Optimization Design of an Industrial Carbon Emission Intelligent Monitoring System for Carbon Neutrality

This study aimed to optimize industrial carbon emission monitoring systems for enhanced accuracy and real-time responsiveness. It proposed an intelligent system that innovatively sinks multi-source carbon accumulation logic into the database layer (replacing traditional application-layer processing), integrated with dynamic factor version control and long short-term memory prediction models. These innovations yielded significant performance gains. Under thousands of concurrent users, key interface response time dropped from 7,465 ms to 40 ms (99.5% reduction), while carbon calculation error rates remained below 0.1%—far exceeding the International Standards Organization 14064 standard's 1% threshold. The proposed solution not only provides industry with efficient carbon management tools but also enables a paradigm shift from post-event statistics to real-time intelligent decision making, advancing global carbon neutrality goals.