Add Timing Training Mode to iOS App

Posted 4 weeks ago

Worldwide

Summary

We're adding a Timing Training mode to our live iOS baseball hitting app (Attack Tee). A pitcher windup counts down 3-2-1, then a marker sweeps toward an "on time" point. The phone's mic must pick up the exact moment the ball is hit off the tee and measure the swing's timing in milliseconds — scoring each rep as on time, early, or late. The phone is already mounted on the tee in our patented holder, so the mic sits fixed next to the point of contact — consistent and ideal for clean, low-latency detection. Design and a working prototype are done. We need a Swift developer to build it. The core challenge is accurate, millisecond-level timing from the mic. What you'll build: Native Swift audio module: detect bat-ball contact and timestamp it to the millisecond Timing screen (countdown, sweeping marker, speed selector, result states) per our mockups Scoring + session summary Mic permission + tap-to-swing fallback Integration into the existing app Must-haves: Strong Swift + iOS audio (AVAudioEngine / AVAudioSession / Audio Units) Low-latency audio: onset detection, buffer timing, host-clock alignment Shipped App Store apps Please answer in your proposal: Have you built millisecond audio timing on iOS? Describe it. How would you align mic-detected contact time with the on-screen animation clock? How accurate (ms) can timing be with the mic mounted next to the ball? Full mockups, prototype, and detailed scope shared with shortlisted candidates.

  • Less than 30 hrs/week
    Hourly
  • 1-3 months
    Duration
  • Intermediate
    Experience Level
  • $15.00

    -

    $30.00

    Hourly
  • Remote Job
  • Ongoing project
    Project Type
Skills and Expertise
Mandatory skills
iOS Development
iPad App Development
Nice-to-have skills
Apple Xcode
Objective-C
Activity on this job
  • Proposals:50+
  • Last viewed by client:4 weeks ago
  • Interviewing:
    4
  • Invites sent:
    0
  • Unanswered invites:
    0
About the client
Member since Feb 22, 2016
  • United States
    Long Beach2:04 AM
  • $1.2M total spent
    173 hires, 14 active
  • 15,920 hours

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