Scientists have developed an easy way to measure water alkalinity using only smartphone technology and artificial intelligence, and the breakthrough could have important implications for water management practices.
Researchers from Case Western Reserve University and Cornell University set out to create a method to test water quality that doesn't require any special equipment, as the team explained in a summary posted by Tech Xplore. The technique enables rapid and precise measurements of water alkalinity levels in fresh and saltwater, which will help agencies save money on water testing.
Alkalinity is crucial for maintaining a stable pH and preventing harmful changes in water quality. High alkalinity neutralizes acids, protects water bodies from the effects of pollution, and is essential for the health of marine animals. In addition, understanding alkalinity is important for water treatment and other industrial processes.
Current methods to measure alkalinity are expensive and require certain equipment, making them impractical for widespread use — especially in areas with limited resources. That prompted the team to look for a simpler solution that would allow both remote and urban communities to access water quality monitoring.
The team explained the breakthrough equipment-free method for alkalinity analysis in the journal Eco-Environment & Health, introducing an approach that combines cost-effective commercial reagents and smartphone technology with machine learning models.
The reagents generate color changes in response to alkalinity levels in various bodies of water. Smartphone cameras capture the changes, and machine learning models process them to correlate color intensity with alkalinity levels.
Dr. Huichun Zhang, the study's senior author, explained how the technology will revolutionize water quality testing: "This AI-powered approach marks a significant milestone in water quality monitoring. It challenges the trend of ever-more complex and costly analysis techniques, offering a foundation for similar advancements in other water quality parameters."
Because the technology will reduce the costs of water quality monitoring, it will help remote, vulnerable communities access it and have cleaner, safer drinking water. If the technique is adopted on a large scale, it could improve water management in industrial and agricultural processes and reduce pollution in waterways, which will benefit animals and ecosystems.
While the technology will undoubtedly have a major positive impact on numerous communities and businesses, the environmental toll of AI can't be ignored. MIT News reported that training and deploying AI models uses an astonishing amount of electricity and water, which increases pollution and strains the electric grid.
But with the world rapidly transitioning to cleaner energy sources such as solar and wind power, that should lessen the impacts of AI. Plus, artificial intelligence is being used in helpful ways, such as to monitor extreme weather and reduce harmful chemicals in fertilizers.
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