Internet of Things最新文献

{"title":"Blockchain based handle system to secure Predictive maintenance analysis system in Industrial IoT using L2S–GRU","authors":"Mahamat Ali Hisseine ,&nbsp;Deji Chen ,&nbsp;Xiao Yang","doi":"10.1016/j.iot.2025.101549","DOIUrl":"10.1016/j.iot.2025.101549","url":null,"abstract":"<div><div>The handle system that assigns persistent identifiers to the information resources is utilized by the Predictive Maintenance analysis. The persistent identifiers are referred to as the handles that assist as a unique and enduring reference for locating, accessing, and utilizing the resources. Nevertheless, Industrial Internet of Things devices were affected by insider attacks in most of the prevailing works. Thus, an effective Blockchain-enabled secure handle system using Adversarial Stylometry-KAnonymity and <span><math><mrow><mi>L</mi><mi>o</mi><msup><mrow><mi>g</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></math></span> Sigmoid–Gated Recurrent Unit is presented in this paper. It is proposed to enhance the Handle System’s scalability and support real-time data processing. Primarily, the Industrial Internet of Things device and user are registered with the Blockchain. Then, based on Adversarial Stylometry-KAnonymity, the details are privacy preserved. Meanwhile, for the Industrial Internet of Things devices and users, the keys, Quick Response code, and hashcode are generated. Later, the Industrial Internet of Things device setup grounded on Message Authentication Code creation and data sensing is conducted. After that, by using Triangular and S-shaped-fuzzy, a controlled access-based smart contract is created. The Fuzzy system is used to enhance the smart contract by enabling flexible and dynamic decision-making in the context of undefined or inaccurate data. Extensive experiments and analysis proved the effectiveness of the proposed framework for predictive maintenance in Industrial Internet of Things. The outcomes proved that a higher accuracy of 99.12%, Precision of 99.24% and of Recall 99.33% was attained by the proposed model, thereby outperforming similar existing models.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101549"},"PeriodicalIF":6.0,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593307","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}

{"title":"Distributing intelligent functionalities in the Internet of Things with agents and Digital Twins","authors":"Samuele Burattini ,&nbsp;Stefano Mariani ,&nbsp;Sara Montagna ,&nbsp;Marco Picone ,&nbsp;Alessandro Ricci","doi":"10.1016/j.iot.2025.101560","DOIUrl":"10.1016/j.iot.2025.101560","url":null,"abstract":"<div><div>Autonomous Agents (AAs) and Digital Twins (DTs) are two widely used abstractions in the literature about the engineering of “intelligent” Internet of Things (IoT) systems and applications. However, their role can be considered partially overlapping given the fragmented landscape of approaches emerging from the literature. There, in fact, either AAs or DTs, or their combination, are sometimes used for achieving the same goals. In this paper, we attempt to clarify similarities and differences of these abstractions and argue that the choice to use AAs or DTs (or an integration of the two) should stem from a principled analysis of the IoT system requirements. That is, by matching the desired <em>intelligent functionalities</em> with the properties of the two abstractions to find the most appropriate one. Accordingly, we <em>(i)</em> analyse the state-of-the-art approaches to identify how AAs and DTs are currently used to encapsulate and distribute intelligent functionalities across IoT system components; <em>(ii)</em> propose a set of <em>principles</em> to assist designers in choosing the most suitable abstraction for a given functionality; and <em>(iii)</em> discuss exemplary architectures that may arise from applying such principles. To conceptually validate our contribution, we analyse the practical case of an intelligent manufacturing system and show how following the outlined principles leads to interesting properties in the final system design.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101560"},"PeriodicalIF":6.0,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593308","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}

{"title":"Solar forced convection dryer for agriproducts monitored by IoT","authors":"Juan Francisco Villa-Medina ,&nbsp;Miguel Ángel Porta-García ,&nbsp;Joaquín Gutiérrez ,&nbsp;Miguel Ángel Porta-Gándara","doi":"10.1016/j.iot.2025.101566","DOIUrl":"10.1016/j.iot.2025.101566","url":null,"abstract":"<div><div>A solar dryer was implemented to monitor the drying process of agricultural products using the Internet of Things (IoT). Remote supervision is facilitated by real-time data transmission and reception via a web interface. The dryer employs forced convection to achieve efficient drying and offers control by manipulating the mass flow rate. Base components of the dryer include an electrical fan for mass flow generation, a load cell for precise measurement of product weight loss, and an embedded camera for continuous monitoring of the drying progress. A photovoltaic panel connected to a rechargeable battery supplies the electrical energy required for dryer operation. The dryer performance was evaluated by drying three different fruits under varying mass flow conditions within the drying chamber. These experimental conditions were programmed remotely using mobile devices. Results demonstrate that this low-cost IoT forced convective solar dryer holds great potential as a valuable tool for enhancing agriproduct drying quality.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101566"},"PeriodicalIF":6.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578209","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}

{"title":"Reducing communication overhead in the IoT–edge–cloud continuum: A survey on protocols and data reduction strategies","authors":"Dora Kreković ,&nbsp;Petar Krivić ,&nbsp;Ivana Podnar Žarko ,&nbsp;Mario Kušek ,&nbsp;Danh Le-Phuoc","doi":"10.1016/j.iot.2025.101553","DOIUrl":"10.1016/j.iot.2025.101553","url":null,"abstract":"<div><div>The adoption of the Internet of Things (IoT) deployments has led to a sharp increase in network traffic as a vast number of IoT devices communicate with each other and with IoT services in the IoT–edge–cloud continuum. This increase in network traffic poses a major challenge to the global communications infrastructure since it hinders communication performance and also puts significant strain on the energy consumption of IoT devices. To address these issues, efficient and collaborative IoT solutions which enable information exchange while reducing the size of transmitted data and associated network traffic are crucial. This survey provides a comprehensive overview of the communication technologies and protocols as well as data reduction strategies that contribute to this goal. First, we present a comparative analysis of prevalent communication technologies in the IoT domain, highlighting their unique characteristics and exploring the potential for protocol composition and joint usage to enhance overall communication efficiency within the IoT–edge–cloud continuum. Next, we explore various data traffic reduction techniques tailored to the IoT–edge–cloud context and evaluate their applicability and effectiveness on resource-constrained end devices. Finally, we investigate the emerging concepts that have the potential to further reduce communication overhead in the IoT–edge–cloud continuum, including cross-layer optimization strategies and Edge AI techniques for IoT data reduction. The paper offers a comprehensive roadmap for developing efficient and scalable solutions across the layers of the IoT–edge–cloud continuum that are beneficial for real-time processing to alleviate network congestion in complex IoT environments.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101553"},"PeriodicalIF":6.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619383","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}

{"title":"Quantum-resistant hardware-accelerated IoT traffic encryptor","authors":"Peter Cíbik,&nbsp;Sara Ricci,&nbsp;Patrik Dobiáš,&nbsp;Jan Hajný,&nbsp;Lukáš Malina,&nbsp;Jan Havlín","doi":"10.1016/j.iot.2025.101554","DOIUrl":"10.1016/j.iot.2025.101554","url":null,"abstract":"<div><div>The rapid expansion of the Internet of Things (IoT) brings new security challenges, particularly with the potential risks posed by quantum computing. In this paper, we present a comprehensive approach to IoT security, offering two deployment options: a hardware-accelerated encryption solution using FPGAs for high-speed IoT aggregators, and a software-based version suited for lower-end IoT devices. Both versions share the same cryptographic architecture, ensuring consistency and compatibility across diverse use cases. Our proposed approach employs a hybrid key management mechanism that integrates classical, quantum, and post-quantum cryptographic schemes, including Elliptic Curve Diffie–Hellman (ECDH), CRYSTALS-Kyber, and Quantum Key Distribution (QKD). These key sources are combined using a custom-designed 3-key combiner to generate a secure hybrid key for AES-256 encryption in Galois-Counter Mode (GCM). Both solutions have been rigorously tested in real-world scenarios, including a pilot deployment between Czechia and Estonia and high-speed lab tests, validating their effectiveness and scalability. This dual approach caters to both resource-constrained edge devices and high-performance central systems, providing scalable and versatile post-quantum security for IoT environments.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101554"},"PeriodicalIF":6.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563496","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}

{"title":"Novel RSSI-Based localization in LoRaWAN using probability density estimation similarity-based techniques","authors":"Mauricio González-Palacio ,&nbsp;Mario Luna-delRisco ,&nbsp;John García-Giraldo ,&nbsp;Carlos Arrieta-González ,&nbsp;Liliana González-Palacio ,&nbsp;Christof Röhrig ,&nbsp;Long Bao Le","doi":"10.1016/j.iot.2025.101551","DOIUrl":"10.1016/j.iot.2025.101551","url":null,"abstract":"<div><div>In localization tasks of Internet of Things (IoT) End Nodes (ENs), the network lifetime and energy efficiency are critical. Due to power constraints, traditional systems like the Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), and Galileo may be unsuitable for IoT applications. As a result, Long-Range Wide Area Network (LoRaWAN) has gained attention due to its large coverage and low power requirements. Traditional localization strategies typically estimate the distance between the EN and Anchor Nodes (ANs) using the Received Signal Strength Indicator (RSSI) combined with a path loss model. However, the accuracy of such an approach can be compromised by different undesirable transmission effects, such as interference, affecting the RSSI. This work introduces a novel distance estimation method that leverages the similarity between Probability Density Functions (PDFs) of RSSI from measurement campaigns and those from deployed ENs. By employing metrics including the enhanced versions of Euclidean and Minkowski distances, the proposed approach surpasses conventional channel-based techniques, achieving a Mean Absolute Percentage Error (MAPE) of 3.9% for wireless environments with a shadowing standard deviation up to 16<!--> <!-->dB. Furthermore, when utilizing Kernel Density Estimation (KDE) for localization, the method demonstrated an 95.1% enhancement in accuracy compared to the localization strategy based on the loglinear path loss model.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101551"},"PeriodicalIF":6.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563304","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}

{"title":"HealthAIoT: AIoT-driven smart healthcare system for sustainable cloud computing environments","authors":"Han Wang ,&nbsp;Kumar Ankur Anurag ,&nbsp;Amira Rayane Benamer ,&nbsp;Priyansh Arora ,&nbsp;Gurleen Wander ,&nbsp;Mark R. Johnson ,&nbsp;Ranjit Mohan Anjana ,&nbsp;Viswanathan Mohan ,&nbsp;Sukhpal Singh Gill ,&nbsp;Steve Uhlig ,&nbsp;Rajkumar Buyya","doi":"10.1016/j.iot.2025.101555","DOIUrl":"10.1016/j.iot.2025.101555","url":null,"abstract":"<div><div>The evolution of Artificial Intelligence of Things (AIoT), coupled with advancements in edge and cloud computing, has enabled the development of real-time IoT-based applications. Integrating Internet of Things (IoT) and AI-driven edge–cloud services can address challenges such as early disease detection, system performance, data management and environmental sustainability in cloud-centric healthcare environments. To address these challenges, we propose <strong>HealthAIoT</strong>, a new architecture that utilises AIoT with cloud computing services to create a smart healthcare system. In our current implementation, HealthAIoT assesses the risk of developing diabetes mellitus in healthy individuals based on their personal health metrics and medical history; however, the proposed framework is fundamentally designed to be disease-agnostic and can be extended to incorporate detection and monitoring for other diseases. The HealthAIoT architecture consists of two main modules: a diabetes predictor and a cloud scheduler. The diabetes prediction module and cloud scheduler both utilise Multilayer Perceptron (MLP) models. The cloud scheduler manages health-related data and application requests from IoT devices, optimising resource utilisation and minimising the environmental impact of cloud services. The performance of the HealthAIoT framework is tested using the realistic testbed CloudAIBus. Experimental results demonstrate that the MLP-based diabetes predictor achieves 78.30% accuracy and an F1-score of 0.7719 on unseen patient data while cloud scheduler achieves 93.6% accuracy. Further, system performance is evaluated using metrics including energy consumption, carbon-free energy usage, cost, execution time, and latency. By identifying individuals at the highest risk of developing diabetes, the framework enables targeted preventative interventions, optimises resource usage and maximises impact, while also serving as a foundational framework for broader healthcare applications.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101555"},"PeriodicalIF":6.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619382","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}

{"title":"Towards privacy-preserving split learning: Destabilizing adversarial inference and reconstruction attacks in the cloud","authors":"Griffin Higgins ,&nbsp;Roozbeh Razavi-Far ,&nbsp;Xichen Zhang ,&nbsp;Amir David ,&nbsp;Ali Ghorbani ,&nbsp;Tongyu Ge","doi":"10.1016/j.iot.2025.101558","DOIUrl":"10.1016/j.iot.2025.101558","url":null,"abstract":"<div><div>This work aims to provide both privacy and utility within a split learning framework while considering both forward attribute inference and backward reconstruction attacks. To address this, a novel approach has been proposed, which makes use of class activation maps and autoencoders as a plug-in strategy aiming to increase the user’s privacy and destabilize an adversary. The proposed approach is compared with a dimensionality-reduction-based plug-in strategy, which makes use of principal component analysis to transform the feature map onto a lower-dimensional feature space. Our work shows that our proposed autoencoder-based approach is preferred as it can provide protection at an earlier split position over the tested architectures in our setting, and, hence, better utility for resource-constrained devices in edge–cloud collaborative inference (<span><math><mi>EC</mi></math></span>) systems.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101558"},"PeriodicalIF":6.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563305","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}

{"title":"A secure image encryption mechanism using biased Fourier quantum walk and addition-crossover structure in the Internet of Things","authors":"Hesheng Huang,&nbsp;Zhenhao Liu,&nbsp;Zhiyuan Wang,&nbsp;Fei Yan","doi":"10.1016/j.iot.2025.101559","DOIUrl":"10.1016/j.iot.2025.101559","url":null,"abstract":"<div><div>The emergence of the fifth-generation network technology, along with ongoing advancements in the Internet of Things (IoT), has stimulated the substantial transformation of production methods and traditional industries to greatly enrich the quality of daily life. However, the vast amounts of data generated by IoT devices often include sensitive personal information, posing risks of hacking, theft, and misuse. In this study, a secure image encryption mechanism is proposed using the biased Fourier quantum walk and addition-crossover structure to ensure the confidentiality of private data in IoT applications. The originality of this study resides in the innovative implementation of ensuing modules to enhance the security and robustness of the mechanism. First, we introduce a two-dimensional discrete biased Fourier quantum walk to design a pseudo-random number generator that produces highly random and sensitive secret keys. Additionally, we develop an addition-crossover structure to create a novel permutation strategy for shuffling the pixel positions of the plain image. To further strengthen the security of the disordered image, we establish a dynamic DNA shift encoding as a diffusion technique to complete the image encryption. A series of experiments was conducted to validate the performance of the proposed encryption mechanism in terms of security and attack resistance. The results confirm that our scheme is reliable and offers distinct advantages over existing quantum-based and other leading encryption methods.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101559"},"PeriodicalIF":6.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563306","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}

{"title":"CONCERN: A model-based monitoring infrastructure","authors":"Antonello Calabrò ,&nbsp;Eda Marchetti ,&nbsp;Paweł Skrzypek ,&nbsp;Jan Marchel","doi":"10.1016/j.iot.2025.101557","DOIUrl":"10.1016/j.iot.2025.101557","url":null,"abstract":"<div><div>Characteristics such as quality, trustworthiness, and cybersecurity are becoming essential in the ecosystems of Internet of Things (IoT) systems. Although significant efforts in industry and academia have been made to create solutions that ensure, monitor, and evaluate these attributes throughout the development process, time-to-market urgency, demands for higher productivity, and competitive pressures often result in faster release schedules. This situation calls for methods and means to quickly and accurately identify and avert anomalies and hazardous circumstances. Among them, a monitoring system is an effective solution for evaluating functional and non-functional attributes during the online execution. This paper proposes an integrated Runtime Monitoring solution called CONCERN (COmplex eveNt proCEssing monitoR iNfrastructure) for guaranteeing a consistent quality of services, managing the possible execution exceptions and interruptions, and providing a high system availability. The paper describes the CONCERN supporting architecture and proof-of-concept implementation of its components, validation of the CONCERN usability, and its performance in a real scenario taken from the financial domain. Finally, the paper reports the discussion, lessons learned, and the future work suggested by the showcase.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"31 ","pages":"Article 101557"},"PeriodicalIF":6.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563303","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}