Developing IoT Sustainable Real-Time Monitoring Devices for Food Supply Chain Systems Based on Climate Change Using Circular Intuitionistic Fuzzy Set
Internet of Things (IoT) real-time monitoring devices, which compromise sustainable sensing parameter-based climate change, are developed to minimize food loss and waste to support supply chain systems during natural disasters. Numerous studies have shown that current IoT real-time monitoring device...
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Institute of Electrical and Electronics Engineers Inc.
2025
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| author | Alsattar H.A. Mourad N. Zaidan A.A. Deveci M. Qahtan S. Jayaraman V. Khalid Z. |
| author2 | 57196317038 |
| author_facet | 57196317038 Alsattar H.A. Mourad N. Zaidan A.A. Deveci M. Qahtan S. Jayaraman V. Khalid Z. |
| author_sort | Alsattar H.A. |
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| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Internet of Things (IoT) real-time monitoring devices, which compromise sustainable sensing parameter-based climate change, are developed to minimize 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, modeling effective IoT real-time monitoring devices to minimize food loss and waste to support supply chain systems is crucial during natural disasters. This modeling process can be classified as multiple-attribute decision-making (MADM) given three issues: 1) the existence of multiple sensing parameter attributes; 2) the uncertainty related to the relative importance of these attributes; and 3) the variability of data. The present study endeavors 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 minimize 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 ten 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. ? 2014 IEEE. |
| format | Article |
| id | my.uniten.dspace-37220 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | my.uniten.dspace-372202025-03-03T15:48:49Z Developing IoT Sustainable Real-Time Monitoring Devices for Food Supply Chain Systems Based on Climate Change Using Circular Intuitionistic Fuzzy Set Alsattar H.A. Mourad N. Zaidan A.A. Deveci M. Qahtan S. Jayaraman V. Khalid Z. 57196317038 57212672587 58789685700 55734383000 57223984929 35606770400 58314479500 Climate change Decision making Disasters Food safety Food supply Fuzzy sets Internet of things Sensitivity analysis Supply chains Uncertainty analysis Waste management Additive ratio assessment Food security Food supply chain IOT Monitoring device Multiple attribute decision making Parameters estimation Real - Time system Real time monitoring Supply chain systems Real time systems Internet of Things (IoT) real-time monitoring devices, which compromise sustainable sensing parameter-based climate change, are developed to minimize 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, modeling effective IoT real-time monitoring devices to minimize food loss and waste to support supply chain systems is crucial during natural disasters. This modeling process can be classified as multiple-attribute decision-making (MADM) given three issues: 1) the existence of multiple sensing parameter attributes; 2) the uncertainty related to the relative importance of these attributes; and 3) the variability of data. The present study endeavors 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 minimize 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 ten 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. ? 2014 IEEE. Final 2025-03-03T07:48:49Z 2025-03-03T07:48:49Z 2024 Article 10.1109/JIOT.2023.3305910 2-s2.0-85168283341 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168283341&doi=10.1109%2fJIOT.2023.3305910&partnerID=40&md5=8c57e6ef64ef30579c00da2281eb3666 https://irepository.uniten.edu.my/handle/123456789/37220 11 16 26680 26689 Institute of Electrical and Electronics Engineers Inc. Scopus |
| spellingShingle | Climate change Decision making Disasters Food safety Food supply Fuzzy sets Internet of things Sensitivity analysis Supply chains Uncertainty analysis Waste management Additive ratio assessment Food security Food supply chain IOT Monitoring device Multiple attribute decision making Parameters estimation Real - Time system Real time monitoring Supply chain systems Real time systems Alsattar H.A. Mourad N. Zaidan A.A. Deveci M. Qahtan S. Jayaraman V. Khalid Z. Developing IoT Sustainable Real-Time Monitoring Devices for Food Supply Chain Systems Based on Climate Change Using Circular Intuitionistic Fuzzy Set |
| title | Developing IoT Sustainable Real-Time Monitoring Devices for Food Supply Chain Systems Based on Climate Change Using Circular Intuitionistic Fuzzy Set |
| title_full | Developing IoT Sustainable Real-Time Monitoring Devices for Food Supply Chain Systems Based on Climate Change Using Circular Intuitionistic Fuzzy Set |
| title_fullStr | Developing IoT Sustainable Real-Time Monitoring Devices for Food Supply Chain Systems Based on Climate Change Using Circular Intuitionistic Fuzzy Set |
| title_full_unstemmed | Developing IoT Sustainable Real-Time Monitoring Devices for Food Supply Chain Systems Based on Climate Change Using Circular Intuitionistic Fuzzy Set |
| title_short | Developing IoT Sustainable Real-Time Monitoring Devices for Food Supply Chain Systems Based on Climate Change Using Circular Intuitionistic Fuzzy Set |
| title_sort | developing iot sustainable real-time monitoring devices for food supply chain systems based on climate change using circular intuitionistic fuzzy set |
| topic | Climate change Decision making Disasters Food safety Food supply Fuzzy sets Internet of things Sensitivity analysis Supply chains Uncertainty analysis Waste management Additive ratio assessment Food security Food supply chain IOT Monitoring device Multiple attribute decision making Parameters estimation Real - Time system Real time monitoring Supply chain systems Real time systems |
| url_provider | http://dspace.uniten.edu.my/ |