Imagine for a moment that you don’t know if your water is safe to drink. It may be, it may not be — just trying to visualize that situation brings a great deal of discomfort, doesn’t it? That’s the situation 2.2 billion people find themselves in on a regular basis.
Chlorine can help with that. Chlorine kills pathogens in drinking water and can make water safe to drink at an optimum level. But it’s not always easy to estimate the optimum amount of chlorine. For instance, if you put chlorine into a piped water distribution system, that’s one thing. But if you chlorinate water in a tank, and then people come and take that water home in containers, it’s a different thing because this water is more prone to recontamination — so you need more chlorine in this type of water. But how much? The problem gets even more complicated because if water stays in place too long, chlorine can also decay.
This is particularly a problem in refugee camps, many of which suffer from a severe water crisis.
“Ensuring sufficient free residual chlorine (FRC) up to the time and place water is consumed in refugee settlements is essential for preventing the spread of waterborne illnesses.” write the authors of the new study. “Water system operators need accurate forecasts of FRC during the household storage period. However, factors that drive FRC decay after the water leaves the piped distribution system vary substantially, introducing significant uncertainty when modeling point-of-consumption FRC.”
To estimate the right amount of FRC, a team of researchers from York University’s Lassonde School of Engineering used a machine learning algorithm to estimate chlorine decay.
They focused on refugee camps, which often face problems regarding drinking water, and collected 2,130 water samples from Bangladesh from June to December 2019, noting the level of chlorine and how it decayed. Then, the algorithm was used to develop probabilistic forecasting of how safe the water is to drink.
AI is particularly good at this type of problem: when it has to derive statistical likelihoods of events from a known data set. In fact, the team combined AI with methods routinely used for weather forecasting. So, you input parameters such as the local temperature, water quality, and the condition of the pipes, and then it can make a forecast of how safe the water is to drink at a certain moment. The model estimates how likely it is for the chlorine to be at a certain level and outputs a range of probabilities, which researchers say is better because it allows water operators to plan better.
“These techniques can enable humanitarian responders to ensure sufficient FRC more reliably at the point-of-consumption, thereby preventing the spread of waterborne illnesses.”
It’s not the first time AI has been used to try and help the world’s less fortunate. In fact, many in the field believe that’s where AI can make the most difference. Raj Reddy, one of the pioneers of AI recently spoke at the Heidelberg Laureate Forum, explaining that he’s most interested in AI being used for the world’s least fortunate people, noting that this type of technology can “move the plateau” and improve the lives of the people that need it most.
According to a World Bank analysis, machine learning can be useful in helping developing countries rebuild after the pandemic, noting that software solutions such as AI can help countries overcome more quickly and efficiently existing infrastructure gaps. However, other studies suggest that without policy intervention, AI risks exacerbating economic inequality instead of bridging it.
No doubt, the technology has the ability to solve real problems where it’s needed most. But more research such as this is needed to find how AI can address specific challenges.
The study has been published in PLoS Water.
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