How AI Improves Energy Efficiency in Water Management

Artificial intelligence has many potential use cases, but some forward-thinking decision-makers have focused on applying it to address areas that need improvement. Increasing energy efficiency in water-management applications is a good example of a goal that affects parties in agriculture, technology, wastewater and other essential industries.

1. Improving Resource Management in Corporate Environments

Buildings associated with some of the world’s most well-known brands can use significant amounts of water, energy and other resources because of their scale and the fact that they may have 24/7 operations to meet customer needs. However, that resource dependence becomes problematic if businesses begin using more than usual and no one notices the change. Fortunately, AI can detect those instances and flag the appropriate parties to investigate further. 
At one of Amazon’s Scottish logistics facilities, an AI-powered utility efficiency tool, FlowMS, analyzed water-meter data and found above-average usage. It notified engineers about the problem, and they determined that the issue was likely due to an underground piping abnormality. The investigation ultimately found that the local water supplier had a buried pipeline with a faulty valve. Fixing it stopped 9 million gallons worth of annual water waste. However, since the leak was too small for humans to see, AI was necessary to resolve the problem. 
In another case, FlowMS indicated that a New York fulfillment center apparently used five times as much energy as other nearby Amazon facilities. Rather than a massive process issue causing excessive energy use, those examining the details found the problem was an energy meter miscalibration. 
Many sustainability-minded consumers expect popular brands to be at the forefront of planet-conscious changes, especially since these entities often have outsized influence. This example shows why AI can enable businesses to make meaningful, measurable changes.

2. Revealing Better Stormwater Solutions

Stormwater originates from precipitation and has remained a central water-management issue, especially with many areas receiving above-average amounts of rain. One of the main issues is that it moves away from where it falls, picking up fertilizer, oil, bacteria and other pollutants as it travels. Those contaminants can end up in local waterways and disrupt ecosystems.
Authorities must also manage stormwater to prevent flooding, especially in urban areas. This occurs because hard surfaces such as conventional pavement cannot absorb rainwater. Some city planners have dealt with that shortcoming by installing permeable versions. Inadequately addressing the problem can decrease energy efficiency by increasing dependence on pumping stations and equipment. Some decision-makers have invested in green infrastructure to minimize sewage overflow events that require significant energy to resolve. 
However, these challenges may need a multifaceted approach that uses advanced technologies, including AI. Many leaders realize that the best approach is to prevent overflows rather than deal with them after the fact. 
A Chinese province recently deployed robots equipped with advanced AI as part of an initiative to combine digital water conservation platforms with artificial intelligence. In addition to preventing floods, these robots supplement emergency response plans, making urgent events less resource-intensive. They analyze real-time rainfall, current water levels and other parameters that could indicate impending stormwater problems. 
This approach has also allowed parties to make basin-scheduling plans in only 30 seconds, although the activity formerly took half an hour. 
Since the system is user-friendly enough for nonspecialists, it is an enticing possibility for leaders who want to adopt AI technology for better water management and energy efficiency without requiring employees to navigate large learning curves.

3. Enabling Responsible Technological Growth

Many concerned parties have rightfully pointed out that artificial intelligence uses enormous amounts of water and energy. That doesn’t mean they should avoid using it, but this emphasizes the need for people to continually seek solutions that enable AI progress without sacrificing environmental goals. A good starting point is for people to prioritize artificial intelligence applications that allow them to live more sustainably. 
For example, households can reduce residential CO2 emissions by as much as 40% when using AI energy-management systems. These products adjust temperatures and appliance usage based on real-time usage patterns. Some even allow people to activate the heater or air conditioner for an hour before they get home from work so their houses feel comfortable when they arrive. Similarly, some connected sensors can detect unusual liquid, warning occupants of leaks. These solutions improve water management and prevent costly property damage. 
However, it is also important for these enhancements to happen on a larger scale, including in data centers that allow companies to run AI and expand use cases. A compelling example comes from Digital Realty, which owns and operates data centers globally. It partnered with Ecolab, a water, hygiene and infection prevention solution provider. The companies will collaborate on an AI water system that should reduce negative environmental impacts and improve the energy efficiency of the facilities’ cooling systems. 
This pilot, which concerns 35 data centers in the United States, relies on machine learning algorithms to create actionable water usage benchmarks and highlight climate-control inefficiencies that could require process enhancements. Those overseeing this initiative anticipate it will reduce water consumption by up to 15% while prolonging equipment life spans. It may also prevent operators from taking up to 126 million gallons of potable liquid from watersheds annually.

Creating a Brighter Future With AI-Enhanced Water Management

Many technological advancements can interfere with sustainability goals. Artificial intelligence is not an exception, but these real-life examples show the many exciting reasons to solve problems rather than exacerbate challenges. People frequently discuss water management as an increasingly pressing issue, especially since many live in areas where they cannot reliably access safe sources for drinking, bathing and cooking. 
Anyone interested in supporting AI use should prioritize service providers committed to minimizing excessive water usage and making other eco-friendly changes. Public interest in these enhancements will show leaders that ongoing investments are worthwhile.