Smart automated noise policy monitoring and feedback control system for mining application

Madahana, Milka C.I.; Ekoru, John E.D.; Nyandoro, Otis T.

doi:10.1016/j.ifacol.2019.09.184

Cited by 7 publications

(2 citation statements)

References 4 publications

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“…The current model shown in Figure 1 has the following enhancements from the previous models by Moroe et al (2019) and Madahana et al (2019), which was further improved by Madahana, Ekoru and Nyandoro (in press):…”

Section: Improvements To the Current Modelmentioning

confidence: 92%

Feedback-based noise management matrix in action

Moroe¹,

Khoza-Shangase²,

Madahana³

et al. 2020

South African Journal of Communication Disorders

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Background: This article presents the details and findings of a practical implementation of a preliminary model for use in hearing conservation programmes (HCPs) in the mining sector in South Africa. Objectives:The implementation is based on a previously published model, called feedbackbased noise monitoring model (FBNMM), and represents its implementation as a tool of predicting occupational noise-induced hearing loss (ONIHL), as well as monitoring and managing HCPs in the mining sector within the South African context. Method:The article, utilising real miners' data, demonstrates this basic static feedback model with its practical applications such as estimating, monitoring and providing quantitative information to aid miners, mining administrators and policymakers in decision-making around HCPs, as recommended in the previous 2019 publication by Moroe et al. This study was conducted in a South African platinum mine. Evidence on the model's sensitivity and practicability in early identification, intervention and management of ONIHL in the workplace is presented.Results: Findings show how the use of the model within an HCP viewed as a complex intervention can allow for early prediction of ONIHL, consequently affording more accurate early intervention as part of preventive audiology within the health and safety goals of mines. Conclusion:The feedback-based model should be a useful tool for successful implementation and monitoring of HCPs within South African mines.

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Section: Improvements To the Current Modelmentioning

confidence: 92%

Feedback-based noise management matrix in action

Moroe¹,

Khoza-Shangase²,

Madahana³

et al. 2020

South African Journal of Communication Disorders

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“…Smart ear muffs or ear plugs are another high‐demand PPE device in mining industry to detect noise above hearing threshold and prevent permanent hearing loss in mine workers. [ 41 ] An automate PPE‐Tool pair check was developed to notifies the operator and safety officer if the construction or mine worker does not wear the required PPE items. In this system, different sensors (optical, force, touch, photoresistor…) transferred their data by using IoT technology.…”

Section: Overview Of the Construction And Mining Industry In Australiamentioning

confidence: 99%

Advances in Wearable Piezoelectric Sensors for Hazardous Workplace Environments

et al. 2023

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Recent advances in wearable energy harvesting technology as solutions to occupational health and safety programs are presented. Workers are often exposed to harmful conditions-especially in the mining and construction industries-where chronic health issues can emerge over time. While wearable sensors technology can aid in early detection and long-term exposure tracking, powering them and the associated risks are often an impediment for their widespread use, such as the need for frequent charging and battery safety. Repetitive vibration exposure is one such hazard, e.g., whole body vibration, yet it can also provide parasitic energy that can be harvested to power wearable sensors and overcome the battery limitations. This review can critically analyze the vibration effect on workers' health, the limitations of currently available devices, explore new options for powering different personal protective equipment devices, and discuss opportunities and directions for future research. The recent progress in self-powered vibration sensors and systems from the perspective of the underlying materials, applications, and fabrication techniques is reviewed. Lastly, the challenges and perspectives are discussed for reference to the researchers who are interested in self-powered vibration sensors.

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