IoT System Selection as a Fuzzy Multi-Criteria Problem

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.

Automated summary

This research aims to analyze the applications of IoT in agriculture and compare the widely used IoT platforms. The study develops a multi-criteria framework for selecting an IoT solution in a fuzzy environment. The proposed framework introduces a modified MABAC method with a specific distance measure using intuitionistic fuzzy values. The effectiveness of the new decision-making framework is verified through an illustrative example of ranking IoT platforms.