Wi

Wireless Audio Modem Libraries

Hacker News

Wireless Audio Modem Libraries

I have created a library for transmit digital data via acoustic signals. Allowing wireless digital communication at low speeds of 50 bps to 1 kbps with general audio devices. Without radio device or cable. The communication range is approximately 60cm. https://www.youtube.com/watch?v=4cB3hWATDUQ Live demo You can try sending and receiving half-duplex texts in browser.(PC or smartphone.) Prepare a computer and a smartphone or two or more smartphones. If a combination of a computer and a smartphone, it is easier the computer side is the transmitter. https://nyatla.jp/tbskmodem/index.en.html Use case - Data transfer from websites not via the Internet. - Offline data transfer between smartphones. - Simple digital data communication via general voice lines (voice telephone lines, AM/FM broadcasts, string phones, etc.). - Digital storage in classical analog signal equipment (cassette tapes, etc.). - Data transfer/retrieval to/from embedded devices and uploading to websites. Source file - Python (Anaconda+Windows/Linux) https://github.com/nyatla/TBSKmodem https://pypi.org/project/tbskmodem/ - C# (Windows) https://github.com/nyatla/TBSKmodemCS - C++ (Windows/Linux/Emscripten) https://github.com/nyatla/NyARToolkitCPP - JavaScript (Chrome/Safari※/SilkBrowser) https://github.com/nyatla/TBSKmodemJS https://www.npmjs.com/package/tbskmodem-js

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% 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
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
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BetaListMay not resonate with beta-testers · Strong signals: audio, smart · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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