The cosmetic industry faces the challenge of detecting mercury contamination in their products, which can lead to harmful health effects such as renal damage, anxiety, depression, and memory loss. This project focuses on developing an IoT-based mercury substance detector for cosmetic products. It involves selecting a suitable sensor, determining the mercury detection range in cosmetics, and building an IoT circuit. The software tools used are Arduino IDE, Blynk, and Google Spreadsheet. Arduino IDE is employed for coding the NodeMCU, while Blynk and Google Spreadsheet receive data from the NodeMCU. The main components include the NodeMCU board, pH sensor, and connecting wires. Reliable sensors like Logo-Rnaenaor v2.0 and PH-4502C ensure accurate pH readings. Through Arduino IDE, the NodeMCU board and pH sensor notify Blynk of the presence of mercury. The pH sensor data is stored in a Google spreadsheet, providing a historical record. Two out of five analyzed cosmetic samples showed pH values of 6 and 6.2, indicating mercury contamination. In summary, this successful project develops an IoT-based mercury substance detector for the cosmetics industry using Blynk software and Google spreadsheets.