Role of Artificial Intelligence in water industry

Role of Artificial Intelligence in water industry

Artificial Intelligence in water and wastewater utilities is still in its early stages, but it is having a huge impact where it is used, and most organizations already have the data they need to enhance their local water conditions.

A brief introduction to AI in the field of water

Collecting and analyzing past performance data to generate operational insights has long been a source of efficiency and innovation for many firms, both in the water industry and beyond.

However, the full extent of this approach's potential benefits has yet to be realized.

Data gathering and analysis used to be time-consuming, labor-intensive and frequently fruitless, but technological advancements have opened up new and exciting possibilities.

Automated data collecting, such as through the use of sensors and artificial intelligence, and the capacity to analyze massive amounts of data through machine learning constitute a significant advancement in this method of gaining insights to improve efficiency.

Artificial intelligence has acquired a lot of interest as a potent tool for solving real-world issues, thanks to its numerous uses.

Artificial Intelligence approaches have been used in water treatment and desalination in recent years to optimize the process and provide practical answers to water contamination and scarcity.

Applications of Artificial Intelligence are also predicted to minimize water treatment process operational costs by lowering costs and optimizing chemical utilization.

Several Artificial Intelligence models have accurately predicted the effectiveness of various adsorbents in the cleanup of a variety of contaminants from water.

This digital technology revolution can help innovative water utilities increase their efficiency.

Water utilities may leverage the knowledge and data available to make better decisions while improving service delivery and lowering costs by leveraging the power of artificial intelligence algorithms and big data analytics.

For water services beginning on this digital transition to enhance their water distribution operations in general, and to solve unaccounted-for-water concerns in particular.

AI improving the water industry

  • AI will drive a decade of technological investment in water and wastewater operations
  • AI in water and wastewater operations will result in huge OPEX
  • AI will be able to foresee and learn from critical situations at a faster rate
  • AI will help operators with superior decision-making intelligence
  • AI will help water and wastewater systems save energy
  • AI will keep the water clean at a low cost
  • AI will make data integrity easier
  • AI will maintain institutional knowledge
  • AI will hasten the transition to value-based asset maintenance.
  • AI will power genuinely smart water

Piloting artificial intelligence in water

To assist water utilities in this digital transition, national water sector policies must be revised.

Any water utility with digital data can benefit from current breakthroughs in artificial intelligence and big data.

Piloting the concept of Artificial Intelligence and Hydraulic Modeling for UFW will show how advanced network analysis algorithms improve operational efficiency and service delivery, as well as give the water utility a competitive edge by combining the power of Artificial Intelligence with big data obtained from the SCADA system, as well as data fed from different sensors on the water distribution system.

On the primary water distribution system, an Artificial Intelligence pilot examines numerical UFW and pipe burst assessment, as well as sensor failure methods (pipe diameter over 200 millimeters).

The Artificial Intelligence algorithms are put to the test on a single water distribution network sector or a small water distribution system chosen in collaboration with the water utility based on the following criteria:

1. The water distribution system should always be up to 800 kilometers long, with linear pipe length and characteristics (pipe size, location, and material) provided in digital format (GIS or Hydraulic Modelling 1.0) with adequate precision;

2. The water distribution system shall contain a minimum density of sensors (pressure gauges, micrometers and customer meters) with at least two years of historical pressure and flow data, as well as the digitized status of pumps and valves.

3. The availability of a traditional hydraulic model, which would be advantageous but not essential.

References

[1] Jenny, H., Alonso, E. G., Wang, Y., & Minguez, R. (2020). Using Artificial Intelligence for Smart Water Management Systems. (online) available at: https://www.adb.org/sites/default/files/publication/614891/artificial-intelligence-smart-water-management-systems.pdf

[2]10 Ways AI is Changing the Water Industry, 27 April (online) available at: https://www.innovyze.com/en-us/blog/ai-in-water-10-ways-ai-is-changing-the-water-industry

[3] Alam, G., Ihsanullah, I., Naushad, M., & Sillanp??, M. (2022). Applications of artificial intelligence in water treatment for optimization and automation of adsorption processes: Recent advances and prospects. Chemical Engineering Journal,?427, 130011. (online) available at: https://www.sciencedirect.com/science/article/abs/pii/S1385894721015965

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