Artificial intelligence in water cycle management - IDRICAArtificial Intelligence (AI) is the technology everyone is talking about this year, an...
Published on by Water Network Research, Official research team of The Water Network
Artificial Intelligence (AI) is the technology everyone is talking about this year, and it is a trend that water utilities cannot ignore. However, how can artificial intelligence really help in water cycle management?
Artificial intelligence is one of the most important and exciting technologies of the 21st century. In fact, it has increased its ranking in the main search engines by 139% compared to last year, which gives an idea of the attention it is receiving.
Artificial intelligence is a field of computer science that focuses on creating machines capable of performing tasks that would normally require human intelligence, such as reasoning, learning and problem-solving. This is a characteristic of all algorithms, including those that are capable of learning and those that are not: the goal of all algorithms is to perform calculations to solve problems. Artificial intelligence now introduces the “learning” part, which is relatively new.
This is why this technology is key in almost every field. However, the advantages it can offer the water cycle mean that artificial intelligence has become an essential element for more sustainable management of water resources:
One of the main advantages of AI is its ability to process large amounts of data and learn from it. This enables data scientists and software engineers to create algorithms and systems that can identify data patterns and trends which, in turn, can help water utilities make more informed and more accurate decisions.
Artificial Intelligence
Along these lines, the paper “Trends in Artificial Intelligence for 2022: building learning into processes“, outlined four types of machine learning:
Supervised: in this type of learning, prior knowledge of the problem is used as the valid hypothesis to be able to characterize new cases in the future.
Unsupervised: this is used when an employee has no previous knowledge about the issue to be solved, but there is information about its characteristics.
Semi-supervised: In this case, we have data that gives us prior knowledge of the problem and other data that does not. Both sets enrich the information needed to solve the problem.
By reinforcement: this one differs in that it is rule-based and deals with action/reaction type information to be modeled, the objective of which is to maximize the reward function.
Another advantage is that if artificial intelligence is added to standard automation, it controls and reduces errors, improving the accuracy of the results, which are calculated at high computational speed thanks to its supporting infrastructure. Thus, utilities can make better decisions as they have real-time information about what is happening in the infrastructure
Five applications of artificial intelligence in the water cycle
There is no doubt that artificial intelligence (having an increasing impact on water cycle management, but how can it really be applied, and where can it be of real assistance?
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- AI