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.
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?
The world’s population continues to grow (United Nations estimates that by 2037 we will reach 9 billion people), and with the consequent increase in demand for water, with 2.2 billion people not having access to drinking water services (UNICEF, 2019) AI is increasingly being used to optimize water management, identify and prevent potential emergencies, and improve water supply efficiency, among others. Five applications of artificial intelligence in water cycle management are listed below:
1. One of the ways in which AI is being used in water management is to monitor and analyze water cycle data. This includes checking water quality, tracking water use, and identifying potential problems in water supply infrastructure. AI is used to analyze large amounts of data in real time, enabling utilities to detect potential issues before they turn into crises.
2. Water demand management: AI can be used to predict water demand and to optimize water supply throughout the day. This can help water utilities reduce water waste and ensure that water demand is met effectively.
3. AI is also used to predict and mitigate potential risks associated with the water cycle. For example, flooding is a constant threat in many cities and communities. AI can be used to analyze weather and water level data and predict when flooding is likely to occur. This enables local authorities to take preventive measures and evacuate people from high-risk areas before it is too late.
4. In addition, AI can also improve water supply efficiency. This includes identifying leaks, detecting pressure-related problems and optimizing water flow. As stated in the whitepaper “Water Technology Trends 2023 report”, AI models can be used to optimize water supply, minimize costs, reduce water losses, and improve the energy efficiency of infrastructures. This can help reduce operation and maintenance costs, as well as improving access to clean water.
5. Air quality monitoring: AI can also be used to monitor air quality in water treatment plants. This can detect and prevent air pollution problems, which can have a negative impact on water quality.
In short, AI has huge potential to improve water management around the world. Data analytics can be used to optimize water management, prevent potential emergencies, and improve water supply efficiency. As we face challenges such as population growth, climate change and water scarcity as a result, artificial intelligence is proving to be an increasingly valuable tool to ensure an efficient and safe water supply is accessible to all.
