This study aims to design and implement a novel Internet of Things (IoT)-based monitoring sysatem for air quality, temperature, and humidity specifically tailored for industrial-scale tissue manufacturing. Unlike previous works that focused on single-sensor applications or small-scale prototypes, this system integrates multiple sensors MQ135 for air quality, DHT11 and BME280 for temperature and humidity into a unified platform controlled by an ESP32 microcontroller. The integration enables simultaneous multi-parameter monitoring with higher accuracy and reliability, while real-time data transmission via Wi-Fi to the Blynk platform allows remote accessibility through mobile devices. Testing results demonstrate strong performance: the DHT11 sensor shows a deviation of only ±0.1 °C and ±0.1% RH compared to standard instruments, the BME280 sensor exhibits an error margin of 0.3–0.5 °C, and the MQ135 successfully detected pollutant concentration increases from 9% to 14%, consistently triggering automated alerts. Voltage measurements across components revealed low error rates of 0.8–2.5%, validating the system’s electrical stability. The novelty of this research lies in the integration of cost-efficient sensors with a dual-alert mechanism (buzzer and mobile notifications) for real-time environmental control, tested and validated in an actual industrial production environment. These findings confirm that the system not only ensures accurate real-time monitoring but also enhances occupational health, operational efficiency, and workplace safety, offering a scalable model for industrial IoT-based environmental monitoring.
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