Wellness TechGroup’s role in the SMART-Plant project

The European project publishes a fact sheet that includes our Online Energy and Greenhouse Gas Monitoring and Control.

The SMART-Plant project will test the viability of circular management of urban wastewater and the environmental sustainability of purification systems, as well as the co-benefit and scaling of water solutions through the integral management of the life cycle of associated costs.

The project, financed by the European Commission and coordinated by the Università Politecnica delle Marche, has the participation of the Wellness TechGroup, whose objectives include providing support and support to the water sector to improve and ensure environmental protection. All this through the application and validation of energy monitoring systems, as well as their customization, installation and supervision.

Solution’s infograph.

«SMART-Technologies for resource recovery aim to move towards low-carbon and energyefficient wastewater treatment. Real-time monitoring of energy demand and greenhouse gas emissions during process operation is crucial to inform operators on the actual performance of SMARTechs, optimise their operation, and detect process disturbance. Based on data from energy meters and greenhouse gas sensors Wellness TechGroup has developed a web application platform to continuously record and display energy consumption and operational carbon footprint of the processes together with sustainability indicators and other metrics conventionally monitored in wastewater treatment.

In the SMART-Plant project, Wellness TechGroup physically installed real time energy consumption and greenhouse gas meters at all demonstration sides. All measured variables are directly shown in an online tool to give the plant operator optimal insight and control. On top, Brunel University developed structured approaches to analyse heterogenous data from online sensors and laboratory analyses such as data mining techniques for pattern recognition, dependencies identification, and outliers detection.»

Read the whole project’s fact-sheet.