Radio

Radio is the technology of using radio waves to carry information, such as sound, by systematically modulating properties of electromagnetic energy waves transmitted through space, such as their amplitude, frequency, phase, or pulse width. When radio waves strike an electrical conductor, the oscillating fields induce an alternating current in the conductor. The information in the waves can be extracted and transformed back into its original form

Enviar señales de radio desde Raspberry Pi mediante una conexión SSH desde PowerShell (parte 3)

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Enviar señales de radio desde Raspberry Pi mediante una conexión SSH desde PowerShell (parte 2)

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Enviar señales de radio desde Raspberry Pi mediante una conexión SSH desde PowerShell (parte 1)

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Detectar micrófono espía con CNN-rtlsdr (deep learning signal classification using rtl-sdr dongle)

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Señal del micrófono con SDRSharp Escanear frecuencias y clasificar las señales encontradas con CNN-rtlsdr teniendo conectado el micrófono Escanear frecuencias y clasificar las señales encontradas con CNN-rtlsdr sin conectar el micrófono Más información sobre Neural Network signal recognition rtlsdr:   https://www.jesusninoc.com/2017/12/15/neural-network-signal-recognition-rtlsdr/


Analizar las señales de radio y convertir a texto con Bing Speech API

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Escanear frecuencias y clasificar las señales encontradas (Neural Network signal recognition rtlsdr https://github.com/randaller/cnn-rtlsdr)

Para cada señal encontrada guardar en un fichero de audio (RTL SDR in Windows https://github.com/2013-UQ-Communication-Systems/public/wiki/Installing-RTL-SDR-in-Windows)

Convertir a texto el audio guardado (Bing Speech API https://azure.microsoft.com/es-es/services/cognitive-services/speech/)

 


Escanear frecuencias y clasificar las señales encontradas

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Resultado de escanear Neural Network signal recognition rtlsdr https://github.com/randaller/cnn-rtlsdr


Neural Network signal recognition rtlsdr

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Description Pre-trained version is able to scan desired frequency range and classify (better or worse) 4 kinds of found signals: wfm, tv secam carrier, tetra and others. You may train neural network to classify your own signals. What you really need for, is a good videoadapter and lots of free time. This is a kind of proof-of-concept, but it really works https://github.com/randaller/cnn-rtlsdr


Detectar señales ADS-B con dump1090 en Windows con PowerShell

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Script que pone en funcionamiento dump1090, almacena los resultados y después los analiza

Datos del vuelo VLG81EF