Categorisation for air quality assessment in car cabin

Abstract The objective of this work was to propose a way of preparing information about in-cabin air quality for the car driver or passenger. It was assumed that information should be objective, relevant, current, complete and useful. The major elements of our concept were: (1) monitoring of selected air parameters inside the cabin, (2) determination of indicators that characterise indoor air, based on measurements, and (3) the method of information extraction. We proposed to realise the first task with a sensor system. The second and third goals were reached by categorisation. The basis for defining categories were ranges of values of measured parameters or their combinations. In a way, the categories were used to quantify indicators of air quality. Shannon entropy and mutual information were applied to find the best categorisation. The concept was investigated using experimental data from car cabin air monitoring in various driving conditions. We conclude that information about air quality in car cabins may be successfully conveyed using the following indicators: thermal conditions – determined based on temperature and relative humidity measurements; air exchange – determined based on CO 2 concentration; and air freshness – determined based on volatile organic compounds (VOCs) content in car cabin air. Each indicator has three categories: bad, intermediate and good.

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