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@article{200039,
        author = {Khushi VijayShingare and Siddhi pravin Lokhande and Prof. Sunita Jadhav},
        title = {Spectrally-Sound Portable Audio Spectrum Analyzer},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {1991-1998},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200039},
        abstract = {The project “Spectrally Sound” presents the design and implementation of a compact, low-cost, and real-time audio spectrum analyzer using the ESP32 microcontroller. The primary objective of this system is to analyze sound signals and convert them into a visual representation of their frequency components, enabling users to understand how sound energy is distributed across different frequency ranges such as bass, mid, and treble. This project aims to provide an affordable and portable alternative to conventional spectrum analyzers, which are often expensive and bulky.
The system uses an INMP441 digital MEMS microphone to capture ambient sound signals. Unlike traditional analog microphones, the digital interface (I2S) ensures better signal quality with reduced noise and distortion. The ESP32 receives this digital audio data and processes it in real time. The core processing technique used is the Fast Fourier Transform (FFT), which converts the captured audio from the time domain into the frequency domain. To improve the accuracy of the analysis and reduce errors such as spectral leakage, a windowing function (such as the Hann window) is applied before performing the FFT.
The processed frequency data is then divided into different frequency bands and displayed on an OLED display as a dynamic bar graph. This allows users to visually interpret sound intensity and frequency variations in real time. The ESP32’s dual-core architecture and efficient peripheral support enable smooth execution of multiple tasks, including data acquisition, signal processing, and display control, ensuring continuous and real-time operation.
In addition to audio spectrum analysis, the system includes an electromagnetic (EM) signal detection module using a copper coil connected to the ESP32’s ADC. This feature allows the system to detect the presence of nearby electromagnetic signals, adding extra functionality beyond basic audio analysis. The entire system is powered by a rechargeable battery using a TP4056 charging module, making it portable and suitable for field applications.
The project demonstrates the practical implementation of key Digital Signal Processing (DSP) concepts such as sampling, windowing, frequency transformation, and real-time visualization on an embedded platform. Although the system has some limitations in terms of precision and advanced features compared to professional analyzers, it successfully achieves its goal of providing a cost-effective, user-friendly, and educational tool for audio analysis. Furthermore, the system offers significant potential for future enhancements, including IoT integration, advanced visualization, and AI-based sound classification, making it a scalable solution for modern applications.},
        keywords = {},
        month = {May},
        }