Mobile Applications for Noise Measurement in the Workplace - A Systematic Review
Applications for Noise Measurement
Abstract
Mobile sound level applications have been proposed as potential substitutes for the conventional sound level meters for noise measurement. However, their performance in measuring noise remain uncertain in the workplace. As such, the current systematic review aimed to identify the various mobile sound level applications that accurately measured noise in the workplace. Literature search was performed using PubMed, Scopus, and Web of Science databases. A total of 17 studies were included from 1184 retrieved articles. A total of 42 mobile sound level applications were identified (30 iOS and 12 android applications). iOS applications such as the NoiSee (n = 4), SPLnFFT (n = 3), and SLA Lite (n = 3) were the accurate applications to measure noise in general. However, when stratified according to the site of study, the NIOSH SLM (n = 2) was most accurate in measuring noise level in the workplace (i.e., field), while NoiSee (n = 4) was the most accurate application in laboratory setting. iOS applications also outperformed Android applications in accuracy. External microphones measured noise better than internal microphones, and devices within three years old provided the most accurate noise measurements.
Keywords :
Mobile applications; noise measurement; sound level meter; workplace,
Abstrak
Aplikasi pengukuran bunyi mudah alih amat berpotensi untuk mengantikan alat pengukur bunyi konvensional dalam pengukuran bunyi bising di tempat kerja. Walau bagaimanapun, prestasi aplikasi tersebut dalam mengukur bunyi bising di tempat kerja masih belum dapat dikenalpasti. Oleh yang demikian, tinjauan sistematik ini bertujuan untuk mengenal pasti pelbagai jenis aplikasi pengukur bunyi mudah alih yang mampu mengukur bunyi bising dengan tepat di tempat kerja. Carian literatur telah dijalankan menggunakan pangkalan data PubMed, Scopus, dan Web of Science. Sebanyak 17 kajian telah disenarai pendek daripada 1184 artikel yang diperoleh. Sebanyak 42 aplikasi pengukur bunyi mudah alih telah dikenal pasti (30 aplikasi iOS dan 12 aplikasi Android). Secara umumnya, aplikasi iOS seperti NoiSee (n = 4), SPLnFFT (n = 3) dan SLA Lite (n = 3) adalah aplikasi yang tepat untuk mengukur bunyi bising. Walau bagaimanapun, analisis berdasarkan tempat kajian mendapati bahawa NIOSH SLM (n = 2) adalah aplikasi yang paling tepat dalam mengukur bunyi bising di tempat kerja manakala NoiSee (n = 4) mengukur bunyi bising dengan paling tepat dalam makmal. Aplikasi iOS juga adalah lebih tepat dalam mengukur bunyi bising berbanding aplikasi Android. Mikrofon luaran dapat mengukur bunyi bising dengan lebih tepat berbanding dengan mikrofon dalaman telefon bimbit. Telefon bimbit yang digunakan dalam tempoh lingkungan tiga tahun dapat memberikan ukuran bunyi bising yang paling tepat.
Kata Kunci :
Aplikasi mudah alih; meter pengukuran bunyi; pengukuran bunyi; tempat kerja,
Correspondance Address
Sheng Qian Yew. Department of Public Health Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif Bandar Tun Razak, Cheras, 56000 Kuala Lumpur, Malaysia Tel: +603-91458792 Email: shengqian@ukm.edu.my
