Flights Directly Above Me

Hacker News

Hi HN, aviation enthusiast often use Flightradar24 and other systems to find out what flights are directly above their location at any time. Inspired by a few other projects, I built a basic HTML + Javascript dashboard, that does the same, simulating an old school LED display. Enjoy the Github repo! How it works: Standard HTML page that loads the flightradar data in a specific location box that you specify. Because the free flightradar24 data is browser only, I used a corsproxy to get around loading issues. Everything works with the free versions, but if you hit limits, you can also specify a key to a paid CORS Proxy service. Once the data is loaded, JS refreshes it every 30 seconds. The HTML itself is refreshed once an hour, so even a dashboard you don't have access to would be updated from new changes.

Visit product View on Hacker NewsDec 20, 2024

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2points

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Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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