Mohd Zain, Anis Suhaila and Tiong, Albert Guo Lee and Salehuddin, Fauziyah and Abd Manap, Nurulfajar and Abdul Razak, Hanim and Haroon, Hazura and Idris @ Othman, Siti Khadijah and Dinar, Ahmed Musa (2025) IoT-integrated mercury substance detection system for cosmetic product safety. International Journal of Research and Innovation in Social Science (IJRISS), IX (X). pp. 1289-1297. ISSN 2454-6186
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Abstract
Mercury is one of the most toxic heavy metals, capable of causing severe health problems such as kidney damage, anxiety, depression, and memory loss. Despite these risks, mercury-containing cosmetics continue to be used as skin-lightening agents, often without consideration of their clinical impacts. To address this issue, this study proposes the development of an IoT-based system for detecting mercury in cosmetic products. The system integrates a pH sensor with a NodeMCU board programmed using Arduino IDE, while Blynk and Google Spreadsheet are employed for real-time monitoring and historical data storage. The detection principle is based on pH analysis, as mercury-containing cosmetics typically fall within the acidic pH range of 5–7. Experimental validation was conducted on five cosmetic samples, of which two (pH 6.0 and 6.2) indicated the presence of mercury. The results demonstrate that the proposed IoT-based system can successfully identify and record mercury contamination, providing accessible monitoring through Blynk and systematic data logging via Google Spreadsheet. This approach highlights the potential of low-cost IoT-based solutions for enhancing cosmetic product safety monitoring.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Mercury detection, IoT based monitoring, pH sensor, Blynk, Cosmetic safety |
| Divisions: | Faculty Of Electronics And Computer Technology And Engineering |
| Depositing User: | Sabariah Ismail |
| Date Deposited: | 23 Feb 2026 01:22 |
| Last Modified: | 23 Feb 2026 01:22 |
| URI: | http://eprints.utem.edu.my/id/eprint/29504 |
| Statistic Details: | View Download Statistic |
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