Approximately 263 watersheds and 300 aquifers are shared between two or more countries worldwide. To make matters worse, during the rainy season, flooding pollutes water – thus, water flowing from one state to another is full of contaminants posing health problems globally. Due to the lack of clean H2O, people fall sick from water-related diseases, such as typhoid, jaundice, mumps, and malaria.
These health problems have prompted researchers to develop a range of Artificial Intelligence tools geared towards improving water management worldwide. AI has proved to be useful for collecting accurate data on flooding, contaminants, precipitation, and groundwater management. It gets better because developing countries such as India and South Africa have been able to find solutions to health problems brought about by contaminated H2O and switching from a traditional method to AI.
Our bodies require essential minerals such as sodium, magnesium, and potassium to function. Drinking H2O contains some of these minerals, and lack of it can result in an imbalance in the body, leading to health problems. Suppose there is a shortage of clean drinking water; consumption of the best electrolyte supplement for keto will help replenish our bodies with the electrolytes and minerals that we’ve lost.
Let’s explore how to prevent health problems caused by water shortage or pollutants and how water managers are using AI-Powered tools.
Maintain Quality of Water
Water managers use AI to test and detect dangerous H2O contaminants such as lead, nitrates, copper, chlorine, and arsenic. The AI machine is equipped with chemical testing equipment that can pinpoint the exact regions that are contaminated.
The machine also provides information on the type of pollutants and the type of treatment to be used. Water managers then use this information to treat H2O in the regions, preventing disease outbreaks, thus, saving thousands of lives.
Monitoring Consumption Patterns and Demand
AI tools are used to detect flow, pressure, volume, and usage. This information is then fed into a machine-learning algorithm to identify possible leaks and cracks in the pipes. The algorithms then provide water managers with information about the amount of H2O lost and the type of loss.
This can be in the form of unauthorized water consumption, equipment failure, or leaks. AI helps save time and money, as teams are deployed faster for pipe replacement.
Increased H2O consumption is evident in urban and industrial areas of densely populated cities. And information obtained from AI monitoring can be used to manage water supply in these regions by improving the water scheduling, faster detection of contaminants, and repair of water leaks.
Understanding Climatic Changes
Through AI, researchers can correctly predict climatic changes. Therefore, people will be better prepared if there is a forecast for flooding, intense storms, or drought. Measures are also put in place to ensure that the public is catered for in any health problems caused by natural disasters.
Identifying Tree Loss Effect on Health
Excessive falling of trees affects forest health, which is the primary source of H2O. Trees absorb poisonous gases such as CO2 from the atmosphere and release oxygen. Our forests are also responsible for controlling rainfall, flooding, water purification, and cooling the environment since they absorb the sunlight.
Excessive tree loss leads to health problems from high humidity, such as headaches, muscle cramps, heatstroke, dizziness, or fatigue. Water managers use AI to obtain data useful in identifying forest health and its significance to water management and public health.
To Sum it Up
Digital technology has taken the world by storm, and water utilities are not left behind. Using Artificial Intelligence, managers are transforming water management and supply. Health problems that arise due to H2O shortage or pollutants are mitigated through AI.
It provides accurate data about possible leaks, contaminants, changes in demand and supply, climatic changes, and the effect of tree loss on water resources. Therefore, giving way to lean operation.
Do you have any questions? Please leave them in the comment section.
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