. This is our first battery benchmarking exercise at a reasonable scale. This goes beyond small scale tests we had done with dozens of users in controlled setups. Turns out, we are able to deliver real-time location tracking with near-zero battery drain.
In this post we share the data that implies that HyperTrack delivers real-time location tracking with near-zero battery drain. We go on to list the battery optimization techniques we used in order to get there.
At HyperTrack, we are building APIs and SDKs which enable developers to track and trace local deliveries. Developers integrate HyperTrack’s tracking SDK into the app that drivers use to mark the start and end of their pickup and delivery tasks. We deploy our SDKs as frameworks and distribute it via Cocoapods – a popular dependency management tool. Having lost few hours every time we deployed our SDK, we gave
Fastlane a spin and found ourselves pleasantly surprised with the result.