Jaekyung Lee^1,2, Youngjun Kim², Byungsung Ko², Taewon Kim², Jaeheon Park², Jiwon Lee², Wonhee Kim^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080624 - 27 April 2026

Abstract Automated reading of analog gauges in industrial environments is essential for predictive maintenance and safety monitoring. However, conventional computer vision approaches encounter two fundamental bottlenecks: polar unwrapping techniques induce severe nonlinear scaling distortions under oblique viewing angles and axis-aligned bounding boxes (AABBs) are geometrically inefficient for encapsulating high-aspect-ratio rotating needles. To overcome these limitations, this paper proposes a novel end-to-end framework that innovatively redefines gauge reading as a structural pose estimation task. We model each gauge as a topological five-keypoint skeleton (kstart,kmid,kcenter,kend,ktip), and localize these landmarks using a customized P2-YOLO-Pose architecture. By integrating a high-resolution… More >

Safaa Zaman¹, Marwa M. Eid^2,*, Ebrahim A. Mattar³, Doaa Sami Khafaga⁴, El-Sayed M. El-Kenawy^5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079827 - 27 April 2026

Abstract The rapid growth of Internet of Things (IoT) technologies has transformed modern urban environments into complex smart cities, generating vast amounts of high-dimensional, heterogeneous data. Effectively analyzing this data is crucial for optimizing urban infrastructure, enhancing quality of life, and supporting sustainable development. However, smart city data presents significant challenges, including non-linear dependencies, noisy signals, and high dimensionality. To address these challenges, this study proposes the Dynamic Leader Sibha Algorithm (DLSA), a novel metaheuristic optimization technique inspired by the structured counting dynamics of the Sibha. The DLSA was applied to the Smart Cities Index dataset,… More >

Hongjiang Wang¹, Jian Yu², Tian Zhang³, Na Ren⁴, Nan Zhang², Zhenyu Liu^1,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077997 - 09 April 2026

Abstract The rapid deployment of Industrial Internet of Things (IIoT) systems, such as large-scale photovoltaic (PV) power stations in modern power grids, has created a strong demand for edge-intelligent fault localization methods that can operate reliably under strict computational and memory constraints. In this work, we propose an edge-intelligent photovoltaic fault localization framework that integrates intelligent computation with classical sub-pixel optimization. The framework adopts a modular, edge-oriented design in which a radial basis function (RBF) network is first employed as a lightweight screening module to enable conditional execution, thereby reducing unnecessary computation for non-faulty samples. For… More >

Pratik Goswami^1,#, Hamid Naseem^2,#, Khizar Abbas^3,*, Kwonhue Choi^1,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077012 - 09 April 2026

Abstract In a distributed edge computing environment, Internet of Things (IoT) and Vehicular-IoT (V-IoT) devices communicate through Wireless Sensor Networks (WSNs) by collecting and transmitting data from different environments. Although energy efficiency is always a critical challenge in WSN due to limited battery power, along with the demand for fast communication over edge devices in 5G and beyond 5G scenarios. Therefore, to overcome the challenges, an advanced hierarchical agent-based power management scheme is proposed for WSNs that optimizes energy distribution while maintaining reliable communication. The proposed model employs Master Agents (MAs), Coordination Agents (CoAs), and Task More >

Chung-Wei Kuo^1,2,*, Cheng-Xuan Wu¹

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076767 - 09 April 2026

Abstract The rapid proliferation of the Internet of Things (IoT) has not only reshaped the digital ecosystem but also significantly widened the attack surface, leading to a surge in network traffic and diverse security threats. Deploying effective defense mechanisms in such environments is challenging, as conventional Intrusion Detection Systems (IDS) often struggle to balance computational efficiency with the reliable detection of low-frequency, high-impact threats, particularly within the tight resource constraints of edge devices. To address these limitations, we propose a lightweight, high-efficiency IDS framework specifically optimized for edge-based IoT applications, incorporating Mutual Information (MI)-based feature selection… More >

Wael A. Altabey^*

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.073949 - 31 March 2026

Abstract The study of long-term pavement performance is a fundamental topic in the field of highway engineering. Through comprehensive and in-depth research on the pavement system, the previous scattered, one-sided, superficial, and perceptual knowledge and experience are summarized and sublimated into a systematic and complete engineering theory, thereby providing powerful guidance and assistance for the practice of pavement design, construction, maintenance, operation, and management. In this research, the mentoring system deployment technology for automatic monitoring is carried out for long-term pavement performance. By burying a variety of sensors in different parts of the road surface, base,… More >

Suman Sukhavasi, Thinagaran Perumal^*, Norwati Mustapha, Razali Yaakob

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075613 - 12 March 2026

Abstract The Internet of Things (IoT) ecosystem is inherently heterogeneous, comprising diverse devices that must interoperate seamlessly to enable federated message and data exchange. However, as the number of service requests grows, existing approaches suffer from increased discovery time and degraded Quality of Service (QoS). Moreover, the massive data generated by heterogeneous IoT devices often contain redundancy and noise, posing challenges to efficient data management. To address these issues, this paper proposes a lightweight ontology-based architecture that enhances service discovery and QoS-aware semantic data management. The architecture employs Modified-Ordered Points to Identify the Clustering Structure (M-OPTICS)… More >

Dina S. M. Hassan^*, Reem Ibrahim Alkanhel, Thuraya Alrumaih, Shiyam Alalmaei

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.074751 - 12 March 2026

Abstract The sustainability of the Internet of Things (IoT) involves various issues, such as poor connectivity, scalability problems, interoperability issues, and energy inefficiency. Although the Sixth Generation of mobile networks (6G) allows for Ultra-Reliable Low-Latency Communication (URLLC), enhanced Mobile Broadband (eMBB), and massive Machine-Type Communications (mMTC) services, it faces deployment challenges such as the short range of sub-THz and THz frequency bands, low capability to penetrate obstacles, and very high path loss. This paper presents a network architecture to enhance the connectivity of wireless IoT mesh networks that employ both 6G and Wi-Fi technologies. In this… More >

Qingwen Yang¹, Zhi Li², Jiawei Tang¹, Yanyi Liu¹, Tiezheng Guo¹, Yingyou Wen^1,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2025.074384 - 12 March 2026

Abstract Deploying Large Language Model (LLM)-based agents in the Industrial Internet of Things (IIoT) presents significant challenges, including high latency from cloud-based APIs, data privacy concerns, and the infeasibility of deploying monolithic models on resource-constrained edge devices. While smaller models (SLMs) are suitable for edge deployment, they often lack the reasoning power for complex, multi-step tasks. To address these issues, this paper introduces LEAF, a Lightweight Edge Agent Framework designed for efficiently executing complex tasks at the edge. LEAF employs a novel architecture where multiple expert SLMs—specialized for planning, execution, and interaction—work in concert, decomposing complex… More >

Wajdan Al Malwi¹, Fatima Asiri¹, Nazik Alturki², Noha Alnazzawi³, Dimitrios Kasimatis⁴, Nikolaos Pitropakis^5,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.074274 - 12 March 2026

Abstract The expansion of 5G-enabled Internet of Things (IoT) networks, while enabling transformative applications, significantly increases the attack surface and necessitates security solutions that extend beyond traditional intrusion detection. Existing intrusion detection systems (IDSs) mainly operate in an open-loop manner, excelling at classification but lacking the ability for autonomous, safety-aware remediation. This gap is particularly critical in 5G environments, where manual intervention is too slow and naive automation can lead to severe service disruptions. To address this issue, we propose a novel Self-Healing Intrusion Detection System (SH-IDS) framework that develops a closed-loop cyber defense mechanism. The… More >