Enhanced Real-Time CO₂ Monitoring Framework with IoT Integration for Domestic-scale Carbon Capture Machine
This paper presents an enhanced real-time Carbon Dioxide (CO₂) monitoring framework for a Domestic�scaled Carbon Capture Machine (DSCCM) developed for small�scale fish-smoking operations in cottage industries. The system incorporates a three-stage emission filtration and treatment process consis...
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| Main Authors: | , , , , , |
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| Format: | Proceeding |
| Language: | en |
| Published: |
IEEE XPLORE
2025
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/50655/3/Enhanced%20Real-Time.pdf http://ir.unimas.my/id/eprint/50655/ https://ieeexplore.ieee.org/document/11233542 |
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| Summary: | This paper presents an enhanced real-time Carbon Dioxide (CO₂) monitoring framework for a Domestic�scaled Carbon Capture Machine (DSCCM) developed for small�scale 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 Node�RED 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. |
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