Remote-Controlled IKEA Deathstar Lamp

Hacker News

Repainting the iconic IKEA PS 2014 lamp into the Deathstar from Star Wars has been a popular IKEA hack for quite some time. This variant additionally replaces the manual, rope-operated mechanism to open and close the lamp with a remote-controlled motor. The firmware is based on ESPHome, and its excellent Home Assistant integration enables one to implement higher-level features, like a "sundial" where the aperture of the Deathstar follows the sun elevation throughout the day (see the timelapse video). That said, I will not consider this project as complete until the Imperial March can be played over the stepper motor (just like the legendary Floppotron) ;-)

Visit product View on Hacker NewsApr 27, 2025

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

77%77% 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: ide, io · Missing: https docs, excited, just released

71%71% 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

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

51%51% 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

48%48% 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

14%14% 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

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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