2022 IEEE International Conference on Smart Internet of Things (SmartIoT)最新文献_第2页

A hybrid SOM and HMM classifier in a Fog Computing gateway for Ambient Assisted Living Environment 环境辅助生活环境中SOM和HMM混合分类器的雾计算网关

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00042

N. Suryadevara, Subham Saha

引用次数: 0

Uncertainty Measured Active Client Selection for Federated Learning in Smart Grid 基于不确定性测量的智能电网联邦学习主动客户端选择

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00032

Peng Li, Yunfeng Zhao, Liandong Chen, Kai Cheng, Chuyue Xie, Xiaofei Wang, Qinghua Hu

{"title":"Uncertainty Measured Active Client Selection for Federated Learning in Smart Grid","authors":"Peng Li, Yunfeng Zhao, Liandong Chen, Kai Cheng, Chuyue Xie, Xiaofei Wang, Qinghua Hu","doi":"10.1109/SmartIoT55134.2022.00032","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00032","url":null,"abstract":"Federated learning is a hot machine learning research direction, its goal is to train a high quality central model while protecting the privacy of all parties, and it has a broad application prospect in smart grid and other fields. However, in federated learning with massive client participation, it is impossible to have all clients participate in training and model aggregation every time due to the limitation of communication and computing resources. Usually the method of selecting clients for federated learning is random, some studies have studied this problem from aspects of client data quality, model training effect, communication and computing resources, etc. In this paper, we propose an active client selection algorithm from the perspective of model uncertainty, this algorithm is called uncertainty measured active client selection in FL (UCS-FL). The server actively selects a subset of clients to participate in the FL training, and the unselected clients do not need to train in this round, saving computing and communication resources. Perform a thorough empirical analysis of the image classification task to demonstrate the excellent performance of UCS-FL against baseline in the context of monitored FL settings. Finally, we describes the real-world application of the proposed architecture, especially in smart grid scenarios.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194453","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}

引用次数: 3

A 0.32-V 151-nW Voltage Reference for Smart IoT Applications 用于智能物联网应用的0.32 v 151-nW基准电压

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00015

Yuntao Wu, Mingyi Chen

引用次数: 1

Visualized Intelligent Warehouse Safety Control System Using Target Detection 基于目标检测的可视化智能仓库安全控制系统

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00049

Bin Zhang, Yi Hao, Jing Zhou, Xiaoming Li, Huichao Li, Shuai Wang, Ximin Sun

引用次数: 0

Optimization of Warehousing Material Turnover Time Based on Clustering 基于聚类的仓储物料周转时间优化

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00047

Yong Li, Xiaoyun Tian, Jiangkai Jia, Bin Zheng, Hairu Li, Mingda Wang, Ximin Sun

引用次数: 0

Smart Nanosensor Networks for Body Injury Detection 用于身体损伤检测的智能纳米传感器网络

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00012

Lawrence He, Mark Eastburn

{"title":"Smart Nanosensor Networks for Body Injury Detection","authors":"Lawrence He, Mark Eastburn","doi":"10.1109/SmartIoT55134.2022.00012","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00012","url":null,"abstract":"Nanosensors synthesize the most recent advantages of nanomaterials and biosensing technologies. Injury detection is one of the important areas of nanosensor applications in healthcare. It is especially useful to the injuries that are more difficult to diagnose at the early stage with the traditional medical methods. This paper focuses on the nanosensor networks for human body injury detection. After reviewing recent progress in the biomedical nanosensor development, an architecture is proposed to employ nanosensors to collect the bio-parameters of the injury part in a human body. Key elements of the architecture are nanosensors, data collectors, medical servers, as well as healthcare providers. Major functions on the biomedical data processing are analyzed in a structure with three layers: sensing layer, networking layer, and application layer. Each layer conducts different data processing functionalities to facilitate sensing, collecting, and analyzing of the vitals. Based on the IEEE nano-scale communication framework, a mathematical model is further derived. This model represents the trade-off between the nanosensor network resource and its injury detection performance. The problem constraints describe the characteristics of the patient body and the injury part. Simulations are conducted in several sets of typical cases to evaluate the model performance. Results demonstrate that the nanosensor amount selection is determined by multiple bio-factors of the human body and the injury part.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130315665","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}

引用次数: 2

Resource Allocation and Load Balancing Based on Edge Computing in Industrial Networks 基于边缘计算的工业网络资源分配与负载均衡

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00048

Ximin Sun, Jiangkai Jia, Zan Liu, Yong Li, Bo Sun, Dan Liu

引用次数: 0

IoT-Based Blood Quality Monitoring: Using LoRaWAN 基于物联网的血液质量监测:使用LoRaWAN

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00017

M. Usman, M. Alryan, M. Qaiser, M. Omar, S. Khan, S. Larkin, B. Raw

引用次数: 0

The transitional phase of Boost.Asio and POCO C++ networking libraries towards IPv6 and IoT networking security Boost的过渡阶段。面向IPv6和IoT网络安全的Asio和POCO c++网络库

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00022

E. Kadusic, N. Zivic, Narcisa Hadzajlic, C. Ruland

{"title":"The transitional phase of Boost.Asio and POCO C++ networking libraries towards IPv6 and IoT networking security","authors":"E. Kadusic, N. Zivic, Narcisa Hadzajlic, C. Ruland","doi":"10.1109/SmartIoT55134.2022.00022","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00022","url":null,"abstract":"With the global transition to the IPv6 (Internet Protocol version 6), IP (Internet Protocol) validation efficiency and IPv6 support from the aspect of network programming are gaining more importance. As global computer networks grow in the era of IoT (Internet of Things), IP address validation is an inevitable process for assuring strong network privacy and security. The complexity of IP validation has been increased due to the rather drastic change in the memory architecture needed for storing IPv6 addresses. Low-level programming languages like C/C++ are a great choice for handling memory spaces and working with simple devices connected in an IoT (Internet of Things) network. This paper analyzes some user-defined and open-source implementations of IP validation codes in Boost. Asio and POCO C++ networking libraries, as well as the IP security support provided for general networking purposes and IoT. Considering a couple of sample codes, the paper gives a conclusion on whether these C++ implementations answer the needs for flexibility and security of the upcoming era of IPv6 addressed computers.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115057609","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}

引用次数: 0

A cardinality estimation scheme for the number of unknown RFID tags under unreliable channels 不可靠信道下未知RFID标签数量的基数估计方案

2022 IEEE International Conference on Smart Internet of Things (SmartIoT) Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00016

Tiancong Wang, Bin Wang

{"title":"A cardinality estimation scheme for the number of unknown RFID tags under unreliable channels","authors":"Tiancong Wang, Bin Wang","doi":"10.1109/SmartIoT55134.2022.00016","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00016","url":null,"abstract":"In recent years, RFID technologies have been widely used in real-life applications, including supply chain manage-ment, warehouse tracking, etc. One of the concerns is the estimation of the number of interested tags. The existence of unknown tags will affect normal operation and management for RFID systems. Existing protocols for estimating the number of unknown tags generally assume ideal communication channels. In practice, there may exist environment interference that affects the transmission from tags to a RFID reader. In this paper, we study the problem of estimating the number of unknown tags under unreliable channels, and propose a cardinality estimation scheme CEUT(Cardinality Estimation for Unknown Tags under unreliable channels). The reader collects responses from all tags after running the Aloha protocol. The number of non-empty slots in the response frame increases due to the presence of unknown tags is designed based on the number of empty slots in the predicted frame converted into non-empty slots in the response frame and the channel noise parameter. The simulation results show that, under the unreliable channel, the estimation result scheme yielded by CEUT is more robust than other existing schemes, and can achieve therequired estimation accuracy.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130858633","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}

引用次数: 2