e-ISSN 2231-8542
ISSN 1511-3701

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Conceptual Framework - Hazard Assessment of Nanomaterials Using Bayesian Network

Mardhati Zainal Abidin, Risza Rusli and Norsuzieanah Halil

Pertanika Journal of Tropical Agricultural Science, Volume 28, Issue S1, December 2020

Keywords: Bayesian Network, big data, data-driven, nanomaterials risk, prediction

Published on: 16 September 2020

The development and application of advanced materials i.e. nanomaterials are important for the technology revolution and economic progress of the country. However, the potential health risk arising from nanomaterials become a major concern. Given the fact that both particulate and molecular identity of nanomaterials is responsible for the biological effects, the effects of nanomaterial exposure cannot be predicted based on the current understanding of their bulk properties. The lack of nanomaterials data for safety assessment become a major challenge to implement safe work practice at nanomaterials related industries. To resolve the aforementioned problem, a conceptual framework for hazard assessment of nanomaterials is presented in this study. Bayesian Network (BN) is used to support hazard assessment according to the guideline issued by the Department of Occupational Safety and Health (DOSH) Malaysia. The understanding of the hazard is crucial to encourage the development of an action plan to ensure the safety aspect while processing and handling nanomaterials.

ISSN 1511-3701

e-ISSN 2231-8542

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