While the importance of both new sensor technologies and fast data strategies is underlined in the earlier sessions, in this last session we are going to focus upon practical international and cross sectoral collaboration options to identify economic project opportunities. How can we use big and fast data to optimize water resources, save energy and operational expenses. Based on a series of pitches an interactive discussion will focus upon creating collaborating opportunities between water utilities and technology providers. The aim is to create (international) follow up projects.
Introducing speaker(s): Joan Carles Guardiola Herrero (Eurecat), Mike Everest (Meniscus)
Anna di Mauro (Ctrl+SWAN), Gabriel Anzaldi (Eurecat)
Title: How can water utilities benefit from digital transformation?
Results from operational, customer and environmental perspectives
Joan Carles Guardiola Herrero, R&D engineer, Global Omnium, Valencia, Spain.
Joan Carles Guardiola, MSc Civil Engineer, Polytechnic University of Valencia. He is Innovation Engineer at Global Omnium / Aguas de Valencia and he is particularly involved in the conversion of the company into a technological front-runner in Digital Water. His focus is currently on the creation of a truly Smart Network and the development of IT solutions capable of leveraging all the potential from Big Data, Machine Learning and AI technologies.
Global Omnium’s digital transformation started more than 10 years ago when the company initiated its Smart Metering program. The company is currently one on the world leaders in this field, with around 700.000 units providing remote and detailed consumption information from customers. The city of Valencia is in fact the largest European city that is totally equipped with Smart Meters.
In order to cope with the billion data provided by the smart metering infrastructure, the company had to transform its IT infrastructure. As a result, Global Omnium started a process of digital transformation that currently is enabling the company leading the development of IT solutions, based on Big Data and advanced algorithms, which are facilitating the creation of new high-added value services, not only from the perspective of network operations and water efficiency, but also from customer’s and environmental perspectives.
Title: (Meniscus Analytics Platform, MAP) Sewer- Delivering predictive analytics of the sewer network
Showing the economic benefits of data analytics
MAP Sewer is a cloud based real time decision support tool that runs simplified hydraulic models across hundreds/thousands of sewer catchments and their associated pumping stations. MAP Sewer combines real time radar and forecast rainfall data to predict sewerage flows into pumping stations and across the whole sewerage network. It can predict flooding at pumping stations due to hydraulic overload and potential blockages and combined with sewer level sensing can be part of a smart solution to predict sewer blockages and associated pollution events. MAP Sewer also uses the predictive flow capability to identify when pumping stations can be turned off during high electricity tariff periods without running the risk of a pollution event.
MAP Sewer is scalable, highly flexible in that models can be readily changed/added, and very fast. It is in operational use in the UK, can be implemented quickly and requires minimal asset and catchment information. MAP Sewer also uses existing historical data on pump run hours and wet well levels to improve the accuracy of models and to validate results against actual performance.
Mike Everest MSc CEng, Managing Director, Meniscus System Ltd, UK
Mike Everest set up Meniscus in 1997 as a service company to “add value to operational data”. The original MCE web based calculation platform currently monitors energy and process analytics on over 2,000 water and wastewater treatment sites. In 2014 we developed our Meniscus Analytics Platform (MAP) which is a generic cloud based real time Big Data Analytics platform for integrating complex analytics into your own applications quickly and easily. MAP is currently used to deliver a range of solutions integrating real time and forecast rainfall data with operational data for the Water, Energy and Smart City sectors. It processes over 0.5 billion data points per day and delivers +100,000 predictions a second.
Prior to Meniscus, Mike set up a subsidiary of Anglian Water operating industrial wastewater treatment plant around the country. He also has five years international experience with the Schlumberger Group of Companies working on oil rigs in the Far East and South Africa. He has a 1st Class Honours degree from Leeds University in Fuel & Energy Engineering, an MSc from Imperial College and is a Chartered Engineer with the Institute of Energy.