Data analytics for integrated water cycle management

At this point, you are surely aware that the quality and accuracy of data are the keys to any industry.

Even more so if we are talking about water cycle management companies, where it is necessary to monitor multiple variables involved in each stage.

The digitalization of water is a fact that has reached companies in the sector. Technologies such as AI, the Internet of Things, and Mixed Reality are increasingly present.

In this post, we want to show you the importance of data analytics and other technologies to improve water cycle management.

Would you like to know the benefits of better data analysis and monitoring in water management?

Keep reading! 🙂

What is data analytics and how does it help water sector companies?

Data analytics is simply about turning a massive amount of data into practical and functional information.

That is, trying to gain knowledge through technical details that we could not collect and classify without Big Data and data analysis technologies that help us detect patterns and trends, control variables, or make predictions.

The Internet and new technologies have favored the continuous collection of a large amount of data by individuals and companies.

Right?

Well, this reality also applies to the integral water cycle industry, where it is possible to gather a multitude of technical data through sensors about the composition and variables of water in the different phases of the integral water cycle.

Water cycle management: main phases

Behind the entire process of managing the integral water cycle, there is an exhaustive job of analysis, monitoring, storage, and regulation of water.

And as you can imagine, Data Analytics helps us systematize information collection, thus optimizing processes at each phase.

In summary, there are at least five phases of the integral water cycle that make it possible for us to have drinking water:

• Collection: In this first stage, water is collected from rivers, reservoirs, aquifers (or even seawater) to store, transport, and start the purification process.
• Storage: The water is collected in reservoirs, which, if we talk about the urban cycle, will be destined for the supply of homes and cities, but it can also have other destinations, such as industry or agriculture.
• Distribution: The water collected from underground or sea sources is transported through appropriate pipelines for treatment.
• Sanitation: Since the collected water is not yet suitable for human consumption, a series of treatments are applied in treatment plants (and desalination plants, in the case of seawater) to ensure that it meets the corresponding sanitary conditions.
• Reuse: Finally, wastewater is sent to the treatment plant for processing and transformation. It is generally reused (industrial, agricultural, etc.).

Water digitalization and new technologies

Water digitalization involves using new technologies to improve efficiency in each of the processes in water cycle management.

First, it is necessary to collect, store, and analyze data, and then use it intelligently through AI and visualization solutions that support water management professionals in the various processes.

The goal?

• Obtain the best quality water.
• Guarantee sanitary conditions.
• Ensure that the water meets the desired chemical variables.
• Make sustainable use of water resources.
• Achieve greater automation and productivity in water cycle management companies.

For example, imagine sensors installed in water sources to detect areas with the highest quality and precision in the water. This would help improve decision-making in the collection phase or anticipate or prevent possible changes in the natural environment affecting water quality.

Data collection and data analytics allow detecting patterns and closely monitoring data, as well as developing machine learning solutions to improve automation.

Just as technologies can be used in the supply phase, many companies in the sector are implementing data analytics solutions for the sanitation process and wastewater treatment.

The role of data analytics in water sanitation and reuse

To carry out the water sanitation process, it must meet certain requirements.

It must be colorless, odorless, and meet sanitary requirements.

Water also contains different components: sodium, calcium, chlorine, magnesium, sulfur, phosphorus... and they must be present in a certain amount to be suitable for human consumption. For example, mineral water must come from underground sources and have a lower mineralization degree (<1.5 g/l).

Controlling the various chemical elements during the water sanitation process is essential to obtain water that meets the desired requirements, both sanitary and market-wise, depending on our product.

Data Analytics is playing an increasingly important role in the phases of integral water cycle management.

Data analytics involves collecting and analyzing a massive amount of data to draw conclusions from the behavior patterns of different variables.

How to apply data analytics to the water sanitation process or wastewater treatment? Improvements can be implemented through various technologies, but Big Data, IoT, Artificial Intelligence, and Mixed Reality are among the most important.

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