Abstract: The aim of this research project is to create a Morse code detecting system by utilizing the ESP32 microcontroller's capabilities and machine learning capacity. An enduring communication technique, Morse code can be used for emergency signals and low-power communication among other things. In order to develop a flexible and effective Morse code detector, we plan to integrate contemporary technology with conventional communication methods. The main goal of the project is to create a small, inexpensive device that can precisely recognize and decode inputs that contain Morse code messages. The core processing unit, the ESP32 microcontroller, is responsible for preprocessing and signal acquisition. It also offers smooth networking choices for remote control and data transfer. In order to recognize Morse code signals, we use machine learning methods.
Keywords: ESP32, Convolutional neural networks, Recurrent neural networks, Signal preprocessing, Audio capture, Real-time recognition, internet of Things (IoT), Remote monitoring, Communication technology, Emergency signaling, Low-power communication.
Cite:
Dr.U.P. Akare, Prof. Kalpana Bhure, Adarsh Sonkusre, Atharva Ganorkar, Mayank Barapatre, Pratyush Roychowdhury, "Morse Code Detector Using Machine Learning", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 4, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13414.
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DOI:
10.17148/IJARCCE.2024.13414
