Live weather radar wallpaper for Android

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My very small team has built an Android live wallpaper that displays the current NEXRAD weather radar data as your Android phone’s live wallpaper. The app automatically selects the nearest radar site using coarse location permissions, or you can manually choose a location. Everything is size optimized and only updates when the wallpaper is being viewed to minimize battery footprint. Interesting technical bits: - Using the US National Weather Service public radar feed (via public S3 bucket) - Custom radar volume data decoder written in Go and running as AWS Lambdas (triggered by S3 bucket events) - Custom rendering API - Kotlin Android app is <10 MB (no cross-platform bloat) Available on Google Play: https://play.google.com/store/apps/details?id=app.radarlove.... Happy to answer questions about the radar data processing pipeline, infrastructure, or the live wallpaper implementation. Also open to interesting opportunities for collaboration...

Visit product View on Hacker NewsOct 21, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

71%71% 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: google, apps, using · Missing: mac, agents, macos

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: apps, google · Missing: mobile apps, ios, personal

60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: pipe, 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.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

46%46% 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

19%19% 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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