Real-Time Monitoring of Modular Carbon Capture Machines with Sensor Networks and Node-RED

Lidyana, Roslan and Annisa, Jamali and Sim, Cai Ying and Mark Louis, Jimmy and Abg Mohd Nizam, Abg Kamaruddin and Mohamad Zulhuschmi, Mohamad Afif Zulhusmi (2024) Real-Time Monitoring of Modular Carbon Capture Machines with Sensor Networks and Node-RED. In: 2024 IEEE 10th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA), 30-31 July 2024, Bandung, Indonesia.

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Abstract

Abstract— Carbon Capture (CC) technology captures carbon from the air for utilization or storage. Heavy industries utilize CC to reduce carbon emissions; however, there are no suitable CC solutions for micro, small, and medium industries (MSME). This paper investigates a real-time carbon dioxide (CO2) monitoring framework for fishery smoking machines used by cottage industries. The proposed CO2 monitoring system uses a wireless data transmission system with the XBee Pro module. Data is sent to Node-RED software for collection, monitoring, and analysis, providing stable data transmission. A controlled experiment was conducted to determine the CO2 measuring reliability of the MG-811 CO2 sensor, which is installed in the filter box of the small-scale modular CC (MCC) machine, by comparing its measured data to the CO2 emissions measured manually with the Testo 440 CO2 digital measuring probe. Data was collected every 15 minutes over a fourhour span. It was found that the CO2 emissions measured using the proposed real-time setup were consistent with the values collected from the Testo 440 device. This demonstrates that the small-scale modular CC machine is a feasible and frugal engineering solution that can be used to sequester CO2 emissions in cottage industry settings. Furthermore, the results imply that a real-time monitoring system employing low-cost materials with minimal technological complexity, featuring wireless data transfer with sufficient sensitivity, has the potential to be deployed in heavy industries on a wider scale.

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