Internet of Things最新文献

Internet-of-Mirrors (IoM) for connected healthcare and beauty: A prospective vision 用于联网医疗和美容的镜联网（IoM）：前景展望

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-29 DOI: 10.1016/j.iot.2024.101415

{"title":"Internet-of-Mirrors (IoM) for connected healthcare and beauty: A prospective vision","authors":"","doi":"10.1016/j.iot.2024.101415","DOIUrl":"10.1016/j.iot.2024.101415","url":null,"abstract":"<div><div>With the shift towards smart objects and automated services in many industries, the health and beauty industries are also becoming increasingly involved in AI-driven smart systems. There is a rising market demand for personalised services and a need for unified platforms in many sectors, specifically the cosmetics and healthcare industries. Alongside this rising demand, there are two major gaps when considering the integration of autonomous systems within these sectors. Firstly, the existing smart systems in the cosmetics industry are limited to single-purpose products and the employed technologies are not widespread enough to support the growing consumer demand for personalisation. Secondly, despite the rise of smart devices in healthcare, the current state-of-the-art services do not fulfil the accessibility demands and holistic nature of healthcare. To bridge these gaps, we propose integrating autonomous systems with health and beauty services through a unified visual platform coined as the Internet-of-Mirrors (IoM), an interconnected system of smart mirrors with sensing and communication capabilities where the smart mirror functions as an immersive visual dashboard to provide personalised services for health and beauty consultations and routines. We aim to present an overview of current state-of-the-art technologies that will enable the development of the IoM as well as provide a practical vision of this system with innovative scenarios to give a forward-looking vision for assistive technologies. We also discuss the missing capabilities and challenges the development of the IoM would face and outline future research directions that will support the realisation of our proposed framework.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Concept-drift-adaptive anomaly detector for marine sensor data streams 海洋传感器数据流的概念漂移自适应异常检测器

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-29 DOI: 10.1016/j.iot.2024.101414

{"title":"Concept-drift-adaptive anomaly detector for marine sensor data streams","authors":"","doi":"10.1016/j.iot.2024.101414","DOIUrl":"10.1016/j.iot.2024.101414","url":null,"abstract":"<div><div>There is an increasing industry demand for reliable Anomaly Detection (AD) solutions to detect erroneous measurements or alarm events in marine sensor data. We evaluated 36 state-of-the-art AD algorithms published in the last three decades on our three real-world univariate time-series datasets collected from marine sensors. None of them achieved the accuracy expected from the marine industry. The algorithms are underperforming on our data because they are too generalized and cannot handle unforeseen data distribution changes, referred to as concept drift.</div><div>To address these issues, we developed a novel algorithm called <span>AdapAD</span>, which incorporates sensor design information into decision-making processes and can adapt to concept drift. We actively collaborated with nine domain experts from six marine organizations to ensure that <span>AdapAD</span> meets their needs. The experiments show that <span>AdapAD</span> satisfies the accuracy expectation and outperforms 40 existing AD algorithms. The decision-making time of <span>AdapAD</span>, measured on a commodity laptop, is generally less than one minute, showing its potential for application to perform real-time AD in marine sensor data streams. <span>AdapAD</span> was acknowledged as a viable solution for automatic marine data quality control and flood detection by 17 domain experts from 12 organizations. For transparency and to facilitate further research, we provide the implementation of <span>AdapAD</span> and the real-world marine sensor data used in the study.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-enhanced multi-task and split federated learning framework for RIS-aided cell-free systems 用于 RIS 辅助无细胞系统的自增强多任务和分裂联合学习框架

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-28 DOI: 10.1016/j.iot.2024.101406

{"title":"Self-enhanced multi-task and split federated learning framework for RIS-aided cell-free systems","authors":"","doi":"10.1016/j.iot.2024.101406","DOIUrl":"10.1016/j.iot.2024.101406","url":null,"abstract":"<div><div>Collaborative learning-based beamforming schemes have been exploited to improve spectral efficiency (SE) with low privacy risks in reconfigurable intelligent surface (RIS)-aided cell-free (CF) systems. However, a single-task-driven federated learning (FL) scheme needs to run a large model on local devices with limited computing capacity due to its imbalanced computing resources. Although a single-task-driven split learning (SL) can split a large model into multiple smaller portions, it concerns the training time overhead due to its relay-based training. Meanwhile, annotation for well-labeled channel state information (CSI) still affects beamforming performance with high labeling costs. In this paper, we first propose a collaborative learning framework, named multi-task and split federated learning (M-SFL), for joint channel semantic reconstruction and beamforming for RIS-aided CF systems. The proposed M-SFL framework simultaneously tackles channel semantic reconstruction and beamforming with shared knowledge to distinguish the inherent information of user equipments (UEs). The proposed M-SFL splits large model into multiple lightweight parts friendly with the limited computing local devices and trains local and global models parallelly with the Federated server. Then, we expand the proposed M-SFL framework into a self-enhanced multi-task and split federated learning (SM-SFL) framework by integrating the contrastive learning technique. The SM-SFL framework pre-trains by predicting and distinguishing the target CSI and others without annotation, and then we fine-tune the local and global models with limited labeled CSI. Simulation results show that the proposed framework can jointly achieve better channel semantic reconstruction and higher SE with balanced computing resources, faster beamforming, and low labeling costs.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Combinative model compression approach for enhancing 1D CNN efficiency for EIT-based Hand Gesture Recognition on IoT edge devices 采用组合模型压缩方法提高基于 EIT 的物联网边缘设备手势识别的一维 CNN 效率

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-28 DOI: 10.1016/j.iot.2024.101403

{"title":"Combinative model compression approach for enhancing 1D CNN efficiency for EIT-based Hand Gesture Recognition on IoT edge devices","authors":"","doi":"10.1016/j.iot.2024.101403","DOIUrl":"10.1016/j.iot.2024.101403","url":null,"abstract":"<div><div>Tiny Machine Learning is rapidly evolving in edge computing and intelligent Internet of Things (IoT) devices. This paper investigates model compression techniques with the aim of determining their compatibility when combined, and identifying an effective approach to improve inference speed and energy efficiency within IoT edge devices. The study is carried out on the application scenario of Hand Gesture Recognition (HGR) based on Electrical Impedance Tomography (EIT), which involves complex signal processing and needs real-time processing and energy efficiency. Therefore, a customized 1-Dimensional Convolutional Neural Network (1D CNN) HGR classification model has been designed. An approach based on strategically combining model compression techniques was then implemented resulting in a model customized for faster inference and improved energy efficiency for IoT embedded devices. The model size became compact at 10.42 kB, resulting in a substantial size reduction of 98.8%, and an inference gain of 94.73% on a personal computer with approximately 8.56% decrease in accuracy. The approach of combinative model compression techniques was applied to a wide range of edge-computing IoT devices with limited processing power, resulting in a significant improvement in model execution speed and energy efficiency for these devices. Specifically, there was an average power consumption gain of 52% for Arduino Nano BLE and 34.05% for Raspberry Pi 4. Inference time was halved for Arduino Nano BLE Sense, Nicla Sense, and Raspberry Pi 4, with a remarkable gain of 94% for ESP32.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative analysis of the standalone and Hybrid SDN solutions for early detection of network channel attacks in Industrial Control Systems: A WWTP case study 用于早期检测工业控制系统中网络通道攻击的独立和混合 SDN 解决方案的比较分析：污水处理厂案例研究

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-28 DOI: 10.1016/j.iot.2024.101413

{"title":"Comparative analysis of the standalone and Hybrid SDN solutions for early detection of network channel attacks in Industrial Control Systems: A WWTP case study","authors":"","doi":"10.1016/j.iot.2024.101413","DOIUrl":"10.1016/j.iot.2024.101413","url":null,"abstract":"<div><div>Industrial Control Systems (ICS) are critical to operating various Critical infrastructures (CIs). However, ICS communication channels connecting sensors, actuators, and local and supervisory controllers are vulnerable to network attacks compromising the system’s availability and integrity. This study proposes and compares Standalone and Hybrid Software Defined Networking (SDN) solutions to mitigate (Detect and Respond) network channel attacks in ICS environments. The methodology utilised applies a testbed designed in GNS3 following the IEC 62264 Industrial Automation Pyramid. It incorporates ICS components such as PLCs and SCADA and a Simulink-based digital twin system for a wastewater treatment plant. This research establishes a proof of concept involving detection and response to network channel attacks evaluated through packet thresholds, packet analysis, and cryptographic hashing techniques in SDN. The Mitre attack framework is implemented to provide insight into the system’s vulnerabilities through adversary emulation. The research findings reveal that both SDN solutions effectively enhance ICS network security; the Standalone SDN solution is more suitable for time-sensitive networks, while the Hybrid SDN solution better serves non-time-sensitive industrial environments. While the Standalone SDN solution offers a 75% efficiency improvement, its’ status as a nascent technology introduces unresolved vulnerabilities and limited testing favouring the Hybrid SDN solution, which provides robust security and reliability due to the integration with the Snort IDS. Thus, selecting the appropriate solution requires carefully considering the trade-offs between enhanced performance and established security. In conclusion, this study underscores the potential of SDN solutions in strengthening ICS security and suggests areas for future research.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic IoT deployment reconfiguration: A global-level self-organisation approach 动态物联网部署重组：全球级自组织方法

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-28 DOI: 10.1016/j.iot.2024.101412

{"title":"Dynamic IoT deployment reconfiguration: A global-level self-organisation approach","authors":"","doi":"10.1016/j.iot.2024.101412","DOIUrl":"10.1016/j.iot.2024.101412","url":null,"abstract":"<div><div>The edge–cloud continuum provides a heterogeneous, multi-scale, and dynamic infrastructure supporting complex deployment profiles and trade-offs for application scenarios like those found in the Internet of Things and large-scale cyber–physical systems domains. To exploit the continuum, applications should be designed in a way that promotes flexibility and reconfigurability, and proper management (sub-)systems should take care of reconfiguring them in response to changes in the environment or non-functional requirements. Approaches may leverage optimisation-based or heuristic-based policies, and decision making may be centralised or distributed: this work investigates decentralised heuristic-based approaches. In particular, we focus on the pulverisation approach, whereby a distributed software system is automatically partitioned (“pulverised”) into different deployment units. In this context, we address two main research problems: how to support the runtime reconfiguration of pulverised systems, and how to specify decentralised reconfiguring policies by a global perspective. To address the first problem, we design and implement a middleware for pulverised systems separating infrastructural and application concerns. To address the second problem, we leverage aggregate computing and exploit self-organisation patterns to devise self-stabilising reconfiguration strategies. By simulating deployments on different kinds of complex infrastructures, we assess the flexibility of the pulverisation middleware design as well as the effectiveness and resilience of the aggregate computing-based reconfiguration policies.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Physical unclonable functions and QKD-based authentication scheme for IoT devices using blockchain 使用区块链的物联网设备的物理不可克隆功能和基于 QKD 的身份验证方案

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-25 DOI: 10.1016/j.iot.2024.101404

{"title":"Physical unclonable functions and QKD-based authentication scheme for IoT devices using blockchain","authors":"","doi":"10.1016/j.iot.2024.101404","DOIUrl":"10.1016/j.iot.2024.101404","url":null,"abstract":"<div><div>As the number of Internet of Things (IoT) devices is increasing exponentially, strong security measures are needed to guard against different types of cyberattacks. This research offers a novel IoT device authentication technique to mitigate these challenges by integrating three cutting-edge technologies namely blockchain technology, Quantum Key Distribution (QKD), and Physically Unclonable Functions (PUFs). By utilizing the distinctive qualities of PUFs for device identification and the unrivaled security of QKD for key exchange, the proposed approach seeks to address the significant security issues present in IoT environments. Adopting blockchain technology ensures transparency and verifiability of the authentication process across distributed IoT networks by adding an unchangeable, decentralized layer of trust. An examination of the computing and communication costs reveals that the proposed protocol is effective, necessitating low computational resources that are critical for IoT devices with limited resources. The protocol’s resistance against a variety of attacks is demonstrated by formal proofs based on the Real-Or-Random (ROR) model and security evaluations using the Scyther tool, ensuring the integrity and secrecy of communications. Various threats are analyzed, and the protocol is proven to be secure and efficient from all forms of attacks.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analyzing common lexical features of fake news using multi-head attention weights 利用多头注意力权重分析假新闻的共同词汇特征

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-24 DOI: 10.1016/j.iot.2024.101409

{"title":"Analyzing common lexical features of fake news using multi-head attention weights","authors":"","doi":"10.1016/j.iot.2024.101409","DOIUrl":"10.1016/j.iot.2024.101409","url":null,"abstract":"<div><div>Numerous approaches have been developed to identify fake news through machine learning; however, these methods are predominantly assessed using singular datasets specific to certain fields, leading to a scarcity of research on versatile models adaptable to a range of domains. This study evaluates the adaptability of a fake news detection model across diverse fields, employing three distinct datasets. Furthermore, the study leverages the multi-head attention feature of bidirectional encoder representations from transformers (BERT) to scrutinize the feature extraction process in the model. In our analysis, we focused on words that are commonly emphasized by machine learning in fake news detection. The dataset comprised 27,442 instances of genuine news and 28,359 instances of fabricated news, each distinctly labeled. To examine the focal words, we utilized multi-head attention, a component of BERT. This mechanism assigns greater weight to words that receive more attention. Our investigation aimed to identify which words were assigned higher weights in each article. The findings indicate that while representing a minor percentage, a common characteristic of fake news is the heightened attention to words that influence the credibility of the article. To assess the versatility of the model, we applied the model trained on one dataset to classify other datasets. The results demonstrate a notable decline in accuracy, attributable to the distinctive characteristics of the training data. These observations suggest that common features among fake news, which could be extracted using the fine-tuned BERT model, are limited.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Powerful graph neural network for node classification of the IoT network 用于物联网网络节点分类的强大图神经网络

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-24 DOI: 10.1016/j.iot.2024.101410

{"title":"Powerful graph neural network for node classification of the IoT network","authors":"","doi":"10.1016/j.iot.2024.101410","DOIUrl":"10.1016/j.iot.2024.101410","url":null,"abstract":"<div><div>Internet of Things (IoT) devices are increasingly used in various applications in our daily lives. The network structure for IoT is heterogeneous and can create a complex architecture depending on the application and geographical structure. To efficiently process the information within this diverse and complex relationship, a robust data structure is needed for network operations. Graph neural network (GNN) technology is emerging as a capable tool for predicting complex data structures, such as graphs. Graphs can be employed to mimic the structure of IoT network and process information from IoT nodes using GNN techniques. In this paper, our goal is to explore the effectiveness of GNN in performing the node classification task for a given IoT network. We have generated three different IoT networks with varying network sizes, number of nodes, and feature sizes. We then test 12 different GNN algorithms to evaluate their performance in IoT node classification. Each method is examined in detail to observe its training behavior, testing behavior, and resilience against noise. In addition, time complexity and generalization ability of each model have also been studied. The experimental results show that some methods exhibit high resilience against noisy data for IoT node classification accuracy.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fuzzy-based task offloading in Internet of Vehicles (IoV) edge computing for latency-sensitive applications 车联网 (IoV) 边缘计算中基于模糊的任务卸载，适用于延迟敏感型应用

IF 6 3区计算机科学

Internet of Things Pub Date : 2024-10-24 DOI: 10.1016/j.iot.2024.101392

{"title":"Fuzzy-based task offloading in Internet of Vehicles (IoV) edge computing for latency-sensitive applications","authors":"","doi":"10.1016/j.iot.2024.101392","DOIUrl":"10.1016/j.iot.2024.101392","url":null,"abstract":"<div><div>As vehicular applications continue to evolve, the computational capabilities of individual vehicles alone are no longer sufficient to meet the increasing demands. This has led to the integration of edge computing in the Internet of Vehicles (IoV) as an essential solution. Due to the limited resources within vehicles, there is often a need to offload tasks to edge nodes. However, task offloading in IoV environments presents several challenges, including high mobility, dynamic network topology, and varying node density. Traditional offloading methods fail to effectively address these challenges. Moreover, tasks differ in importance, necessitating a mechanism for edge nodes to prioritize tasks based on their urgency. To overcome these challenges, we propose a Vehicle-to-Vehicle (V2V) fuzzy-based task offloading scheme. In this scheme, fuzzy logic plays a critical role by enabling dynamic prioritization of tasks based on their urgency and the available computational resources at edge nodes, ensuring intelligent, context-aware decision-making. The user vehicle selects an appropriate edge node using an edge selection mechanism, which guarantees prolonged connection time and sufficient computational resources. Tasks at the edge are then organized based on their latency requirements and evaluated using a fuzzy rule-based inference system. Our simulation results demonstrate improved task execution rates, reduced overall system delay, and minimized queuing delays.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":null,"pages":null},"PeriodicalIF":6.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0