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  • Open Access

    ARTICLE

    Energy Optimization for Autonomous Mobile Robot Path Planning Based on Deep Reinforcement Learning

    Longfei Gao*, Weidong Wang, Dieyun Ke

    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-15, 2026, DOI:10.32604/cmc.2025.068873 - 10 November 2025

    Abstract At present, energy consumption is one of the main bottlenecks in autonomous mobile robot development. To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments, this paper proposes an Attention-Enhanced Dueling Deep Q-Network (AD-Dueling DQN), which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework. A multi-objective reward function, centered on energy efficiency, is designed to comprehensively consider path length, terrain slope, motion smoothness, and obstacle avoidance, enabling optimal low-energy trajectory generation in 3D space from the… More >

  • Open Access

    REVIEW

    AI-Powered Digital Twin Frameworks for Smart Grid Optimization and Real-Time Energy Management in Smart Buildings: A Survey

    Saeed Asadi1, Hajar Kazemi Naeini1, Delaram Hassanlou2, Abolhassan Pishahang3, Saeid Aghasoleymani Najafabadi4, Abbas Sharifi5, Mohsen Ahmadi6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1259-1301, 2025, DOI:10.32604/cmes.2025.070528 - 26 November 2025

    Abstract The growing energy demand of buildings, driven by rapid urbanization, poses significant challenges for sustainable urban development. As buildings account for over 40% of global energy consumption, innovative solutions are needed to improve efficiency, resilience, and environmental performance. This paper reviews the integration of Digital Twin (DT) technologies and Machine Learning (ML) for optimizing energy management in smart buildings connected to smart grids. A key enabler of this integration is the Internet of Things (IoT), which provides the sensor networks and real-time data streams that fee/d DT–ML frameworks, enabling accurate monitoring, forecasting, and adaptive control.… More >

  • Open Access

    ARTICLE

    Energy Optimization Strategy for Reconfigurable Distribution Network with High Renewable Penetration Based on Bald Eagle Search Algorithm

    Jian Wang, Hui Qi, Lingyi Ji*, Zhengya Tang, Hui Qian

    Energy Engineering, Vol.122, No.11, pp. 4635-4651, 2025, DOI:10.32604/ee.2025.068667 - 27 October 2025

    Abstract This paper proposes a cost-optimal energy management strategy for reconfigurable distribution networks with high penetration of renewable generation. The proposed strategy accounts for renewable generation costs, maintenance and operating expenses of energy storage systems, diesel generator operational costs, typical daily load profiles, and power balance constraints. A penalty term for power backflow is incorporated into the objective function to discourage undesirable reverse flows. The Bald Eagle Search (BES) meta-heuristic is adopted to solve the resulting constrained optimization problem. Numerical simulations under multiple load scenarios demonstrate that the proposed method effectively reduces operating cost while preventing More >

  • Open Access

    ARTICLE

    An Energy Optimization Algorithm for WRSN Nodes Based on Regional Partitioning and Inter-Layer Routing

    Cui Zhang1, Lieping Zhang2,*, Huaquan Gan3, Hongyuan Chen3, Zhihao Li3

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3125-3148, 2025, DOI:10.32604/cmc.2025.064499 - 03 July 2025

    Abstract In large-scale Wireless Rechargeable Sensor Networks (WRSN), traditional forward routing mechanisms often lead to reduced energy efficiency. To address this issue, this paper proposes a WRSN node energy optimization algorithm based on regional partitioning and inter-layer routing. The algorithm employs a dynamic clustering radius method and the K-means clustering algorithm to dynamically partition the WRSN area. Then, the cluster head nodes in the outermost layer select an appropriate layer from the next relay routing region and designate it as the relay layer for data transmission. Relay nodes are selected layer by layer, starting from the… More >

  • Open Access

    ARTICLE

    An Enhanced Fuzzy Routing Protocol for Energy Optimization in the Underwater Wireless Sensor Networks

    Mehran Tarif1, Mohammadhossein Homaei2,*, Amir Mosavi3,4,5

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1791-1820, 2025, DOI:10.32604/cmc.2025.063962 - 16 April 2025

    Abstract Underwater Wireless Sensor Networks (UWSNs) are gaining popularity because of their potential uses in oceanography, seismic activity monitoring, environmental preservation, and underwater mapping. Yet, these networks are faced with challenges such as self-interference, long propagation delays, limited bandwidth, and changing network topologies. These challenges are coped with by designing advanced routing protocols. In this work, we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks (UWF-RPL), an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes. Our method extends RPL with the aid of fuzzy logic More >

  • Open Access

    ARTICLE

    A Fuzzy Multi-Objective Framework for Energy Optimization and Reliable Routing in Wireless Sensor Networks via Particle Swarm Optimization

    Medhat A. Tawfeek1,*, Ibrahim Alrashdi1, Madallah Alruwaili2, Fatma M. Talaat3,4

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2773-2792, 2025, DOI:10.32604/cmc.2025.061773 - 16 April 2025

    Abstract Wireless Sensor Networks (WSNs) are one of the best technologies of the 21st century and have seen tremendous growth over the past decade. Much work has been put into its development in various aspects such as architectural attention, routing protocols, location exploration, time exploration, etc. This research aims to optimize routing protocols and address the challenges arising from conflicting objectives in WSN environments, such as balancing energy consumption, ensuring routing reliability, distributing network load, and selecting the shortest path. Many optimization techniques have shown success in achieving one or two objectives but struggle to achieve… More >

  • Open Access

    ARTICLE

    A Tolerant and Energy Optimization Approach for Internet of Things to Enhance the QoS Using Adaptive Blended Marine Predators Algorithm

    Vijaya Krishna Akula1,*, Tan Kuan Tak2, Pravin Ramdas Kshirsagar3, Shrikant Vijayrao Sonekar4, Gopichand Ginnela5

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2449-2479, 2025, DOI:10.32604/cmc.2025.061486 - 16 April 2025

    Abstract The rapid expansion of Internet of Things (IoT) networks has introduced challenges in network management, primarily in maintaining energy efficiency and robust connectivity across an increasing array of devices. This paper introduces the Adaptive Blended Marine Predators Algorithm (AB-MPA), a novel optimization technique designed to enhance Quality of Service (QoS) in IoT systems by dynamically optimizing network configurations for improved energy efficiency and stability. Our results represent significant improvements in network performance metrics such as energy consumption, throughput, and operational stability, indicating that AB-MPA effectively addresses the pressing needs of modern IoT environments. Nodes are More >

  • Open Access

    ARTICLE

    AI-Driven Energy Optimization in UAV-Assisted Routing for Enhanced Wireless Sensor Networks Performance

    Syed Kamran Haider1,2, Abbas Ahmed2, Noman Mujeeb Khan2, Ali Nauman3,*, Sung Won Kim3,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4085-4110, 2024, DOI:10.32604/cmc.2024.052997 - 12 September 2024

    Abstract In recent advancements within wireless sensor networks (WSN), the deployment of unmanned aerial vehicles (UAVs) has emerged as a groundbreaking strategy for enhancing routing efficiency and overall network functionality. This research introduces a sophisticated framework, driven by computational intelligence, that merges clustering techniques with UAV mobility to refine routing strategies in WSNs. The proposed approach divides the sensor field into distinct sectors and implements a novel weighting system for the selection of cluster heads (CHs). This system is primarily aimed at reducing energy consumption through meticulously planned routing and path determination. Employing a greedy algorithm More >

  • Open Access

    ARTICLE

    A Novel Approach to Energy Optimization: Efficient Path Selection in Wireless Sensor Networks with Hybrid ANN

    Muhammad Salman Qamar1,*, Ihsan ul Haq1, Amil Daraz2, Atif M. Alamri3, Salman A. AlQahtani4, Muhammad Fahad Munir1

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2945-2970, 2024, DOI:10.32604/cmc.2024.050168 - 15 May 2024

    Abstract In pursuit of enhancing the Wireless Sensor Networks (WSNs) energy efficiency and operational lifespan, this paper delves into the domain of energy-efficient routing protocols. In WSNs, the limited energy resources of Sensor Nodes (SNs) are a big challenge for ensuring their efficient and reliable operation. WSN data gathering involves the utilization of a mobile sink (MS) to mitigate the energy consumption problem through periodic network traversal. The mobile sink (MS) strategy minimizes energy consumption and latency by visiting the fewest nodes or pre-determined locations called rendezvous points (RPs) instead of all cluster heads (CHs). CHs… More >

  • Open Access

    ARTICLE

    Regional Renewable Energy Optimization Based on Economic Benefits and Carbon Emissions

    Cun Wei1, Yunpeng Zhao2,*, Mingyang Cong1, Zhigang Zhou1,*, Jingzan Yan3, Ruixin Wang1, Zhuoyang Li1, Jing Liu1

    Energy Engineering, Vol.120, No.6, pp. 1465-1484, 2023, DOI:10.32604/ee.2023.026337 - 03 April 2023

    Abstract With increasing renewable energy utilization, the industry needs an accurate tool to select and size renewable energy equipment and evaluate the corresponding renewable energy plans. This study aims to bring new insights into sustainable and energy-efficient urban planning by developing a practical method for optimizing the production of renewable energy and carbon emission in urban areas. First, we provide a detailed formulation to calculate the renewable energy demand based on total energy demand. Second, we construct a dual-objective optimization model that represents the life cycle cost and carbon emission of renewable energy systems, after which More >

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