IoT Based Smart Industrial Carbon Emission Monitoring and Alert System | IJEEE Volume 9 – Issue 3 | IJEEE-V9I3P3
IJEEE
International Journal of Electrical Engineering and Ethics
ISSN 2456-9771 · Peer-Reviewed · Open Access
📚 Volume 9, Issue 3
📅 June 15, 2026
📄 Pages 8–18
🔖 ID: IJEEE-V9I3P3
IoT Based Smart Industrial Carbon Emission Monitoring and Alert System
Author(s)
Dr. Infant Vinoth C, Dr. Sundar G, Archana N, Divya G G, Subivarsha D, Vishnupriya G
Abstract
Industrial carbon emissions are a major contributor to environmental pollution and climate change. Continuous monitoring of these emissions is essential to ensure compliance with environmental regulations and to promote sustainable industrial operations. This project presents an Internet of Things (IoT)-based Smart Industrial Carbon Emission Monitoring and Alert System designed to monitor carbon-related gases in real time and provide instant alerts when emission levels exceed predefined limits. The proposed system utilizes gas sensors, such as CO and CO2 sensors, connected to a microcontroller (ESP8266/ESP32 or Arduino) for data acquisition. The collected data is transmitted to a cloud platform through IoT technology, enabling remote monitoring and analysis. A web dashboard or mobile application displays real-time emission levels, historical trends, and system status. When the concentration of harmful gases exceeds the safe threshold, the system automatically generates alerts through notifications, emails, or alarms to notify plant operators and environmental authorities. The implementation of this system helps industries reduce environmental impact, improve workplace safety, and comply with emission standards. By providing accurate, continuous, and remote monitoring capabilities, the proposed solution offers a cost-effective and efficient approach to managing industrial carbon emissions.
Keywords
IoT, Carbon Emission, Gas Sensors, Industrial Monitoring, Alert System
Conclusion
The IoT-Based Smart Industrial Carbon Emission Monitoring and Alert System provides an effective solution for monitoring and controlling industrial carbon emissions in real time. The system utilizes gas sensors, ESP32/Arduino microcontrollers, cloud computing, and wireless communication technologies to continuously measure carbon dioxide (CO2) and other harmful gas concentrations. The collected data is processed and transmitted to a cloud platform, enabling remote monitoring through web and mobile applications.
The implementation results demonstrate that the system can accurately detect abnormal emission levels and generate immediate alerts whenever predefined safety thresholds are exceeded. This helps industries take timely corrective actions, reduce environmental pollution, and improve workplace safety. The cloud-based monitoring feature further enhances accessibility by allowing users to monitor emission levels from any location. The proposed system is cost-effective, reliable, and suitable for industrial environments. It supports environmental sustainability by helping industries comply with pollution control regulations and reduce their carbon footprint. Future enhancements may include Artificial Intelligence (AI)-based prediction models, machine learning techniques for emission forecasting, and integration with automated pollution control mechanisms.
The implementation results demonstrate that the system can accurately detect abnormal emission levels and generate immediate alerts whenever predefined safety thresholds are exceeded. This helps industries take timely corrective actions, reduce environmental pollution, and improve workplace safety. The cloud-based monitoring feature further enhances accessibility by allowing users to monitor emission levels from any location. The proposed system is cost-effective, reliable, and suitable for industrial environments. It supports environmental sustainability by helping industries comply with pollution control regulations and reduce their carbon footprint. Future enhancements may include Artificial Intelligence (AI)-based prediction models, machine learning techniques for emission forecasting, and integration with automated pollution control mechanisms.
References
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[5] Ghayvat, H., Mukhopadhyay, S., Gui, X., Suryadevara, N. WSN and IoT-Based Smart Homes and Their Extension to Smart Buildings. Sensors, Vol. 15, No. 5, 2015, pp. 10350-10370.
[6] Pawar, P., Patil, S. Real-Time Industrial Pollution Monitoring Using IoT Technology. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2020.
[7] Rajalakshmi, P., Devi, M. Smart Environmental Monitoring System Using IoT and Cloud Computing. International Journal of Advanced Research in Computer and Communication Engineering, Vol. 7, Issue 4, 2018.
[8] World Health Organization (WHO). Air Pollution and Health Report. WHO Publications, Geneva.
[9] Madhuvanthani Rajendran, G. Sundar, Performance Improvement of AGC Using Novel Controllers in a Multi-Area Solar Thermal System under Deregulated Environment published in Electric Power Components and Systems, Vol. 54, No. 6, pp. 847-862, July 2023.
[10] Madhuvanthani Rajendran, G. Sundar, Influence of the output impedance of an inverter on its droop control strategies in a microgrid, published in Indian Journal of Engineering and Material Sciences, Vol. 29, No. 4, 2022.
[2] Xu, L. D., He, W., Li, S. Internet of Things in Industries: A Survey. IEEE Transactions on Industrial Informatics, Vol. 10, No. 4, 2014, pp. 2233-2243.
[3] Kumar, A., Singh, R. IoT-Based Air Pollution Monitoring System Using Wireless Sensor Networks. International Journal of Engineering Research and Technology (IJERT), Vol. 8, Issue 6, 2019.
[4] Bacco, M., Barsocchi, P., Ferro, E., Gotta, A., Ruggeri, M. The Internet of Things for Smart Cities. Journal of Internet Services and Applications, Vol. 8, No. 1, 2017.
[5] Ghayvat, H., Mukhopadhyay, S., Gui, X., Suryadevara, N. WSN and IoT-Based Smart Homes and Their Extension to Smart Buildings. Sensors, Vol. 15, No. 5, 2015, pp. 10350-10370.
[6] Pawar, P., Patil, S. Real-Time Industrial Pollution Monitoring Using IoT Technology. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2020.
[7] Rajalakshmi, P., Devi, M. Smart Environmental Monitoring System Using IoT and Cloud Computing. International Journal of Advanced Research in Computer and Communication Engineering, Vol. 7, Issue 4, 2018.
[8] World Health Organization (WHO). Air Pollution and Health Report. WHO Publications, Geneva.
[9] Madhuvanthani Rajendran, G. Sundar, Performance Improvement of AGC Using Novel Controllers in a Multi-Area Solar Thermal System under Deregulated Environment published in Electric Power Components and Systems, Vol. 54, No. 6, pp. 847-862, July 2023.
[10] Madhuvanthani Rajendran, G. Sundar, Influence of the output impedance of an inverter on its droop control strategies in a microgrid, published in Indian Journal of Engineering and Material Sciences, Vol. 29, No. 4, 2022.
📋 How to Cite This Paper
Dr. Infant Vinoth C, Dr. Sundar G, Archana N, Divya G G, Subivarsha D, Vishnupriya G (2026). IoT Based Smart Industrial Carbon Emission Monitoring and Alert System. International Journal of Electrical Engineering and Ethics, 9(3), 8–18. ISSN: 2456-9771. DOI: https://doi.org/10.5281/zenodo.20706253
