Design and testing of a personalized noise monitoring system

Abstract

Agricultural workers are more prone to noise-induced hearing loss than are many other workers. Hearing protection device use among agricultural workers is low, but training can increase hearing protection device use. This work proposes a system designed to automatically inform agricultural workers when they were exposed to noises that exceed the National Institute for Occupational Safety and Health (NIOSH) recommended exposure level. The smartphone-based system worn on the arm uses a noise dosimeter to measure noise exposures throughout the day to within ±2 A-weighted decibels of a Class 2 sound level meter. The device collects location and audio data, which are transferred to a server and presented to the worker on a locally hosted website. The website details noise exposure and helps the worker identify where exposure occurred and what specific tasks exceed NIOSH’s recommended exposure limit, putting them at higher risk of noise-induced hearing loss. With this understanding, the worker is expected to adopt behavior changes and better hearing protection use at critical places and times. This pilot study evaluates the accuracy of the noise dosimeter and GPS relative to gold-standard instruments. The system was tested on a farm with outputs compared with gold-standard instruments. A-weighted, 1-sec averaged sound pressure levels and position data were collected while users were performing a variety of tasks indoors and outdoors. The smartphone’s external noise dosimeter read within ±2 A-weighted decibels of the Class 2 reference dosimeter 59% of the time. The positioning devices had an average error of sub-4 m. While not perfectly matching gold-standard instruments, the device is capable of identifying and collecting information relative to loud noise events that promote noise-induced hearing loss.