How it works
Digital twin module
By taking the historical data and integrating with sensor to get real-time data we make a digital twin of your manufacturing facility, non-residential building or water utility. Through this we achieve a precise simulation of the operational process, accurate correlation of dependencies and a safe environment to design and test changes in your manufacturing process.
Using the digital twin as a foundation we then run our algorithms and optimize the operational model. By controlling the frequency of pumps or other aggregates, directly integrate our solution with controllers, and at the same time use a rule-based approach to ensure safe work of aggregates we can save between 15 and 45% of cost for energy for the specific process.
APPLICATION FOR WATER UTILITIES
GridMetrics' for Water Utilities is a software solutions for automated real-time supply pump control. Through machine learning we predict future demand for a given water tank based on historical demand data. This information is then combined with the current water level in tanks and current price for electricity to generate a schedule for pump usage and what frequency should be used.
The software is built on top of EPANET 2.0, which is used to create digital twin of the pumping station and simulate its operations in real-time using live data from the station's sensors. The software allows for offline simulations to be carried out with historical or mock data to identify additional optimization opportunities. The system can be used to fully automate the controlling process or to provide insight and serve as an advisory function to the operators.
DEMAND FORECASTING, PUMP FREQUENCY CONTROL, ELECTRICITY COST CORRELATED
DIGITAL TWIN & ADAPTING ML
INTEGRATION & TESTING
MAINTENANCE & IMPROVEMENT
We first started as an AI agency working on various projects. Gaining experience in the energy and manufacturing sector we decided to focus our approaches on building products that combine technology, domain expertise and scientific research.
Through the usage of digital twins and process optimization, we help companies increase their efficiency of both production and energy usage. This also lowers their CO2 footprint and cost for carbon certificates.
By harnessing the power of Machine Learning, Scientific Research and Industry Expertise we achieve significant savings.