IOT-Enabled Low-Cost Hearing Aid with Flutter Control App

Authors

  • Dr. M. N. Tibdewal Department of Electronics and Telecommunication SSGMCE, Shegaon, India Author
  • Sakshi Satao Department of Electronics and Telecommunication SSGMCE, Shegaon, India Author
  • Srushti Dabhade Department of Electronics and Telecommunication SSGMCE, Shegaon, India Author
  • Srutika Vir Department of Electronics and Telecommunication SSGMCE, Shegaon, India Author
  • Yash Dubey Department of Electronics and Telecommunication SSGMCE, Shegaon, India Author

DOI:

https://doi.org/10.32628/IJSRST2613330

Keywords:

Smart Hearing Device, ESP32-S3 Controller, Internet of Things (IoT), I2S Audio Interface, Flutter Application, Assistive Systems, Digital Signal Processing (DSP), Wearable Electronics

Abstract

Hearing loss has a major impact on communication, situational awareness and personal safety, especially in noisy and urban environments where auditory cues are essential. Most hearing aids are designed as passive amplifiers of sound and generally do not dynamically adapt to variations in acoustic environment or personal taste. In this paper, we will explain the complete design and development of an IoT-based smart hearing aid system based on the ESP32-S3 microcontroller that implements I2S digital audio processing, as well as a mobile application developed in Flutter. Environmental sound is captured using an I2S MEMS microphone and processed in real time through digital signal processing techniques such as gain control, low-pass filtering, and high-pass filtering to enhance speech intelligibility while reducing unwanted noise. The processed audio is delivered via an I2S audio amplifier to earphones or a miniature speaker. Wireless connectivity enables real-time customization of hearing parameters through a mobile interface. A TP4056-based battery charging and protection module ensures portability, safety, and energy efficiency. The proposed system provides a low-cost, scalable, and user-centric assistive solution suitable for wearable hearing aid applications.

Downloads

Download data is not yet available.

References

World Health Organization. World report on hearing. (World Health Organization, 2021)

Lenneke M. R. M. Wong et al.

Zhao, Y., Wang, D., Johnson, E. M. & Healy, E. W. A deep learning based segregation algorithm to increase speech intelligibility for hearing-impaired listeners in reverberant-noisy conditions. J. Acoust. Soc. Am. 144, 1627-1637 (2018).

Andersen, A. H. et al. Creating clarity in noisy environments by using deep learning in hearing aids. Semin. Hear 42, 260-281

Nicolson, A. & Paliwal, K. K. Masked multi-head self-attention for causal speechenhancement. Speech Commun. 125, 80–96(2020)

Defossez, A., Synnaeve, G. & Adi, Y. Real Time Speech Enhancement in the Wav

Downloads

Published

05-04-2026

Issue

Section

Research Articles

How to Cite

[1]
Dr. M. N. Tibdewal, Sakshi Satao, Srushti Dabhade, Srutika Vir, and Yash Dubey, Trans., “IOT-Enabled Low-Cost Hearing Aid with Flutter Control App”, Int J Sci Res Sci & Technol, vol. 13, no. 2, pp. 554–560, Apr. 2026, doi: 10.32628/IJSRST2613330.