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 minimise 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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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , , , |
| منشور في: |
2024
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/3085 https://doi.org/10.1109/JIOT.2023.3305910. |
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| _version_ | 1862980618937171968 |
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| author | A. Alsattar, Hassan |
| author2 | Mourad, Nahia Zaidan, A.A. Deveci, Muhammet Member, IEEE Qahtan, Sarah Jayaraman, Vaidyanathan Khalid, Zainab |
| author2_role | author author author author author author author |
| author_facet | A. Alsattar, Hassan Mourad, Nahia Zaidan, A.A. Deveci, Muhammet Member, IEEE Qahtan, Sarah Jayaraman, Vaidyanathan Khalid, Zainab |
| author_role | author |
| dc.creator.none.fl_str_mv | A. Alsattar, Hassan Mourad, Nahia Zaidan, A.A. Deveci, Muhammet Member, IEEE Qahtan, Sarah Jayaraman, Vaidyanathan Khalid, Zainab |
| dc.date.none.fl_str_mv | 2024-02-21 2025-05-21T16:27:47Z 2025-05-21T16:27:47Z |
| dc.identifier.none.fl_str_mv | 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. 2327-4662 https://bspace.buid.ac.ae/handle/1234/3085 https://doi.org/10.1109/JIOT.2023.3305910. |
| dc.language.none.fl_str_mv | en_US |
| dc.publisher.none.fl_str_mv | Natural Language Processing (NLP), Koçtaş, video camera, FSA-Net |
| dc.relation.none.fl_str_mv | IEEE Internet of Things Journalv11 n16 (2024): 26680-26689 |
| dc.subject.none.fl_str_mv | Additive ratio assessment (ARAS) , climate change , food security , Internet of Things (IoT) , multiattribute decision-making (MADM) |
| dc.title.none.fl_str_mv | Developing IoT Sustainable Real-time Monitoring Devices for Food Supply Chain Systems based on Climate Change using Circular Intuitionistic Fuzzy Set |
| dc.type.none.fl_str_mv | Article |
| description | 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. |
| id | budr_8beae14b18dfe7d862dc87cb44b10007 |
| identifier_str_mv | 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. 2327-4662 |
| language_invalid_str_mv | en_US |
| network_acronym_str | budr |
| network_name_str | The British University in Dubai repository |
| oai_identifier_str | oai:bspace.buid.ac.ae:1234/3085 |
| publishDate | 2024 |
| publisher.none.fl_str_mv | Natural Language Processing (NLP), Koçtaş, video camera, FSA-Net |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Developing IoT Sustainable Real-time Monitoring Devices for Food Supply Chain Systems based on Climate Change using Circular Intuitionistic Fuzzy SetA. Alsattar, HassanMourad, NahiaZaidan, A.A.Deveci, MuhammetMember, IEEEQahtan, SarahJayaraman, VaidyanathanKhalid, ZainabAdditive ratio assessment (ARAS) , climate change , food security , Internet of Things (IoT) , multiattribute decision-making (MADM)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.Natural Language Processing (NLP), Koçtaş, video camera, FSA-Net2025-05-21T16:27:47Z2025-05-21T16:27:47Z2024-02-21ArticleAlsattar, 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. 26680–26689.2327-4662https://bspace.buid.ac.ae/handle/1234/3085https://doi.org/10.1109/JIOT.2023.3305910.en_USIEEE Internet of Things Journalv11 n16 (2024): 26680-26689oai:bspace.buid.ac.ae:1234/30852026-01-29T16:47:09Z |
| spellingShingle | Developing IoT Sustainable Real-time Monitoring Devices for Food Supply Chain Systems based on Climate Change using Circular Intuitionistic Fuzzy Set A. Alsattar, Hassan Additive ratio assessment (ARAS) , climate change , food security , Internet of Things (IoT) , multiattribute decision-making (MADM) |
| 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 | Additive ratio assessment (ARAS) , climate change , food security , Internet of Things (IoT) , multiattribute decision-making (MADM) |
| url | https://bspace.buid.ac.ae/handle/1234/3085 https://doi.org/10.1109/JIOT.2023.3305910. |