Predictive Maintenance: AI's Role In Securing Water Infrastructure
By Katie Brenneman
The reliability of water infrastructure shouldn’t be a guessing game. Public water supply in the U.S. covers millions of miles, providing billions of gallons of water every day. That leaves a lot of room for error. However, public health depends on the proper management of this vast water infrastructure.
Artificial intelligence (AI) can help. AI in the water sector has recently converged in some unexpected ways, including AI’s ability to predict maintenance and mitigation needs.
How The Democratization Of AI Is Transforming Water Infrastructure Management
When AI first burst onto the scene, the most sophisticated platforms were confined to use at high-level, well-funded institutions. However, the democratization of AI has more recently allowed municipalities of all sizes to harness machine learning algorithms to predict water demand, detect leaks, and optimize distribution networks.1 AI-driven solutions enable more efficient resource allocation, reduced water wastage, and improved overall infrastructure resilience.
Deregulating AI empowers local authorities to make data-informed decisions, enhancing their ability to address water challenges effectively and sustainably. As a result, the widespread adoption of AI in water infrastructure management contributes to the development of smarter, more resilient, and environmentally conscious communities.
AI Innovations In Water Infrastructure
Traditionally, maintaining water utility operations is often accompanied by complications like being unable to visualize the infrastructure. Utility operations are mostly underground and inaccessible, making it difficult to detect issues like leaks and breaks — manual meter reads can only do so much. If there is a discrepancy between the amount billed and the amount of water used, there is likely an issue going on in the piping. Instead of manually calculating that difference, data-driven analysis can identify the larger issue at hand and even predict future issues for better regulation.
Specifically, industrial companies have harnessed this data analysis through Industry 4.0 to predict and mitigate errors in manufacturing, production, and distribution.2 In the water industry, this helps optimize resource allocation, predict maintenance needs, and boost overall operational efficiency. The synergy of Industry 4.0 technologies in the water infrastructure maintenance sector not only enhances this efficiency but also contributes to the longevity and sustainability of water systems by preventing failures and reducing downtime.
IoT
Through the implementation of advanced sensors, Internet of Things (IoT) devices, and real-time data analytics, Industry 4.0 enables proactive strategies. Water utilities are now able to monitor the condition of critical infrastructure components in real-time, detecting potential issues before they escalate. Smart sensors embedded in pipelines and treatment facilities provide continuous data streams, facilitating the identification of anomalies and optimizing maintenance schedules. Furthermore, automation and AI streamline decision-making processes, allowing for quicker responses to emerging challenges.
Automation
Through the deployment of automated technologies, tasks such as water quality monitoring, treatment processes, and distribution network management can be executed with greater precision and efficiency. Automated sensors continuously collect and analyze data, providing real-time insights into the condition of infrastructure components.
This proactive approach allows for the swift detection of leaks, contamination, or irregularities, enabling rapid response and minimizing potential risks. Additionally, automated control systems optimize the operation of pumps, valves, and other equipment, enhancing energy efficiency and reducing operational costs. The integration of automation in the water infrastructure industry not only improves the reliability and performance of systems but also contributes to resource conservation and environmental sustainability.
Lasting Impacts Of AI On Water Infrastructure Security In The Face Of Climate Change
AI can touch almost every aspect of maintaining the integrity of water infrastructure. With the increasingly intense impacts of climate change on resource needs and issues, AI has a powerful job to do. The increased risk of flooding, extreme weather, and rising sea levels cause the infrastructure to be more vulnerable to damage. Luckily, AI can not only use historical data models to predict future maintenance needs in water infrastructure, but it can also incorporate weather pattern predictions into this analysis. This allows for preparation that is privy to the dangers that climate change is inevitably going to bring about for the water supply.
This also extends to the prediction of contamination. For example, algal blooms in dead zones, or places with water bodies where aquatic life is not able to thrive due to low levels of oxygen, can be harmful to the water supply.3 Toxic chemicals are released by the larger algal blooms, seeping into the bodies of water. Lakes, streams, rivers, reservoirs, and coastal waters can be impacted. AI can predict more closely when these algal blooms will occur and the amount of impact they will have on public and aquatic health. This allows mitigation through applications of clay and other means to rid these dead zones of harmful algae, preventing further complications down the line.
Moving Forward
The integration of AI in water infrastructure management marks a transformative leap toward a more secure and resilient future. Deregulating AI has empowered municipalities of all sizes to leverage machine learning algorithms, enhancing their ability to predict water demand, detect leaks, and optimize distribution networks. This shift toward data-informed decision-making not only ensures efficient resource allocation but also contributes to the development of environmentally conscious and sustainable communities.
The IoT and automation address the traditionally challenging aspects of maintaining water utility operations. Real-time data analytics and advanced sensors enable proactive monitoring of critical infrastructure components, allowing for the swift detection of anomalies and optimization of maintenance schedules. Automation, on the other hand, enhances the precision and efficiency of tasks such as water quality monitoring, treatment processes, and distribution network management, ultimately improving the reliability and performance of systems while promoting resource conservation and environmental sustainability.
As the impacts of climate change intensify, posing increased risks to water infrastructure, AI emerges as a powerful ally in securing the integrity of these vital systems. Moreover, AI's capacity to forecast algal blooms in dead zones enables proactive measures to mitigate the impact on public and aquatic health, showcasing its potential to address emerging challenges and contribute to the long-term sustainability of water systems.
Using AI for water infrastructure management not only enhances operational efficiency but also fortifies this oft-unpredictable sector against the uncertainties of a changing climate. The lasting impacts of AI extend beyond immediate problem-solving, fostering a future where water resources are managed with foresight, resilience, and a commitment to environmental and societal well-being.
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