Written by: Mya Bonney, Project Assistant, Syracuse University Environmental Finance Center

Image Credit: Tara Winstead via Pexels

When you think of Artificial Intelligence (AI), what comes to mind? Robots? Human-like machines designed to cause widespread destruction and chaos?

As the popularity of AI has surged in recent years, people are not only becoming more comfortable with the use of AI, but are also actively seeking out ways to use it to their advantage. As AI technologies continue to revolutionize various industries, the global artificial intelligence market has an expected annual growth rate of 37.3% between 2023 and 2030, as reported by Grand View Research.

AI extends beyond the traditional scope of pattern identification and data analytics. It presents a range of opportunities that have the potential to revolutionize the water industry as we know it.


What Is Artificial Intelligence (AI)?

Artificial Intelligence, or AI, is the field of computer science dedicated to creating systems capable of performing tasks that would normally require human intelligence. It involves creating algorithms that enable systems to analyze and interpret vast amounts of data. These algorithms then allow computer systems to imitate aspects of human thought, enabling machines to replicate tasks such as learning, planning, problem-solving, and decision-making.

With the changing climate and strained resources, whether that be financial or labor shortages, the water industry is facing significant challenges. Extreme weather events are making water increasingly scarce, unpredictable, and polluted, leading to more stress on our water infrastructure, treatment processes, and those who manage it all.

AI technology has the potential to revolutionize the future of water and wastewater systems and ensure the long-term viability of the industry. Here are six ways in which AI can solve problems across the water sector:

1. Water quality monitoring

AI can be used to continuously monitor the quality of water in real time. By analyzing data from sensors placed in water bodies, AI algorithms can detect changes in water quality and identify potential contaminants or public health hazards such as pollution plumes and waterborne disease pathogens. Through this, AI can also detect eutrophication, harmful algal blooms, and the dumping or discharging of hazardous chemicals.

2. Leak detection and prevention

AI can help in identifying and preventing leaks in water distribution systems. By analyzing data from sensors and meters, AI algorithms can detect anomalies in water flow and pressure, indicating possible leaks. This proactive approach can potentially save significant amounts of water and reduce the costs associated with repairing leaks.


3. Infrastructure maintenance

AI can use real-time data from network sensors to measure, monitor, and optimize flow pressure and velocity to be more energy efficient and reduce operating costs. Advanced systems may even assist in preventing detrimental sewage overflows during severe weather conditions by adjusting storage usage in wastewater pump stations, pipes, and manholes. Additionally, predictive analytics can be used to detect anomalies and predict, diagnose, and fix wastewater network defects and blockages. AI can even expedite notifications to cleanup teams in the event of unexpected discharges.

4. Flood prediction and management

AI can be used to analyze data from weather forecasts, river levels, and historical flood patterns to predict and manage flood events. By using machine learning algorithms, AI can provide accurate and timely flood warnings, allowing authorities to take necessary measures to mitigate the impact of floods and protect their communities.

5. Water conservation

AI can help optimize water usage by analyzing data from various sources, such as weather patterns, soil moisture levels, and crop water requirements. By utilizing this data, AI algorithms can provide valuable insights on when and how much water should be used for irrigation, reducing water waste and promoting sustainable agriculture practices.

6. Water resource management

AI can assist in managing water resources more efficiently. By analyzing data on water availability, usage patterns, and population growth, AI algorithms can help authorities make informed decisions on water allocation and infrastructure planning, especially when navigating water scarcity.


AI In Action

In 2020, the city of Tucson, Arizona implemented AI technology in an effort to be more proactive in managing its water system, consisting of over 4,600 miles of distribution water main pipes.

The city used machine learning technology from VODA.ai, which discovers patterns from historical pipe failures, and evaluates data on soil, weather, land use, and more, to develop targeted and precise pipe break predictions. The AI technology then calculates the Likelihood of Failure (LoF) and Consequence of Failure (CoF) scores for each pipe segment. From these two scores, the technology generates a quarterly Business Risk Exposure score, allowing utilities to focus their resources on the most important assets. “There is limited data we currently have to make expensive decisions around maintaining our pipe network. With VODA.ai’s daVinci machine learning technology, we will be able to make smart decisions, save valuable resources, and protect our water infrastructure,” said Tim Thomure, previous Director of the Tuscon Water Department. The current Director of the Tuscon Water Department, John P. Kmiec, believes that coupling human experience with AI technology will help the city make better-informed decisions with greater confidence.

AI is a rapidly evolving field with the potential to transform industries and our daily lives. While there are challenges and ethical concerns to address, the advancements in AI technology continue to push the boundaries of what machines are capable of achieving. By harnessing the power of AI, we can address the challenges faced by water and wastewater systems, potentially leading us down a path of a more sustainable and resilient water sector.