One of the leading causes of infectious diseases in refugee settlements is waterborne illnesses. The good news is that a research team from York University has developed a new method that will keep drinking water safe through the use of machine learning, as reported by PhysOrg.
Artificial Neural Network (ANN)
Through machine learning, the team used ANN with Ensemble Forecasting Systems (EFS). EFS is a probabilistic model that is usually used to predict the probability of precipitation in weather forecasts.
ANN-EFS can generate forecasts at the time of consumption that takes various factors into consideration that affect the level of residual chlorine. The factors are local temperature, water storage, water handling, type and quality of the water pipes, and water quality. In fact, even if whether a child dipped their hand in the water container can also play a role in drinking water safety.
The researchers used routine water quality monitoring data from two refugee settlements in Tanzania and Bangladesh via the Safe Water Optimization Tool Project.
In Bangladesh, the data was gathered from 2,130 samples from Médecins Sans Frontières from Camp 1 of the Kutupalong-Balukhali Extension Site, Cox's Bazaar between June and December 2019.
The researchers used cost-sensitive learning, which morphs the cost function towards a specific, targeted behavior when using machine learning. They found that it improved probabilistic forecasts and reliability.
Through their Safe Water Optimization Tool, it takes machine learning work and make it available to support workers in the field. The difference is, the researchers ask water operators to sample water in the container at the tap, and in the same container, at the home after a few hours.
Not only can this help with safe drinking water, but it can also be used in other applications.
Also Read: Safe Drinking Water from Air Humidity? Solar Powered Prototype Attempts to Help Billions of People
How Machine Learning is Changing the Game in Water Safety and the Environment
Machine learning is changing the way water is viewed. With machine learning, you can get real-time information on water quality at the tap, and it can help with treatment systems. It is also helping governments with monitoring and surveillance, as well as in emergency response situations.
Over the last few years, there's been a lot of research that looks at how machine learning is changing the game in water safety and the environment. In particular, it's helping policy-makers and scientists to monitor the quality of water, as well as its impact on the environment.
There's also been a lot of research that is looking at how machine learning can help in water monitoring and surveillance, as well as in emergency response situations.
Related Article: How Technology Can Deal With Contaminated Drinking Water
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Written by: April Fowell
