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Live-Streaming Next Week's Solar Eclipse from Above the Clouds

Hacker News

Live-Streaming Next Week's Solar Eclipse from Above the Clouds

Hi HN, I've been working on a high altitude balloon along with a team of volunteers that is going to take pictures during the solar eclipse next week. The balloon has a gimballed camera (or more accurately, a gimballed mirror) that autonomously tracks the sun. Real-time video is sent down to the ground via 70cm ham radio. The comms was developed almost entirely by myself, and on previous flights we've tested it to a range of 140km. Along with the real-time video, it also uses spare bandwidth to send down high resolution imagery from several other cameras on the payload. We'll be streaming the video to Youtube. Our channel is linked on our website. If you're not going to be in the path of the eclipse, this is a great way to participate. And even if you are in the path, this gives you a second opportunity to view it - we'll be launching from New Brunswick, Canada, which is one of the last places the eclipse will pass through. Aside from the project website, I also wrote up a short article on one of our previous launches. It focuses primarily on the communications system since that's my contribution to the project: https://www.scd31.com/posts/real-time-balloon-video I hope you like it, and I hope to hear your thoughts. Thanks!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
70%70% 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: new · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: communications · Missing: plus, platform, intuitive
57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video, way · Missing: mobile apps, ios, personal
52%52% 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
12%12% 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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