A heterogeneous fuzzy collaborative intelligence approach: Air quality monitor selection study

Abstract

Smart backpacks with novel functions have an enormous potential market. Therefore, the ability to embed smart functions (e.g., air quality detection) into a backpack design is critical. This study aimed to select an air quality monitor suitable for the design of a smart backpack. Accordingly, a heterogeneous fuzzy collaborative intelligence approach is proposed. In the proposed methodology, experts apply heterogeneous methods to derive the fuzzy priorities of the criteria and evaluate the suitability of an air quality monitor. The evaluation results by all experts are aggregated using fuzzy-weighted intersection (FWI). After defuzzification, the top-performing air quality monitor is chosen. Based on the experimental results, the most critical features of an air quality monitor are price and size. Furthermore, not all air quality monitors are suitable for a smart backpack design. Among the compared air quality monitors, OO-KFR-PMA was the optimal choice. The contribution of this research is twofold. First, experts are enabled to apply heterogeneous fuzzy multi-criteria decision-making methods. Second, the unequal authority levels of experts are considered by aggregating their evaluation results using FWI.