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1. Executive Summary
An IoT-enabled hearing protection solution is proposed, and a novel device will be developed based on this solution. This implementation will bring together digital signal processing (DSP) noise cancellation technology, Bluetooth connectivity technology, smartphones, traditional hearing protection technology, and complementary technologies involving cloud and big data analytics, enabling better health and safety protection of workforce and data-driven decision-making. This solution meets the fundamental challenge of HSE (i.e., Health, Safety and Environment) managers by providing effective communication, reduced workforce's noise exposure, and real-time noise exposure measuring, monitoring, analyzing and reporting. The outcomes of this project have the great potential for commercializing this IoT-enabled hearing protection device.
From factories to construction sites, work environments are full of health hazards and dangers. Industrial noise is one of the most commonly overlooked occupational hazards. Each year, approximately 22 million workers in USA are at risk of hearing damage or hearing loss due to occupational exposure to industrial noise . Approximately 14 million current workers in the European Union  claim that their work has resulted in hearing disorders, which can progress slowly over many years and cause permanent hearing damage. Effective from April 2018, the new PPE Regulation (EU) 2016/425 moves hearing protection from Category II (i.e., intermediate risk) to Category III (i.e., the highest level of risk) .
However, strict regulations alone are not enough to safeguard the workforce’s hearing effectively. Traditional hearing protection devices have two major drawbacks: 1) masking warning sounds, such as alarms and verbal warnings; 2) interfering with communication, increasing the risk of accidents at work. In addition, good communication with co-workers is one of the key drivers of an effective workforce.
According to the HSE Regulations, in the environments where noise exceeds 80dB, a noise report and risk assessment are required. The data in these documents is measured by using noise dosimeter, however, this static data does not accurately represent the reality of the noisy environment, due to noisy environments commonly change over time. The reports are not able to provide any insights into the actual noise exposure experienced by the workforce, either. Therefore, many HSE officers, project managers and workers cannot aware the true exposure levels to hazards at work and the associated liabilities.
IoT technology provides a useful solution to enhancing safety in the workforce.
3. Aims and Objectives
This project is based on my previous research on wearable technologies and wireless body sensor networks . It explores the solution for protecting workforce from hearing damage or hearing loss due to occupational exposure to industrial noise by integrating IoT technology, novel DSP noise cancellation algorithms, speech feature extraction algorithms, real-time noise data analytics and visualization, and cloud-based web services. It addresses the following technical issues:
- DSP noise cancellation algorithms to automatically reduce the noise to safety levels.
- DSP algorithms for extracting speech features in the presence of background noise to enable effortless function switching and pairing with smartphones to implement one-to-one, one-to-many, locally and long-distance duplex communication.
- Advanced audio algorithms to enable environmental awareness and communications as talking as in a quiet room.
- Real-time noise data analytics and visualization for data-driven decision-making.
By wirelessly integrating with the existing communication network, the workplace will be set up as a connected workforce without disruption. The microphones onboard the headset pick up the wearers' voice even in very noisy environment and transmit it via one of the methods available at the workplace: Wi-Fi, cellular, 3G/4G mobile network or radio frequency. This enables the workers to communicate in a noisy environment one-to-one, one-to-many, locally and in long distance, all simultaneously and in full duplex. Furthermore, this can be done hands free and via voice control.
This project mainly uses:
- CSR8670 Bluetooth module.
- Kalimba 24-bit DSP.
- BlueLab xIDE.
- Smartphones and iBeacons.
- Raspberry Pi SBCs.
- Secure cloud-based services of Amazon Web Services (AWS).
The look and feel of the prototype of the IoT-enabled hearing protection device and the visualization of the noise intensity of a worksite:
 Bureau of Labour Statistics, United States Department of Labour.
 European Union Labour Force Survey, the Statistical Office of the European Union.
 Regulation [EU] 2016/425 of the European Parliament and the Council of the European Union.