Intelligent Carbon Management: Integrating AI, Industrial Data and Decarbonization Strategies

Pierre Azoulay

Intelligent Carbon Management: Integrating AI, Industrial Data and Decarbonization Strategies

Author(s)	Pierre Azoulay
Country	United States
Abstract	The transition toward a low-carbon economy requires organisations to move beyond conventional carbon accounting and develop intelligent systems capable of continuously measuring, predicting, optimising, and reducing greenhouse-gas emissions. Rapid advances in artificial intelligence, industrial Internet of Things technologies, digital twins, cloud computing, and advanced analytics are creating new opportunities for intelligent carbon management across manufacturing, energy, transportation, buildings, and supply chains. This paper examines the integration of AI, industrial data, and decarbonisation strategies as an emerging framework for achieving measurable and economically viable emissions reductions. It explores AI applications in emissions monitoring, carbon forecasting, energy optimisation, process control, predictive maintenance, renewable-energy integration, carbon capture, supply-chain optimisation, and industrial decision support. Particular attention is given to the integration of operational technology data with enterprise sustainability information, lifecycle assessment, Scope 1, Scope 2, and Scope 3 emissions, and carbon-intensity metrics. The paper proposes an Intelligent Carbon Management Framework comprising five interconnected layers: data acquisition, carbon intelligence, predictive analytics, optimisation, and strategic decarbonisation. It argues that AI should not be viewed simply as a reporting or forecasting tool but as an enabling technology for continuously adaptive carbon reduction. At the same time, challenges related to data quality, interoperability, model transparency, cybersecurity, greenwashing, organisational capability, and the energy consumption of AI itself must be addressed. The paper concludes that intelligent carbon management can become a strategic component of industrial transformation when AI-driven insights are connected directly to operational decisions, investment planning, and measurable emissions outcomes.
Keywords	Intelligent Carbon Management, Artificial Intelligence, Industrial Data, Decarbonisation, Carbon Accounting, Industrial IoT, Digital Twins, Scope 1, Scope 2, Scope 3, Carbon Intelligence, Sustainable Manufacturing.
Field	Engineering
Published In	Volume 6, Issue 5, September-October 2024
Published On	2024-10-31

View / Download PDF File

About AJAMRI Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+1-872-302-3851	editor@ajamri.com

American Journal of Advanced Multidisciplinary Research and Innovation

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Intelligent Carbon Management: Integrating AI, Industrial Data and Decarbonization Strategies

Share this