The exponential growth of data plays a critical role for AI’s success. In today’s world, data is being generated at an unprecedented rate — a trend that is going to continue across the globe.
Another significant driver of the recent rise in AI is the growing availability of cloud computing. Cloud-based platforms allow a flexible and cost-effective way to access the computational power required to run large AI algorithms.
The current status of infrastructure in the U.S. has been the focus of discussions in recent years. The $1 trillion Bipartisan Infrastructure Law (previously known as the Infrastructure Investment and Jobs Act) puts special focus on water related infrastructure.
The need to invest in infrastructure is becoming increasingly pressing, particularly in the face of climate change. Extreme weather events including flooding and sea level rise are putting our infrastructure at risk, and without significant investment, many communities will be left vulnerable to the impacts of climate change. This includes not only the risk of damage to infrastructure during extreme weather events, but also the increased costs of maintaining and operating infrastructure in a changing climate.
AI and emerging technologies will play a key role in these efforts. Beyond just using typical pattern recognition or finding trends from historical data, AI has a lot to offer that will redefine the future of water infrastructure planning and management.
Here are five ways AI is going to change the future of water and infrastructure in the U.S. and around the globe:
1. Predictive Maintenance for Water Supply
AI can help predict equipment failures and maintenance needs, leading to improved uptime and reduced downtime. A number of local municipalities and agencies across the U.S. have implemented AI systems that detect potential equipment failures in real time, allowing maintenance teams to address issues before they cause a problem.
2. Future Flood Risk Prediction
Mother Nature can be extremely complex when it comes to flooding. The classical practice of future flood risk determination was based upon “past performance” or historical data.
AI has added new dimension to future flood risk detection for complex predictive modeling. Numerous pilot studies are being conducted nationwide where the AI can “learn” using previously completed modeling instead of just historical data and “predict” the flood risk for more complex areas with multiple risk factors. This allows the authority in charge to take preemptive measures to protect its infrastructure and citizens by helping mitigate flooding impact.
3. Water Quality
AI can analyze future water quality patterns using similar results and data from sensors to identify changes in water quality, which can be indicative of contamination or other issues. This enables the local agency to have preplanned action plans ready to respond to issues such as harmful algae blooms or other contaminants.
4. Sustainability and Energy Optimization
AI can optimize energy usage in water treatment and distribution, reducing costs and carbon emissions.
Water treatment and distribution require significant amounts of energy, making them an ideal candidate for optimization through the use of AI. AI can be utilized for predicting future demand in treatment and distribution network by analyzing historical water usage patterns. AI can also be used to optimize the distribution network itself.
By analyzing flow rates, pressure, and other data, AI can identify areas of the network that are over- or underutilized. This can serve as a decision support system to adjust the network and ensure that water is distributed efficiently, reducing energy consumption and carbon emissions.
5. Asset and Water Resource Management
AI can help manage and prioritize infrastructure assets, ensuring their proper maintenance and replacement. It can also help conserve water by optimizing irrigation and reducing wastage.