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IoT System Selection as a Fuzzy Multi-Criteria Problem.

Galina Ilieva1, Tania Yankova1

  • 1Department of Management and Quantitative Methods in Economics, University of Plovdiv Paisii Hilendarski, 4000 Plovdiv, Bulgaria.

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Summary
This summary is machine-generated.

This study introduces a new fuzzy decision-making framework to select the best Internet of Things (IoT) systems for agriculture, considering uncertain factors for optimal IoT platform selection.

Keywords:
Agriculture 4.0IoTMABAC methodMCDMdistance measureintuitionistic fuzzy sets

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Area of Science:

  • Agricultural Technology
  • Decision Science
  • Computer Science

Background:

  • The Internet of Things (IoT) offers significant potential for agricultural advancements.
  • Selecting the most suitable IoT system is challenging due to incomplete and uncertain data.
  • Existing decision-making methods may not adequately handle the complexities of IoT adoption in agriculture.

Purpose of the Study:

  • To analyze IoT applications in agriculture.
  • To compare prevalent IoT platforms.
  • To develop a robust framework for selecting appropriate IoT solutions in uncertain environments.

Main Methods:

  • Development of a multi-criteria decision-making framework for IoT solution selection.
  • Application of a modified Multi-Attribute Border approximation Area Comparison (MABAC) method.
  • Utilization of intuitionistic fuzzy values, incorporating membership, non-membership, and hesitancy degrees.

Main Results:

  • The proposed framework effectively handles incomplete and uncertain estimates in decision-making.
  • The modified MABAC method provides a more precise analysis compared to crisp and fuzzy methods.
  • An illustrative example demonstrated the framework's capability in ranking IoT platforms.

Conclusions:

  • The developed intuitionistic fuzzy MABAC framework offers a superior approach for IoT system selection in agriculture.
  • This method enhances decision accuracy by considering the nuances of fuzzy data.
  • The research provides a valuable tool for optimizing IoT adoption in the agricultural sector.