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| Title | Leveraging The Industrial Internet Of Things (Iiot) For Real-Time Co2 Monitoring, Measurement And Visualization: Technologies, Applications And Future Directions |
|---|---|
| ID_Doc | 35137 |
| Authors | Christensen M.S.F. |
| Year | 2025 |
| Published | Communications in Computer and Information Science, 2328 |
| DOI | http://dx.doi.org/10.1007/978-3-031-78572-6_3 |
| Abstract | Global CO2 emissions reduction requires industries to manage and understand their CO2 emission levels in real-time. This paper examines the Industrial Internet of Things (IIoT) for real-time monitoring, measurement, and visualization of reducing CO2 emissions in industrial and environmental domains. Methodology: The methodology consists of a literature review based on peer-reviewed publications and use cases to explore the current state and practical implications. Furthermore, a technical analysis of IIoT systems, CO2 sensors, and data processing techniques is also identified. Results: IIoT systems can support CO2 emission monitoring and accuracy optimization in industrial domains by combining CO2 sensors, wireless communication, and data fusion techniques. In addition, machine learning and artificial intelligence can be used to reduce anomalies in CO2 sensor readings and predictive maintenance of systems. Challenges: Challenges include interoperability, data security and system scalability. To resolve these issues standardized communication protocols, data security methods and implementation barriers should be improved. Future Directions: To enhance data processing and security features, future work should focus on integrating edge computing, artificial intelligence, machine learning, and blockchain techniques. In addition, data visualizations and cost-effective solutions should also be in focus, to provide more adoptable IIoT systems in industrial domains. Conclusion: As IIoT systems and CO2 sensor technologies evolve, IIoT systems can contribute significantly to increasing global air quality and CO2 emission control in industry, agricultural, and urban areas. © The Author(s) 2025. |
| Author Keywords | Air Quality; Blockchain Technology; Carbon Footprint Monitoring; CO2 Monitoring; Edge Computing; Emission Management; Environmental Sustainability; Industrial Internet of Things (IIoT); Machine Learning; Predictive Maintenance; Real-Time Data Processing; Security and Privacy in IIoT; Smart Buildings; Smart Cities |
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