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- W4387237486 abstract "Pollution is our greatest threat. It affects the weather and threatens living beings’ lives. People breathe in particulate matter (PM), which is waste with very minute dimensions. This causes lung, blood vessel, neurological system, and cancer diseases. Only awareness can solve this problem. This is the only method to solve it, together with a comprehensive medical approach. Modern technology can solve all environmental problems. This research produces models for assessing and locating harmful gases in the environment and determining tolerable levels. First, we constructed a toxic gas detector. This lets you compare harmful substances that can harm sensitive persons anywhere and disrupt daily life. In this strategy, we used a machine learning-trained model and the K-nearest neighbor (KNN) set of rules to forecast levels and then explain them in three stages: low, medium, and high. Our results suggest that our methodology is the best technique to measure air pollution and improve urban prevention efforts." @default.
- W4387237486 created "2023-10-02" @default.
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- W4387237486 date "2023-01-01" @default.
- W4387237486 modified "2023-10-18" @default.
- W4387237486 title "Prediction of Toxic Gases Tolerance Level and Analysis of Impact on Human Respiratory System Using Machine Learning" @default.
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- W4387237486 doi "https://doi.org/10.1007/978-981-99-2746-3_17" @default.
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