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Developing IoT Sustainable Real-time Monitoring Devices for Food Supply Chain Systems based on Climate Change using Circular Intuitionistic Fuzzy Set
Date
2024-02-21
Journal Title
Journal ISSN
Volume Title
Publisher
Natural Language Processing (NLP), Koçtaş,
video camera, FSA-Net
Abstract
Internet of Things (IoT) real-time monitoring devices,
which compromise sustainable sensing parameter-based climate
change, are developed to minimise food loss and waste to support
supply chain systems during natural disasters. Numerous studies
have shown that current IoT real time monitoring devices offer
remarkable prospects for future developments involving food
supply chain systems with sustainable sensing parameters.
Hence, modelling effective IoT real time monitoring devices to
minimise food loss and waste to support supply chain systems is
crucial during natural disasters. This modelling process can be
classified as multiple-attribute decision-making (MADM) given
three issues: the existence of multiple sensing parameter
attributes, the uncertainty related to the relative importance of
these attributes and the variability of data. The present study
endeavours to combine the fuzzy weighted with zero
inconsistency method and circular intuitionistic fuzzy sets (C
IFS-FWZIC) with a new additive ratio assessment (ARAS) to
determine ideal IoT real-time monitoring devices to minimise loss
and waste and support food supply chain systems during natural
disasters. The decision matrix for the study is built by
intersecting 54 IoT real-time monitoring devices with 10
sustainable sensing parameter attributes. The proposed method
is further developed to ascertain the importance level of the
sustainable sensing parameter attributes. These data are used in
ARAS. Sensitivity analysis and correlation coefficient test are
performed to assess the robustness of the proposed method.
Description
Keywords
Additive ratio assessment (ARAS)
,
climate change
,
food security
,
Internet of Things (IoT)
,
multiattribute decision-making (MADM)
Citation
Alsattar, H.A. et al. (2024) “Developing IoT Sustainable Real-Time Monitoring Devices for Food Supply Chain Systems Based on Climate Change Using Circular Intuitionistic Fuzzy Set,” IEEE Internet of Things Journal, 11(16), pp. 26680–26689.