EMASESA (Empresa de Abastecimiento y Saneamiento de Aguas de Sevilla S.A.) is responsible for water cycle management in the Spanish city of Seville and its metropolitan area. The utility supplies approximately 100 hm3 of drinking water to 1.4 million residents in 12 municipalities every year, as well as distributing raw water to 31 municipalities, serving a total area of 1,220 km2. It manages a 4,000 km network, six water reservoirs, 35 pumping stations, 28 municipal tanks, three drinking water treatment plants (DWTPs), and six wastewater treatment plants (WWTPs).
Challenge
EMASESA's aim was to reduce water consumption, increase water and energy efficiency, and enhance customer service in the municipalities it serves. This required improving the monitoring and control of its operations and assets.
In its 2030 Strategic Plan, the utility included the integration, processing and dissemination of large amounts of data from different sources, including those generated by smart meters, as a starting point for digitally transforming its processes. The use of advanced analytics, AI, and machine-learning algorithms was required to improve decision-making at the technical, operational, and production levels.
In addition, it was vital to foster more responsible water use amongst the population. The vast majority of EMASESA’s customers used shared meters, which discouraged them from adopting more responsible practices. In fact, only 1,344 users had an individual meter in 2022. Reducing consumption in a region characterized by increasingly frequent droughts and shortages was absolutely imperative.
Solution
The Xylem Vue platform was implemented to integrate data from 70,000 signals, 200 sectors, multiple sensors, 170,000 conventional meters, 180,000 smart meters and other types of data in a single repository, thanks to its big data capabilities and Smart Water Engine (SWE). Its data intake layer brings together information from different sources, which is subsequently acquired, digested, and stored in the data lake. The Domain Master Data (DMD) standardizes and unifies the data, which is centralized in the IoT layer of the platform for further exploitation. The solution seamlessly integrates the information produced by EMASESA and third parties, including customer management systems.
The project provided EMASESA with a Data Science Framework (DSF) for controlled analysis and integration of information into the system through advanced algorithms, which can be connected to future AI and machine-learning modules. As part of its Operational Intelligence module, Xylem Vue also includes a BI panel and advanced dashboards where data can be visualized and exploited by all business areas to improve processes.
Additionally, the implementation of specific drinking water and wastewater applications gave EMASESA better control over its infrastructure. The drinking water applications deployed were Xylem Vue’s Meter Data Analytics, for AMI/AMR monitoring; Leak Detection, for advanced leak location; Real-Time What-If Scenarios, for developing the network’s digital twin, and Plant Management, for advanced DWTP monitoring and operations. The wastewater solution chosen was Xylem Vue’s Plant Management application. The implementation of Xylem Vue enables the future deployment of additional applications and use cases depending on the utility’s needs.
The project included a personalized consultancy and training service for internal and external staff and the development of a process map to assess operational performance. It also included adapting the platform to cater for the needs of potential new clients and end-customers. In parallel, the utility also rolled out a plan to replace shared meters with individual meters.
Outcomes
The Xylem Vue platform has boosted digital transformation in EMASESA, centralizing information from different sources to optimize management, enhance customer service, and make data-driven decisions. Water balances are calculated continuously across the supply network thanks to the implementation of AI algorithms and automated processes. This helps EMASESA to measure network performance improvements, reduce non-revenue water (NRW), and detect fraud.
Moreover, the advanced data insights and anomaly detection capabilities have enabled the utility to reduce operational costs and comply with environmental obligations. The system also supports forecasting and preventing water quality issues, predicting consumption demand, and implementing predictive maintenance strategies, thus contributing directly to increasing water, energy, and economic efficiency.
Xylem Vue has also helped the Spanish utility to adapt to climate change thanks to its simulation and scenario modeling tools, included in its digital twin. The reduction of per capita water consumption is also bringing EMASESA closer to achieving its sustainability goals.