Selection of artificial intelligence tool for blind assistance based on Dombi aggregation operators for intuitionistic linguistic decision-making problems

Zeeshan Ali (), Tapan Senapati () and Sarbast Moslem ()
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Zeeshan Ali: National Yunlin University of Science and Technology
Tapan Senapati: Southwest University
Sarbast Moslem: University College of Dublin

International Journal of System Assurance Engineering and Management, 2025, vol. 16, issue 5, No 11, 1844-1864

Abstract: Abstract The selection of an artificial intelligence tool or technique for blind assistance contains numerous factors that analyze the validity and capability of the solution in giving safety, autonomy, and accessibility to visually compromised people. The model or technique of AI tools planned for this perseverance typically goal to assist with object recognition, reading, navigation, and real-time interaction with the situation. The fundamental goal of this theory is to develop the Dombi operational laws for intuitionistic linguistic numbers. In addition, we analyze the informative form of intuitionistic linguistic Dombi weighted averaging operator, intuitionistic linguistic Dombi ordered weighted averaging operator, intuitionistic linguistic Dombi weighted geometric operator, and intuitionistic linguistic Dombi ordered weighted geometric operator with numerous vital properties. To help the visually impaired and blind people be independent, this manuscript determines a moveable electronic assistive device based on artificial intelligence. For this, we analyze the decision-making problems for introduced operators to evaluate the significant or central device for assessing blind people independently. Lastly, we explain numerous illustrations to compare suggested operators and prevailing procedures to perform the expertise and rationality of the introduced information.

Keywords: Intuitionistic linguistic sets; Dombi aggregation operators; Blind assistance; Artificial intelligence; Decision-making problems (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13198-024-02683-3

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