Work

A hybrid approach for smart city air quality monitoring using q-rung orthopair fuzzy fairly aggregation with Z-numbers

Year: 2025

Type: article

Abstract: This study presents a novel approach for enhancing air quality monitoring (AQM) in smart cities by employing q-rung orthopair fuzzy Z-numbers (q-ROFZNs) within a robust multi-criteria decision-making framework. The proposed methodology addresses the challenges of uncertainty and imprecision in environmental data through the integration of q-ROFFZN aggregation operators. In particular, we develop and apply the aggregated operation weighted averaging and ordered weighted averaging operators under the proposed set, enabling more flexible and accurate data fusion . By leveraging Grey Relational Analysis (GRA), the model demonstrates superior assessment accuracy and resilience compared to existing techniques. The hybrid computational strategy effectively supports dynamic decision-making by incorporating real-time traffic and industrial data, leading to optimized environmental control and public health protection. The findings highlight the potential of advanced fuzzy set theories in developing sustainable and intelligent solutions for urban air pollution management.

Source: Ain Shams Engineering Journal

DOI: 10.1016/j.asej.2025.103492

Authors: Muhammad Shazib Hameed, Shahbaz Ali, Qin Xin, Mansour Shrahili

Institutions: Khwaja Fareed University of Engineering and Information Technology, Islamia University of Bahawalpur, University of the Faroe Islands, King Saud University

Language: English

Topic: Multi-Criteria Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Clean water and sanitation, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,200