Qingmin Hou¹, Guanghua Xiao¹, Tongtong Dai^2,*

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.087157 - 24 August 2026

Abstract To address the issue of angular deviation in inclined single-axis photovoltaic tracking mounts during long-term operation-caused by wind disturbances, mechanical transmission gaps, installation inaccuracies, and environmental factors-a angle sensor based on reflective fiber-optic ranging principles has been developed for monitoring the rotation angle of the main shaft. This sensor employs a structural conversion approach of “using straight lines to replace curves”, transforming the shaft’s rotational angle into linear displacement of a mirror via a gear-rack mechanism, and generating corresponding output voltage signals through variations in reflected light intensity to measure rotation angles. Due to factors… More >

Yongning Zhang¹, Dongxue Li^1,2,*, Cen Yang³, Yongwang Gui⁴

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.081767 - 24 August 2026

Abstract To address the challenge that the baseline state of FE models for operational highly statically indeterminate bridges is difficult to evaluate accurately, this paper proposes an intelligent multi-parameter inversion and updating framework driven by measured dynamic strains and a LSTM neural network. First, to tackle the complex environmental interferences coupled within short-term monitoring strain signals, a moving-window baseline detrending and refined thermal effect decoupling algorithm is employed. This successfully strips away long-term dead loads and temperature drift, extracting pure mechanical strain sequences with a high signal-to-noise ratio. Second, to overcome the mode omission issue caused… More >

Caiping Huang^*, Yulong Mei, Wangyuan Tian, Zihang Yu

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.073282 - 24 August 2026

Abstract Bridge damage detection is critical to bridge maintenance practices. However, traditional inspection methods are plagued by high labour intensity and low operational efficiency. To enhance the intelligence, objectivity, and efficiency of bridge damage detection, this study proposes an automated approach for the identification and quantitative measurement of concrete defects. Specifically, this method adopts the Visual Geometry Group (VGG) network as the backbone of the U-Net architecture to perform semantic segmentation on images containing typical concrete defects, including spalling, cracks, and exposed reinforcement bars. Subsequently, mathematical morphology algorithms are employed to optimise the segmented images, thereby… More >

Shounak Mandal¹, Subhadip Pati^1,#, Nirmallyadeb Ray^1,#, Bipasha Guha Roy^2,#, Priyanka Saha³, Deepsubhra Guha Roy^2,*

Digital Engineering and Digital Twin, Vol.4, pp. 27-47, 2026, DOI:10.32604/dedt.2026.081859 - 14 August 2026

Abstract HealthyBrain is a scalable, interoperable, and intelligent Remote Patient Monitoring (RPM) platform built on Internet of Things (IoT) technologies and a modular microservices architecture. The system integrates wearable IoT devices, MQTT (Message Queuing Telemetry Transport)-based lightweight messaging, and high-throughput real-time data streaming via Apache Kafka. Edge-side preprocessing enables low-latency analytics, while machine learning-based anomaly detection models facilitate early identification of critical health events. To ensure clinical interoperability, the platform adheres to the HL7 FHIR (Fast Healthcare Interoperability Resources) standard for electronic health record exchange. The system’s novel contribution lies in the unified integration of edge… More >

Hyunbum Kim^*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.085773 - 13 August 2026

Abstract Recently, unmanned aerial vehicles (UAVs), or drones, have attracted considerable research interest across diverse fields, encompassing public and private domains, industrial and academic fields, transportation areas, disaster and harsh environments, reliable delivery services, digital twin-enabled space, and smart cities. In particular, UAVs play a critical role in surveillance and security applications. In this paper, we investigate recent advances in surveillance and intelligent security applications using UAVs. This study covers a wide range of practical tasks and missions including intelligent traffic monitoring, disaster environments, forests and national parks, large-scale events and patrols in public circumstances. Also, More >

Jinlin Chen^1,2, Yiquan Wu^1,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.085761 - 13 August 2026

Abstract Accurate waterline detection is critical for automated ship draft monitoring but remains challenging due to weak textures, low contrast, and dynamic maritime interferences. This paper presents TGNet, a task-guided framework that jointly optimizes character recognition and waterline keypoint localization. TGNet introduces a triple attention network (TAnet) with channel, spatial, and texture attention modules to enhance discriminative feature extraction. Crucially, a task-to-task guidance mechanism leverages detected draft characters to spatially constrain and crop feature maps, focusing the keypoint detection head on the most relevant waterline region. Extensive experiments on three large-scale aerial datasets show that TAnet More >

Zulfiqar Ali, Azhar Mahmood^*, Shaheen Khatoon, Seyed Ali Ghorashi

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084386 - 13 August 2026

Abstract Smart city systems increasingly depend on data analytics and visualization to support informed and timely decision making in complex urban environments. However, existing middleware solutions predominantly focus on data acquisition and communication, while analytical processing and visualization are typically delegated to external applications, resulting in increased development complexity, reduced reusability, and fragmented system architectures. This study presents analytics and visualization-centric middleware named “Service-Oriented Middleware for Smart City Applications” (SOMSCA), in which these capabilities are embedded directly within the middleware layer. SOMSCA adopts a service-oriented approach, exposing analytics and visualization functionalities as reusable platform services, and… More >

Kiran Saleem¹, Upinder Kaur^2,*, Abdulrahman Mohammed Alamoudi³, Mai Alduailij⁴, Ahmad Subhi Salem Mufleh⁵, Ateeq Ur Rehman^6,*, Salil Bharany⁷

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.083670 - 13 August 2026

Abstract Underwater Wireless Sensor Networks (UWSNs) are exceedingly critical for large-scale underwater applications, such as environmental monitoring, infrastructure inspection, target tracking, and marine surveillance. Nevertheless, network lifetime and communication reliability are severely constrained by harsh underwater acoustic conditions, limited battery power, large propagation delays, node mobility, and uneven energy consumption. In response to these issues, this study proposes a Climate-Aware Hybrid Clustering and Routing (CA-HCR-UWSN) framework to enable sustainable, long-term underwater monitoring. This work proposes a hybrid framework that combines Elephant Herding Optimization (EHO) with the Gravitational Search Algorithm (GSA) to provide an effective solution to… More >

Aigerim Altayeva^1,*, Nurzhan Omarov²

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.080878 - 13 August 2026

Abstract Hazardous impulsive sound detection plays a critical role in intelligent surveillance, public safety monitoring, and automated emergency response systems. This study proposes a lightweight channel-attention-enhanced deep learning architecture for real-time detection and classification of hazardous acoustic events. The proposed framework utilizes mel-spectrogram representations to capture time-frequency characteristics of audio signals and employs a compact convolutional neural backbone to efficiently extract hierarchical features. To enhance feature discrimination, a squeeze-and-excitation channel-attention mechanism is integrated into the architecture, enabling adaptive recalibration of feature channels and improved robustness under noisy and complex acoustic environments. A custom dataset consisting of More >

Kui Hu, Peng Zhang^*, Xiang Xiao, Yuan Xu, Yunhuang Zhang, Yuan Yuan, Zhiyuan Feng

Energy Engineering, Vol.123, No.9, 2026, DOI:10.32604/ee.2026.078340 - 06 August 2026

Abstract The rapid development of gas-cooled microreactors (GMRs) for remote and modular power supply necessitates highly efficient and autonomous core power monitoring systems. Traditional monitoring systems, such as those deployed in commercial power plants, rely on dense in-core instrumentation, whereas due to the limitation of space and simplicity in hardware designs, only sparse ex-core detectors are employed in microreactor designs. To address this challenge, this study proposes an advanced online power reconstruction approach based on the higher-order harmonic expansion. A dedicated higher-order harmonic calculation module was developed within a multi-group diffusion framework, capable of executing rapid… More >