Ilieva Galina, Yankova Tania
Department of Management and Quantitative Methods in Economics, University of Plovdiv Paisii Hilendarski, 4000 Plovdiv, Bulgaria.
Sensors (Basel). 2022 May 28;22(11):4110. doi: 10.3390/s22114110.
This research aims to analyse the applications of IoT in agriculture and to compare the most widely used IoT platforms. The problem of determining the most appropriate IoT system depends on many factors, often expressed by incomplete and uncertain estimates. In order to find a feasible decision, this study develops a multi-criteria framework for IoT solution selection in a fuzzy environment. In the proposed framework, a new modification of the Multi-Attribute Border approximation Area Comparison (MABAC) method with a specific distance measure via intuitionistic fuzzy values has been presented as a decision analysis method. The new technique is more precise than existing crisp and fuzzy analogues, as it includes the three components of intuitionistic numbers (degree of membership, degree of non-membership and hesitancy degree) and the relationships between them. The effectiveness of the new decision-making framework has been verified through an illustrative example of ranking IoT platforms.
本研究旨在分析物联网在农业中的应用，并比较使用最广泛的物联网平台。确定最合适的物联网系统这一问题取决于许多因素，这些因素往往通过不完整和不确定的估计来表达。为了找到一个可行的决策，本研究开发了一个在模糊环境中选择物联网解决方案的多标准框架。在所提出的框架中，提出了一种通过直觉模糊值采用特定距离度量的多属性边界近似区域比较（MABAC）方法的新改进，作为一种决策分析方法。新技术比现有的清晰和模糊类似方法更精确，因为它包括直觉数的三个组成部分（隶属度、非隶属度和犹豫度）以及它们之间的关系。通过一个对物联网平台进行排名的示例验证了新决策框架的有效性。
