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Thanks to SMC, firefighters with iPhones can track stairs climbed (OSS)

Hacker News

Thanks to SMC, firefighters with iPhones can track stairs climbed (OSS)

Hey HN! After months of work and over 1000 hours of research, design & development, I just released SMC, an open-source & free iPhone fitness game for firefighters, hikers, tower-runners and people who want to become fit by climbing stairs with friends - The app can also measure and track stairs climbed on a StairMill/StairMaster machine. Earlier users using stair stepper exercise machines would have to use/purchase more expensive machines that pair with their phones, now they simply wear their Apple Watch (or keep their phone in their pocket) using instructions in the app while exercising. - Firefighters across the world regularly wear heavy weights/their suits+hose reels) while using the stair mill / stair master machine in their fire stations, as climbing stairs is a critical part of their job. There is no central place where the exercise is tracked, requiring them all to be self-motivated and self-disciplined, SMC hopes to improve that. - SMC is open-source, safe to use and doesn’t have its own database/backend, so we collect 0 data/analytics from users on our servers. The app uses the secure HealthKit and in-built hardware to deliver the floors/storeys/flights of stairs climbed by the user. - The app also deeply integrates with GameCenter to encourage friends to be fit together, and it’s all meticulously translated in >10 languages (Includes Arabic, Ukrainian, Chinese Simplified & Traditional, Spanish, French, German, Slovak...) so you can compete & hold accountable your friends remotely, or just complete globally. - The app was designed to make a low impact exercise more exciting, to encourage people to take the stairs rather than the elevator, and so I can provide my kid a game that require exercising to get achievements for me. We'd love to get your feedback, and for you to share it with your friends :) We plan to add more features to the app if we get some traction & interest to enhance the fun experience.

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, apple, user · Missing: agents, macos, agent
92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: just released, ide, 000 · Missing: https docs, excited, exist
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: month, users, fitness · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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