Machine Learning Based Predictive Model for Closed Loop Air Filtering System
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Abstract
An automaton is showcased here to assess the high-quality of air with two elements: the quantity of dirt debris present inside the air and the temperature of the room. These two pieces of information are taken and a simple pinnacle-down mathematical version with a conditional clause is employed for assessing the satisfaction of air in a room. The mathematical model will consist of an easy equation. Destiny studies may be accomplished by optimising the mathematical model to enhance the accuracy of assessing the air quality.
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