A noise dosimeter controller app

• Main Author: Tang, Ignatius Zhen Yu
• Other Authors: Victor Adrian
• Format: Final Year Project
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
• Online Access: http://hdl.handle.net/10356/64657
• Institution: Nanyang Technological University

The rapid and continuous development of smartphone products in recent years has changed the way people enjoy their mobile entertainment. Often music is listened to over a prolonged period of time and at relatively loud volume levels. Such extended exposure may lead to several health risks to the listener. One of such risk would be noise-induced hearing loss (NIHL). This hearing loss is known as sensorineural hearing loss. The risk of suffering a permanent hearing loss through NIHL is preventable. One effective method is to ensure that one’s noise exposure is being kept within the limits of a safety standard. This can be done through the use of a noise dosimeter. A noise dosimeter is a device that is able to measure and compute the noise dosage that a user is exposed to. With this information available to users, their music can be monitored, thus allow them to limit the level of noise exposure. Preventive measures can then be taken. This project focuses on an iPhone Operating System application (iOS app) to work along side a personalised dosimeter to ensure that audio signals output from headphones are within safe threshold noise dosage limits. Integrated Development Environment (IDE), Xcode and programming language, Objective-C were utilised to achieve the completion of this project. This report first analyses sound waves and its effects on human ears. International safety standards for noise exposure duration are discussed to act as a guideline for safety threshold limits. Finally the implementation of an iOS system is explained. Several methods are discussed to carry out communication between the dosimeter with the iPhone through the auxiliary port of the iOS device, including an offline voice recognition function and binary signal demodulation. The dosimeter will not be extensively discussed as the dosimeter project focused on by another FYP student.