Description:

“PEMS” (Predictive Emission Monitoring System) is a data driven solution used in various industries, this solution is particularly relevant with industries that have emissions and environmental compliance requirements. The aim of this solution is to monitor and predict the emissions of pollutants and greenhouse gases produced during operation. PEMS combines real-time data acquisition, advanced modeling techniques, and sensor technology to provide continuous and accurate monitoring of emissions. This enables organizations to maintain compliance with environmental regulations, reduce emissions, optimize processes, and make informed decisions to minimize their environmental impact.
“PWOA” (PlantWeb Optics Analytics) is a part of Emerson’s Plantweb digital ecosystem, which offers a range of technologies and services aimed at improving the efficiency, reliability, and safety of industrial processes. Plantweb Optics Analytics specifically focuses on data analytics and diagnostics within this ecosystem.
The objective of this internship is to build a PEMS solution based on PWOA platform.

Scope Of Work:

Within this context, we propose this end of year project to design and implement a PEMS application which could ensure the following functionalities

Deliverables:

Key Words:

PEMS, PWOA, Data science, Machine Learning, Modeling, Stochiometric.