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Syncing iPhone & Apple Watch Apps with Smart Suits to Provide Insight into Muscle Activity

Syncing iPhone & Apple Watch Apps with Smart Suits to Provide Insight into Muscle Activity

Industry

Fitness

Platform

iOS

company image

  • Company Profile

    Athos is a system that enables smart clothing to measure how hard your muscles are working using the science of Electromyography. The clothing is integrated with Core modules sending the captured metrics to a smartphone via Bluetooth. The AI-powered mobile app gives you insights to understand how your muscles perform

  • Project Goals

    - Develop an Apple Watch app
    - Calibrate the smart suit’s
    - Cores and provide manual testing
    - Implement automated testing for the mobile app
    - Develop a web app for version control and bug reporting

  • Business Need

    - Enter the prospecting Apple Watch app’s market in Q3 2015
    - Extend functionality and increase reliability of the mobile app

  • Engagement Model

    Outsourcing (Agile)

  • Duration

    12 month

  • Effort

    1 iOS Developer, 1 QA Engineer

Technologies Used

Development

  • scala
    Scala
  • play-framework
    Play Framework
  • swift
    Swift
  • mysql
    MySQL
  • obj-c
    Objective-c
  • bluetooth-le
    Bluetooth Low Energy
  • hibernate
    Hibernate

Test Automation

  • java-new
    Java
  • carina-new
    Carina Framework
  • test-ng-new
    Test NG
  • appium-new
    Appium

Challenges and Solutions

  • Many bugs causing delays in update releases

    We set up a CI/CD process, created and implemented Test Automation cases. This way we reduced the number of blockers by 50%

  • Inability to manually test smart clothing signals in 24/7 mode

    We automated the testing process by creating mocks which were sending awaited responses for special requests from the mobile app

  • Testing coach-athlete engagement routine

    With Carina Framework we built integrated tests to work with both web and mobile platforms simultaneously. This helped us to imitate the user flow and accomplish all identified goals

  • Integration of BLE (Bluetooth Low Energy) Technology with self-developed unique signals

    We implemented algorithms developed by Athos engineers. These algorithms consider an athlete’s body position and send the correct signals to the app, which process them and provide valid metrics for the end users

Results

Firstly, Solvd delivered an internal solution for Athos engineers, that collects raw data from hardware devices via BLE-service and prepares it for further visualization inside IOS mobile application. We also set up user data analytics service Mixpanel for experimental design and behaviour analysis.

results image

Secondly, we conducted a full QA cycle, which resulted in significantly reducing the number of bugs and helped Athos to eliminate crashes in production. Moreover, we created a reliable infrastructure for Core’s firmware version control, that provided more transparent synchronization between smart clothing and apps.

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Lastly, we developed the app for Apple Watch, which made it possible for Athos to break into the emerging market and stay relevant in the fitness arena. Our priority was to balance performance and feature variety, which is why we paid special attention to the load dispatch between devices. As a result we increased battery efficiency by 60% and earned the loyalty of Apple Watch users.

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