I

I turned my TV into a '90s Weather Channel with an Android kiosk app

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I turned my TV into a '90s Weather Channel with an Android kiosk app

! wanted to bring back some of that old weather channel vibe and the WeatherStar 4000+ emulator was a great way to get it, but it wasn't really easy to just pull it up on my Shield TV in the morning. So I put together this Android app and figured others might be into it too. The app is a WebView wrapper around the WeatherStar 4000+ web emulator by netbymatt. It bundles everything locally and injects some JavaScript on top for kiosk features like location detection, settings, and music. Location chains through GPS first, then falls back to IP geolocation if that's not available. Settings are accessed with a long press and get saved between sessions. The music comes from the Weatherscan Complete Collection on Archive.org.

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
83%83% 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 · Missing: mac, agents, macos
52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: 000, io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: ios, way · Missing: mobile apps, personal, entrepreneurs
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
40%40% 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
17%17% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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