Enhanced Real-Time CO₂ Monitoring Framework with IoT Integration for Domestic-scale Carbon Capture Machine - Annisa, Jamali; Lidyana, Roslan; Abang Mohammad Nizam, Abang Kamaruddin; Ahmad Rizal, Ahmad Bokhari; Ahmad Zaki, Abu Bakar; Nur Tahirah, Razali (IEEE XPLORE, 2025)
This paper presents an enhanced real-time Carbon Dioxide (CO₂) monitoring framework for a Domesticscaled Carbon Capture Machine (DSCCM) developed for smallscale fish-smoking operations in cottage industries. The system incorporates a three-stage emission filtration and treatment process consisting of: (i) a high-temperature catalyzer for filtering particulates and converting volatile compounds such as carbon monoxide (CO) and polycyclic aromatic hydrocarbons (PAHs) into CO₂, (ii) a water-based scrubber to separate CO₂ from ambient air, and (iii) a low-temperature catalyzer to ensure that residual emissions are rendered non-toxic CO₂. CO₂ concentrations before and after capture are monitored using industrial-grade Non-Dispersive Infrared (NDIR) sensors (SKU: 101991028), integrated with a Raspberry Pi-based NodeRED dashboard for real-time data visualization and analytics. Experimental validation demonstrated a CO₂ scrubbing efficiency ranging from 73.56% to 90.79%, with notably narrow ±3–8% deviation margin when compared to a calibrated Testo 440 reference device. The system is cost-effective, modular, and suitable for deployment in unregulated emission environments, contributing to more inclusive carbon mitigation strategies in rural and artisanal industries.