The Carbon Dioxide Filtration System Using Chlorella Pyrenoidosa Microalgae IoT-based for Air Quality Improvement

Air pollution is a global problem that affects climate stability and human health. It is mainly caused by increasing carbon dioxide $\left(\mathrm{CO}_{2}\right)$ levels. This project aims to lower CO2 levels using a novel technique that employs green microalgae, specifically Chlorella pyrenoidosa, and an Internet of Things monitor. This experiment combines an MG-811 CO2 sensor and an ESP32 microcontroller to measure CO2 levels in a controlled setting. In real-time, the ThingSpeak platform receives and processes the sensor data. During the observation period, the average concentration of CO2 in the system decreased from 707.07 ppm to 677.90 ppm, representing a $\mathbf{3.15 \%}$ drop in CO2 levels. A statistical study revealed a significant trend indicating a steady drop in CO2 levels, with a regression coefficient of $\mathbf{-0.000526}$ and a p-value of $7.8975 \times 10^{-6}$. Nevertheless, the data showed inconsistency, with a standard deviation of 81.44 ppm, indicating differences that may be due to the aerator capacity and volume of Chlorella pyrenoidosa used. These results indicate that it is possible to integrate Chlorella pyrenoidosa with Internet of Things technology to reduce CO2 and manage air quality effectively. This study shows the prospects of this method for scalable and cost-effective environmental solutions, but indicates that further research is needed to improve the performance and adaptability of the system.