Internet of Things and Artificial Intelligence for Carbon Emissions Monitoring and ForecastingA Systematic Review of Smart Environmental Accounting Systems

Why It Matters

Real‑time emissions data and accurate forecasts are essential for corporate carbon reporting, regulatory compliance, and investment decisions, directly influencing climate‑related risk management. Unified digital platforms could streamline measurement, reporting, and verification, accelerating the transition to net‑zero targets.

Key Takeaways

• IoT sensor networks provide continuous, location‑specific emissions data.
• AI models achieve high accuracy in short‑term carbon forecasts.
• Integration gaps hinder seamless carbon accounting and verification.
• Unified IoT‑AI platforms could streamline MRV processes.
• Research calls for standards to align monitoring with reporting frameworks.

Pulse Analysis

The accelerating pace of climate change has forced companies and governments to move beyond annual, spreadsheet‑based carbon inventories toward continuous, data‑driven accounting. Traditional methods rely on manual data entry and periodic site visits, which introduce delays and inconsistencies that can obscure true emissions profiles. As investors demand greater transparency and regulators tighten disclosure rules, the need for real‑time, verifiable carbon data has become a strategic priority across sectors ranging from manufacturing to logistics.

Internet of Things devices—such as low‑power gas sensors, smart meters, and satellite‑linked monitoring stations—are now capable of capturing granular emissions data at the point of source. When paired with advanced AI algorithms, these streams can be transformed into short‑ and medium‑term forecasts with predictive accuracies rivaling conventional statistical models. The systematic review underscores that AI‑enhanced forecasting not only improves the timeliness of emissions reporting but also enables scenario analysis for policy testing and operational optimization, offering firms a competitive edge in sustainability planning.

Despite these technological advances, the review identifies a critical shortfall: most IoT and AI solutions operate in silos, disconnected from established carbon accounting standards such as the GHG Protocol. This fragmentation hampers the verification process and limits the credibility of reported figures. Developing integrated platforms that embed IoT data capture, AI forecasting, and standardized accounting workflows could streamline measurement, reporting, and verification (MRV) while reducing compliance costs. For businesses, such unified systems promise more accurate risk assessments, better alignment with ESG investor expectations, and a clearer pathway toward net‑zero commitments.