Developing an Artificial Intelligence on an Activated Noise Cancelling Device to Prevent Potential Noise-Induced Hearing Loss at a Urea Factory as an Occupational Safety Hazard Environment

Abstract

Background: The occupational safety hazard had regular monitoring of noise levels on the health risks of prolonged noise exposure.  

Objective: Hence, this study developed an activated noise cancelling earplugs in preventing noise-induced hearing loss.

Method: Integrating Python-based algorithms involved embedding lightweight interpreters, implementing efficient signal processing routines, in 4 stages. The first stage was the manufacturing, construction, and selecting of the ready-made earplugs characterized by noise cancelling technology to a noise level exceeding 85 decibels. Integrating AI into hearing protection systems is the next. The integration of the software to the online cloud and embedding it to the software app was the third stage. The last stage was the installation of the app.

Results: The final development of the activated noise cancelling earplugs demonstrated significant improvements in both noise attenuation and adaptability to noise variability. Conventional passive hearing protection devices, lacked adaptive responsiveness and real-time exposure analytics.

Conclusion: The activated noise cancelling earplugs were effective in preventing an occupational hazard called the noise-induced hearing loss at a urea fertilizer factory in Bangladesh.