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The value of asset intelligence in the water sector

Minsait supports water companies as they face the challenge of digital transformation and the modernization of the sector through the use of real-time information.

Effective water resources management is a critical global challenge in the face of population growth, climate change, urbanization, and industrial and agri-food activities. To address this complex issue, the water sector is increasingly recognizing the critical role of real-time information in facilitating sustainable water management practices.

Real-time information refers to data collected and transmitted instantly, allowing decision-makers to access up-to-date information on water availability, quality and use patterns.

This information is essential for a variety of stakeholders, including policymakers, water utilities, agricultural industries, environmental agencies, and the general public. 

Published in SWM Bimonthly 19 - September 2023
SWM Bimonthly 19

The value of real-time data has an effect on improved decision-making, efficient water resource management and environmental protection, as well as public participation and awareness.

To achieve an efficient digital environment, several essential aspects related to asset intelligence must be addressed, such as the use of sensors and the Internet of Things (IoT), data storage & management, and data analytics.

The water sector is increasingly recognizing the critical role of real-time information in facilitating sustainable practices

Minsait, Indra's leading company in digital transformation and information technologies, develops projects in different sectors, with more than 20 years of experience in the water sector. These solutions cover the entire process, from data collection in the field to data analysis from different perspectives, including the transmission, organization, storage, analysis and utilisation of the information.

Asset intelligence

Sensors and IoT

Connectivity between assets, people and businesses is growing exponentially, and the IoT strategy will be increasingly relevant to avoid the congestion and vulnerability of systems. Beyond the digital transformation, IoT growth is driven by the need to optimize costs and increase efficiency, as well as develop new use cases, improve processes and increase process quality and flexibility.

Among the main advantages are fewer maintenance trips, optimized asset operations, reduced CO2 emissions, as well as increased productivity, flexibility, quality and speed of operations. IoT allows us to address the challenges of our customers with disruptive, dynamic and scalable solutions that adapt to their growth needs and to the creation of new business models, sharing information with citizens in a public water management model that is sustainable.

The value of real-time data has an effect on improved decision making, efficient water resource management and environmental protection

The main objective of an IoT ecosystem for the water sector is the acquisition, processing and provision of good quality data – such as data on water flow and quality, pressure, leaks, asset status (pumps, valves, tanks, etc.) – through a flexible and scalable architecture, but also the comprehensive management and governance of all the devices deployed to equip the physical world with sensors, regardless of their origin, as well as their communications (deployment of distributed computing on any type of asset in the water abstraction, treatment or distribution network, among other functions).

Minsait has developed Onesait Edge, a different IoT platform proposal that brings together multiple capabilities, accelerators and frameworks that allow us to develop value-added use cases for multiple industries, and especially for the water sector.

Data storage and management

The acquisition and structuring of real-time process information is essential for the digitalisation of the water sector. One of the areas that will benefit most from the acquisition of real-time information is the monitoring and management of drinking water distribution networks. This wealth of information must be structured in a way that facilitates subsequent use and analysis, as well as having data available for use in other solutions.

These solutions cover the entire process, from data collection in the field to data analysis from different perspectives

Minsait has developed Onesait Assets Engine, an open, scalable and secure asset data management platform designed to meet the needs of customers in various industrial sectors. Assets Engine enables the integration of information from any area of the business, with the capacity to connect with different and heterogeneous sources of information.

Its three fundamental components are firstly inventory management, flexible and comprehensive, capable of including any type of asset, taking into account existing relationships; secondly, IoT device management, ensuring secure and optimal transmission of information; and thirdly, monitoring with information visualization capabilities, using management dashboards and reports.

Real-time information management tools are the foundation on which to develop an effective digitalisation strategy. Having the infrastructure in place to capture and store operational information in a cross-cutting and transparent manner is the only way to enable data-driven decision-making and foster a business culture geared towards efficiency and continuous improvement.

Data analytics

Once the data have been obtained and consolidated, asset management applications are responsible for extracting the operational value they contain, usually considering them from different perspectives. At this point, the type of analysis to be performed can be divided into two categories: ad hoc analytics (designed and implemented specifically in each case) or systematic analytics integrated into the production processes, which consists of applying techniques to certain common cases that are cross-cutting in scope.

SaaS solutions avoid infrastructure investments and provide scalability that allows projects to be approached gradually

A typical example of the second point is the family of solutions grouped under the name APM (asset performance management). The APM solution developed by Minsait, Onesait Assets APM, consists of three main modules: APM Predictive, with the use of AI (machine learning) algorithms for the early detection of anomalous operating conditions; APM Performance, with analyses aimed at the energy efficiency of assets or systems; and APM Asset Health, aimed at optimizing maintenance processes based on asset health and risk indicators.

Each of the above modules generates results that are used specifically in operation & maintenance (O&M) processes, thus resulting in a positive impact on the bottom line.

The use of these tools is very simple and within the reach of any employee involved in O&M. The complexity of the numerical methods is not apparent in the use of the solution.

The solutions of the APM family have proven their effectiveness in different sectors and many companies have integrated them into their operational processes in a very satisfactory way.

Water companies must be aware that data use involves a complex value chain that goes from the asset to decision making

Another type of analytical solution is the digital twin, increasingly applied in asset management. A digital twin combines process data with a process model to generate virtual sensors, detect anomalies or optimize the operation of a system. The possibilities associated with digital twins are well understood when you consider that a company's assets are typically optimized individually by design.

But what happens when multiple assets are connected in a given system? It is quite possible that the overall system optimum does not match the individual asset optima, so the digital twin becomes a great help in finding it.

Digital twin projects involve a series of capabilities related to asset intelligence (sensors, IoT, information management, modelling) that Minsait has in its portfolio of solutions.


There is significant potential for improvement in the digitalisation of production process information in water companies, but we must be aware that data use involves a complex value chain that goes from the asset to decision-making. For maximum effectiveness, it is essential to address the problem as a whole, enabling the present use cases without compromising the new possibilities that will come in the future.

It is important to note that the availability of solutions through a SaaS (software as a service) model facilitates the democratization of their use, as it avoids investments in infrastructure and provides scalability that allows projects to be approached gradually, thereby limiting risk.

Examples of the specific impact of digital solutions on business results include reductions of around 5% in energy consumption (with a subsequent benefit for CO2 emissions), lower maintenance costs of physical assets by 15% (due to the reduction of failures associated with predictive monitoring) and a reduction in the maintenance of digital assets of approximately 45%.