Abstract
The interior decoration materials and the new furniture using formaldehyde, ammonia, and other poisonous substances are known as the main sources of indoor air pollutions. However, it is still a big challenge to estimate accurately the overall air quality by using the current measuring tools. Accordingly, the region-dot fusion (RDF) algorithm is proposed to evaluate the air quality in this paper. For the conversion from a region to a dot, the region-dot function is firstly defined as the summation of the belief function and the weighted width of the belief interval. In the RDF algorithm, the belief intervals of the two sensors with the basic probability functions are calculated based on the measurements of formaldehyde sensor and ammonia sensor. Then, the belief intervals are converted to the specific values. After the computation of collision degree and combination, the pollution level represented by a belief interval with the maximum probability is selected as the outcome of fusion decision. Compared with the weighted fusion algorithm and D-S evidence reasoning method, it is experimentally proved that the RDF algorithm can improve the separability of the belief intervals of the belief functions. Also, the evidence collision degree is decreased dramatically.
Highlights
Environment pollution is one of the most severe problems on the earth
Opposite to the algorithm from pixels to region [10] and making use of advantage of the multiple sensor fusion [11, 12], we developed the region-dot fusion (RDF) algorithm for the air quality estimation in this paper
The standard for indoor air pollution level can be defined in Table 1, where the pollution index I is used for classification of pollution level
Summary
Environment pollution is one of the most severe problems on the earth. Among them, indoor air pollution produced from decoration and new furniture is of concern but ignored. It is quite clear that the indoor air pollution exists within our living surrounding widely Aiming at these poisonous substances, the development of the effective air quality estimation method is a crucial research topic. Based on the recent publications, scientists [1] used the differential optical absorption spectroscopy, Fourier transform infrared spectroscopy, and ceilometer to interpret and estimate the air quality of the surrounding. The uncertainty problem has been studied, but the evidence collision problem was not worked out In another case, the adaptive-weighting fusion (AWF) method [9] could employ efficiently the original data without the experience knowledge, but it lacks adequate capability in the collision problem. It includes the basic probability function, belief function, D-S combination rule, and adaptive weighted fusion (AWF) algorithm.
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