The Water Industry Can Use AI to Better Predict Emergency Events
Emily Newton is a manufacturing journalist who regularly covers the industry trends. She is also the Editor-in-Chief of Revolutionized. Subscribe to read more from Emily.
Heavy rainstorms flooded the northeast in early July. New York City subways flooded with runoff, and some passengers waded in chest-high water. While some New Yorkers bravely faced the flooding, others experienced injuries and adverse health effects.
Now, environmental engineers and scientists search for sustainable solutions to future emergency events. With adequate technological advancements, society can predict water-driven challenges, helping officials take action. Artificial intelligence (AI) may conduct the predictions and offer protective suggestions.
Challenges in the Industry
The water industry can face significant challenges during an emergency. Inadequate maintenance practices at a treatment facility can also cause severe degradation, impacting public health. Various inefficiencies may alter the safety of regional water systems.
Without timely detection, aging pipes can burst and limit the flow out of a system. When sewage lines break, it can increase the quantity of toxic runoff polluting local water sources. A block in clean water output can also cause an adverse effect, decreasing the potable water supply.
Over time, water pumps decrease in efficiency or develop issues. As they degrade, they experience a reduced ability to remove water from dangerous areas. With an efficient pump system, the subways could remove stormwater before it causes local safety challenges.
A recent challenge in the water management industry derives from climate change. As global temperatures rise, the evaporation rate increases. Professionals have trouble maintaining optimal clean water output with global heat rising.
High temperatures also increase the development of bacteria in water supplies. Sustained warm temperatures promote the development of new toxins that modern sensing systems may fail to detect. Fortunately, companies are adopting water AI devices, expanding the efficiency of water filtration and management practices.
An Example of a Clean Water AI System
The Winneke treatment plant in Melbourne, Australia, recently adopted an AI system to manage the pump system. It filters 350 ML of liquid daily, impacting residents across the region. The new program maximizes the pump’s efficiency while maintaining optimal output rates.
It relies on the Python system, accessing historical readings and predicting adequate maintenance measures. Rather than signaling a worker for pump alterations, the program conducts them itself. It also decreases the plant’s energy costs by 20% annually.
Other plants can adopt the system and prevent pump failure and other impactful events. When used in collaboration with other emergency prediction technologies, the pump can improve the safety of water and surrounding areas.
Machine Learning for Water Quality
The United Kingdom also adopted an AI system for its wastewater treatment plants. The system recognized 926 separate sewage spills that were polluting local rivers. During the summer, as swimming rates increase, individuals become sick from bacterial exposure.
The system uses an algorithm originally designed for face recognition. Rather than locating facial features, the AI locates flow disturbances causing runoff and spills. The devices can predict and prevent emergency events like the Flint water crisis.
In 2014, government officials changed Flint, Michigan’s water source from the Detroit supply to a local river. Soon after the switch, residents became ill, developing Legionnaire’s disease and other adverse health effects. It took two years for professionals to trace back the conditions to the water supply.
General Motors had a successful manufacturing facility in the area for years, but illegally dumped toxins into the water source. Even after the company left town, lead levels remained high. Without adequate purification and quality identification technology, the community accumulated lead poisoning cases.
Fortunately, we can prevent current water crises using water AI devices and localized water treatment systems. Industrial plants can maintain healthy water quality around manufacturing sites by using reverse osmosis for byproduct and mineral removal. The low-level filtration can send their output to cooling towers for bacterial reduction and growth prevention.
When combined, AI and filtration systems can protect residents against adverse health effects. Combining multiple machine learning systems creates a smart water treatment plant, further improving the efficiency of water quality maintenance.
Smart Water Treatment
Some water treatment companies also utilize smart technology to predict and prevent emergencies. South Bend, Indiana’s wastewater management facility uses smart water sensors to prevent overflows. In the past, the city experienced runoff issues like pollution of the St. Joseph River with sewage.
The system uses AI, autonomously gathering data on water levels and distribution. Smart sensors send the findings to professionals, signaling maintenance requirements for issue prevention. The devices can detect problems throughout the city and develop a central detection resource.
Another smart water device detects leaks throughout city pipe systems. After pinpointing the damaged part, the devices send messages to maintenance professionals. The two smart devices can work together to determine the source of a runoff problem.
Rather than spending time and resources searching for an issue, a smart water system can conduct detections with ease. It protects the local environment by limiting surface pollution and may decrease atmospheric degradation when powered with renewable energy. When powered with solar or wind energy, smart water devices can maintain optimal quality levels through disasters.
Many electricity-driven treatment facilities rely on fossil fuels and grid distribution. During disasters, power outages can decrease the efficiency and safety of water plants. Fortunately, renewable energy reduces a company’s reliance on the grid, increasing its access to power during emergencies.
Preparing for the Future
As greenhouse gas emissions remain high, we may expect the frequency of hurricanes, flooding, and wildfires to increase. The future climate may negatively impact our clean water access. A significant portion of the world already lacks pure drinking water, increasing the rate of dehydration.
We can prevent the rate from increasing by establishing AI systems now. When fueled with renewable energy, the systems can decrease the emissions associated with water management. Over time, the reduction in atmospheric pollution can reduce climate change and the frequency of disasters.