Compliance Monitoring Simplified with PEMS.ai
A cost effective software alternative to your traditional hardware-based Continuous Emissions Monitoring System(CEMS).
Faster, Better, Affordable
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Predictive Emissions Monitoring Systems (PEMS) are a software-based solution for emissions monitoring. PEMS is generally regarded as a cost-effective alternative to traditional hardware based Continuous Emissions Monitoring Systems (CEMS). There are three main model types used in PEMS - neural networks. first principles, and statistical hybrid models
CEMS, or Continuous Emissions Monitoring Systems are hardware analyzer based solution for emissions monitoring. CEMS collect air samples from the emission source using probes, condensers, heated sample lines, and analyzers. The different types of CEMS can be catogorized into Dilution, Extractive and FTIR CEMS.
PEMS.ai is a neural network based PEMS. Here is a brief explanation on how it works:
1. Data Collection
First, Historical process and emissions data are collected.
2. Model Training
Next, Using deep learning techniques, the neural network learns correlations between the input process data and the emissions produced, building a predictive model. The model can be retrained easily as more data is collected, improving prediction accuracy.
3. Deployment
When deployed at a site, real-time process data is fed into the model and predicted emissions are generated. After that, an initial certification audit is performed where the predicted emissions are verified using reference methods (i.e: Mobile CEMS).
