LED Website Indicator – an LED lights up when someone visits your site

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Recently while looking for coding work I connected an LED to my resume site so that I would have instant feedback in the form of a visual notification whenever anyone visited. People seemed to like the idea when I wrote about it on my blog, so I have made this into a free service. Using ESP8266, my own hosted MQTT broker and WordPress plugin. If you want to try it out, I have the instructions over at https://ledindicator.devsoft.co.za - see the "learn" page. All you need is a spare ESP8266 module and a WordPress site. I'm concentrating on WordPress for now, but it should be relatively simple to send MQTT messages from other types of websites. If there is enough interest I plan to do this as a pre-programmed product, with an RGB LED and support for multiple websites. I know you can set this up yourself with Node-Red or Adafruit but I'm going for a very focused product which does one thing well, and is super simple to set up.

Visit product View on Hacker NewsOct 23, 2021

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

79%79% 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 HuntUnlikely to reach the leaderboard · Strong signals: visual, using, coding · Missing: mac, agents, macos

47%47% 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: ide, io · Missing: https docs, excited, just released

40%40% 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 · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% 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

15%15% 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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