Pub Date : 2022-10-01DOI: 10.1109/msmc.2022.3205493
Haibin Zhu
{"title":"Blockchain and Artificial Intelligence Are Also Hot Topics in the IEEE Systems, Man, and Cybernetics Society [Editorial]","authors":"Haibin Zhu","doi":"10.1109/msmc.2022.3205493","DOIUrl":"https://doi.org/10.1109/msmc.2022.3205493","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"71 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85335606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.1109/msmc.2022.3216167
{"title":"2022 Index Systems, Man and Cybernetics Mag., Vol. 8","authors":"","doi":"10.1109/msmc.2022.3216167","DOIUrl":"https://doi.org/10.1109/msmc.2022.3216167","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"17 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89119482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.1109/MSMC.2022.3198023
Lulwah M. Alkwai
Rich material is buried in the entity’s textual description information, its hierarchical-type information, and the graph’s topological structure information in the knowledge graph. As a result, these data can be a useful supplement to triple information in terms of improving performance. To appropriately exploit these social Internet of Things (IoT) data, entity details are first encoded using artificial-intelligence (AI)-based convolutional neural networks (CNNs). The unit vector and unit description vector are then projected into a given relational space using the hierarchical-type information, thus restricting its semantic content. The graph attention approach is then used to fuse the graph’s topological structure information to calculate the influence of various neighboring points on the entity. To deal with the data-sparse problem, the multihop relationship information among entities is calculated at the same time. Finally, a decoder is used to collect global information among dimensions. Link prediction experiments show that the multisource information combined knowledge representation learning (XAI-CNN) model based on explainable AI (XAI) can effectively use multisource social IoT information beyond triples and that other techniques may be better than the baseline model.
{"title":"An Explainable Artificial-Intelligence-Based CNN Model for Knowledge Extraction From the Social Internet of Things: Proposing a New Model","authors":"Lulwah M. Alkwai","doi":"10.1109/MSMC.2022.3198023","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3198023","url":null,"abstract":"Rich material is buried in the entity’s textual description information, its hierarchical-type information, and the graph’s topological structure information in the knowledge graph. As a result, these data can be a useful supplement to triple information in terms of improving performance. To appropriately exploit these social Internet of Things (IoT) data, entity details are first encoded using artificial-intelligence (AI)-based convolutional neural networks (CNNs). The unit vector and unit description vector are then projected into a given relational space using the hierarchical-type information, thus restricting its semantic content. The graph attention approach is then used to fuse the graph’s topological structure information to calculate the influence of various neighboring points on the entity. To deal with the data-sparse problem, the multihop relationship information among entities is calculated at the same time. Finally, a decoder is used to collect global information among dimensions. Link prediction experiments show that the multisource information combined knowledge representation learning (XAI-CNN) model based on explainable AI (XAI) can effectively use multisource social IoT information beyond triples and that other techniques may be better than the baseline model.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"11 1","pages":"48-51"},"PeriodicalIF":3.2,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76737846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.1109/MSMC.2022.3197914
Urvashi Sugandh, Swati Nigam, Manju Khari
Blockchain technology swiftly rose to prominence in a wide range of applications within the smart agriculture field. The necessity to construct smart peer-to-peer systems capable of validating, securing, monitoring, and analyzing agricultural data has prompted discussions regarding the development of blockchain-based Internet of Things (IoT) systems in smart agriculture. Blockchain technology plays a critical role in the transformation of traditional means of storing, sorting, and exchanging agricultural data into a more trustworthy, immutable, transparent, and decentralized method of sharing data. Smart farming will benefit from the integration of the IoT and the blockchain, which will take us from having merely smart farms to having an Internet of smart farms as well as provide better control over supply chain networks in general. As a consequence of this combination, smart agriculture will be managed more autonomously and intelligently, resulting in greater efficiency and optimization of operations.
{"title":"Blockchain Technology in Agriculture for Indian Farmers: A Systematic Literature Review, Challenges, and Solutions","authors":"Urvashi Sugandh, Swati Nigam, Manju Khari","doi":"10.1109/MSMC.2022.3197914","DOIUrl":"https://doi.org/10.1109/MSMC.2022.3197914","url":null,"abstract":"Blockchain technology swiftly rose to prominence in a wide range of applications within the smart agriculture field. The necessity to construct smart peer-to-peer systems capable of validating, securing, monitoring, and analyzing agricultural data has prompted discussions regarding the development of blockchain-based Internet of Things (IoT) systems in smart agriculture. Blockchain technology plays a critical role in the transformation of traditional means of storing, sorting, and exchanging agricultural data into a more trustworthy, immutable, transparent, and decentralized method of sharing data. Smart farming will benefit from the integration of the IoT and the blockchain, which will take us from having merely smart farms to having an Internet of smart farms as well as provide better control over supply chain networks in general. As a consequence of this combination, smart agriculture will be managed more autonomously and intelligently, resulting in greater efficiency and optimization of operations.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"37 1","pages":"36-43"},"PeriodicalIF":3.2,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78599904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/msmc.2022.3177330
{"title":"Special Issue on Advancements, Challenges and Application of Parallel and Distributed Algorithms [Call for Papers]","authors":"","doi":"10.1109/msmc.2022.3177330","DOIUrl":"https://doi.org/10.1109/msmc.2022.3177330","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"18 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77518914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/msmc.2022.3177349
{"title":"Special Issue on Explainable Artificial Intelligence for Social Internet of Things (XSIoT): Analysis and Modeling using Collaborative Technologies [Call for Papers]","authors":"","doi":"10.1109/msmc.2022.3177349","DOIUrl":"https://doi.org/10.1109/msmc.2022.3177349","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"7 7","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72369157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/msmc.2022.3177351
Haibin Zhu
{"title":"Getting to Know Our Volunteers [Meet Our Volunteers]","authors":"Haibin Zhu","doi":"10.1109/msmc.2022.3177351","DOIUrl":"https://doi.org/10.1109/msmc.2022.3177351","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"54 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84802205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/msmc.2022.3162696
Fargol Nematkhah, F. Aminifar, M. Shahidehpour, S. Mokhtari
The excessive number of connected devices and the unprecedented large volumes of data have triggered significant advancements in computing technologies to leverage the collected data for establishing novel services. Accordingly, cloud, edge, and fog notions have been developed to provide data processing, storage, and networking to fulfill the ever-changing application requirements. Recent efforts have attempted to push data processing closer to the edge of the network, where potential data producers and consumers reside. The evolving paradigm of computing methods has enabled innovative data-based solutions in health-care, industry, transportation, and energy domains for societal, economic, and productivity enhancements. Along with the computational shifts, power systems are undergoing transformative changes. Extensive penetration of nondispatchable generation resources, electric vehicles (EVs), and storage systems is occurring at various levels of power systems, particularly at the edge of the grid.
{"title":"Evolution in Computing Paradigms for Internet of Things-Enabled Smart Grid Applications: Their Contributions to Power Systems","authors":"Fargol Nematkhah, F. Aminifar, M. Shahidehpour, S. Mokhtari","doi":"10.1109/msmc.2022.3162696","DOIUrl":"https://doi.org/10.1109/msmc.2022.3162696","url":null,"abstract":"The excessive number of connected devices and the unprecedented large volumes of data have triggered significant advancements in computing technologies to leverage the collected data for establishing novel services. Accordingly, cloud, edge, and fog notions have been developed to provide data processing, storage, and networking to fulfill the ever-changing application requirements. Recent efforts have attempted to push data processing closer to the edge of the network, where potential data producers and consumers reside. The evolving paradigm of computing methods has enabled innovative data-based solutions in health-care, industry, transportation, and energy domains for societal, economic, and productivity enhancements. Along with the computational shifts, power systems are undergoing transformative changes. Extensive penetration of nondispatchable generation resources, electric vehicles (EVs), and storage systems is occurring at various levels of power systems, particularly at the edge of the grid.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"99 1","pages":"8-20"},"PeriodicalIF":3.2,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79260216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/msmc.2022.3172826
Xiaonan Wang, Xinyan Qian
The Internet of Things (IoT) aims to improve the quality of human life by delivering collected data efficiently for real-time monitoring. With the increasing complexity of data, it is hard for an individual IoT device to produce information due to the restrictions of visual angles and resources. For instance, the camera mounted on the front of a vehicle captures only data from the road ahead; it cannot collect information from the side. The local cloud (LC) is a new communication paradigm where cloud members collaboratively generate data locally by sharing their resources, so integration of the IoT and LC (ITLC) should be an effective way to overcome the resource restriction of an individual device. Named data networking (NDN) is a novel and efficient communication mechanism, and its features are able to assist in realizing the ITLC and enhancing the efficiency of ITLC-based data delivery. However, NDN has different architectures and features than the ITLC, so it is challenging to exploit NDN to realize ITLC. In this article, we propose an edge-assisted, NDN-based ITLC framework and provide evaluation results that verify its advances.
{"title":"Toward Named Data Networking: An Approach Based the Internet of Things Cloud With Edge Assistance","authors":"Xiaonan Wang, Xinyan Qian","doi":"10.1109/msmc.2022.3172826","DOIUrl":"https://doi.org/10.1109/msmc.2022.3172826","url":null,"abstract":"The Internet of Things (IoT) aims to improve the quality of human life by delivering collected data efficiently for real-time monitoring. With the increasing complexity of data, it is hard for an individual IoT device to produce information due to the restrictions of visual angles and resources. For instance, the camera mounted on the front of a vehicle captures only data from the road ahead; it cannot collect information from the side. The local cloud (LC) is a new communication paradigm where cloud members collaboratively generate data locally by sharing their resources, so integration of the IoT and LC (ITLC) should be an effective way to overcome the resource restriction of an individual device. Named data networking (NDN) is a novel and efficient communication mechanism, and its features are able to assist in realizing the ITLC and enhancing the efficiency of ITLC-based data delivery. However, NDN has different architectures and features than the ITLC, so it is challenging to exploit NDN to realize ITLC. In this article, we propose an edge-assisted, NDN-based ITLC framework and provide evaluation results that verify its advances.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"35 1","pages":"21-27"},"PeriodicalIF":3.2,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79361963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1109/msmc.2022.3177331
{"title":"The 2021 IEEE International Conference on Systems, Man, and Cybernetics Report [Conference Reports]","authors":"","doi":"10.1109/msmc.2022.3177331","DOIUrl":"https://doi.org/10.1109/msmc.2022.3177331","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"126 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88032209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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