Zeeshan Ali Haider¹, Inam Ullah^2,*, Ahmad Abu Shareha³, Rashid Nasimov⁴, Sufyan Ali Memon^5,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.071042 - 10 November 2025

Abstract The advent of sixth-generation (6G) networks introduces unprecedented challenges in achieving seamless connectivity, ultra-low latency, and efficient resource management in highly dynamic environments. Although fifth-generation (5G) networks transformed mobile broadband and machine-type communications at massive scales, their properties of scaling, interference management, and latency remain a limitation in dense high mobility settings. To overcome these limitations, artificial intelligence (AI) and unmanned aerial vehicles (UAVs) have emerged as potential solutions to develop versatile, dynamic, and energy-efficient communication systems. The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning (CoRL) to manage an autonomous network.… More >

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 >

Chirag Devendrakumar Parikh^*

Journal on Artificial Intelligence, Vol.7, pp. 571-584, 2025, DOI:10.32604/jai.2025.073765 - 01 December 2025

Abstract With the increasing complexity and scale of hyperscale data centers, the requirement for intelligent, real-time power delivery has never been more critical to ensure uptime, energy efficiency, and sustainability. Those techniques are typically static, reactive (since CPU and workload scaling is applied to performance events that occur after a request has been submitted, and is thus can be classified as a reactive response.), and require manual operation, and cannot cope with the dynamic nature of the workloads, the distributed architectures as well as the non-uniform energy sources in today’s data centers. In this paper, we… More >

Ratan Kumar Das^1,*, Abhijit Date¹, Harun Chowdhury¹, Hamed Hassan²

Energy Engineering, Vol.122, No.12, pp. 4815-4835, 2025, DOI:10.32604/ee.2025.071727 - 27 November 2025

Abstract Bangladesh has achieved notable progress in expanding electricity access nationwide. Nonetheless, remote and topographically challenging regions such as the Chittagong Hill Tracts (CHT) continue to face coverage gaps due to grid extension difficulties. This research investigates the technical feasibility of micro-hydro power (MHP) systems as viable off-grid solutions for rural electrification in CHT. Field surveys conducted across various sites assessed available head and flow rates using GPS-based elevation measurements and portable flow meters. Seasonal fluctuations were factored into the analysis to ensure year-round operational viability. The study involved estimating power output, selecting appropriate turbine types… More > Graphic Abstract

S. Srinivasa senthil, K. Vijayakumar^*

Energy Engineering, Vol.122, No.12, pp. 5149-5173, 2025, DOI:10.32604/ee.2025.070889 - 27 November 2025

Abstract Heating, ventilation, and air conditioning (HVAC) systems contribute substantially to global energy consumption, while rejecting significant amounts of low-grade heat into the environment. This paper presents a non-intrusive spiral-coil heat exchanger designed to recover waste heat from the outdoor condenser of a split-type air conditioner. The system operates externally without altering the existing HVAC configuration, thereby rendering it suitable for retrofitting. Water was circulated as the working fluid at flow rates of 0.028–0.052 kg/s to assess thermal performance. Performance indicators, including the outlet water temperature, heat transfer rate, convective coefficient, and efficiency, were systematically evaluated.… More >

Rebhi M’hamed^1,*, Himri Youcef^2,3,*, Bouchiba Bousmaha¹, Yaichi Mouaadh¹

Energy Engineering, Vol.122, No.12, pp. 4899-4918, 2025, DOI:10.32604/ee.2025.070806 - 27 November 2025

Abstract Currently, most conventional street lighting systems use a constant light mode throughout the entire night, from sunset to sunrise, which results in high energy consumption and maintenance costs. Furthermore, scientific research predicts that energy consumption for street lighting will increase in the coming years due to growing demand and rising electricity prices. The dimming strategy is a current trend and a key concept in smart street lighting systems. It involves turning on the road lights only when a vehicle or pedestrian is detected; otherwise, the control system reduces the light intensity of the lamps. Power… More >

Hao Yue¹, Di Gao², Jin Gao¹, Chengmei Wei¹, Jiali Duan³, Shaocheng Mei^3,*

Energy Engineering, Vol.122, No.12, pp. 5091-5109, 2025, DOI:10.32604/ee.2025.069140 - 27 November 2025

Abstract Against the backdrop of regional coordinated development and China’s “dual carbon” strategic objectives, the Beijing-Tianjin-Hebei (BTH) region faces an urgent need to transition from its traditional economic growth model, which is heavily reliant on resource consumption. This study investigates the decoupling dynamics among economic growth, energy consumption, and carbon emissions in the BTH region, along with the underlying driving forces, aiming to provide valuable insights for achieving the “dual carbon” targets and fostering high-quality regional development. First, the Tapio decoupling model is employed to analyze the decoupling relationships between economic growth, energy consumption, and carbon… More >

Jian Wang¹, Hui Qi¹, Feilong Jiang^2,*, Biao Jiang³, Tiankui Sun⁴, Lingyi Ji¹, Yajun Zhao², Feifei Bu²

Energy Engineering, Vol.122, No.12, pp. 4873-4897, 2025, DOI:10.32604/ee.2025.069071 - 27 November 2025

Abstract To enhance power supply reliability and reduce customer outage time, Mobile Emergency Power Supply Vehicles (MEPSVs), including Mobile Diesel Generator Vehicles (MDGVs) and Mobile Energy Storage Vehicles (MESVs), have become indispensable sources for grid maintenance and disaster response. However, in practice, relying solely on MESVs is constrained by battery capacity, making it difficult to meet long-duration power demands. Conversely, using only MDGVs often results in low efficiency and high fuel consumption under fluctuating load conditions, posing challenges to achieving economical and efficient power supply. To address these issues, this paper investigates the parallel power supply… More >

Baiyue Song¹, Chenxi Zhang², Wei Zhang^2,*, Leiyu Wan²

Energy Engineering, Vol.122, No.12, pp. 4919-4945, 2025, DOI:10.32604/ee.2025.068971 - 27 November 2025

Abstract Hydrogen energy is a crucial support for China’s low-carbon energy transition. With the large-scale integration of renewable energy, the combination of hydrogen and integrated energy systems has become one of the most promising directions of development. This paper proposes an optimized scheduling model for a hydrogen-coupled electro-heat-gas integrated energy system (HCEHG-IES) using generative adversarial imitation learning (GAIL). The model aims to enhance renewable-energy absorption, reduce carbon emissions, and improve grid-regulation flexibility. First, the optimal scheduling problem of HCEHG-IES under uncertainty is modeled as a Markov decision process (MDP). To overcome the limitations of conventional deep… More >

Mekhled Alharbi^1,*, Khalid Haseeb², Mamoona Humayun^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2601-2616, 2025, DOI:10.32604/cmes.2025.073039 - 26 November 2025

Abstract Emerging technologies and the Internet of Things (IoT) are integrating for the growth and development of heterogeneous networks. These systems are providing real-time devices to end users to deliver dynamic services and improve human lives. Most existing approaches have been proposed to improve energy efficiency and ensure reliable routing; however, trustworthiness and network scalability remain significant research challenges. In this research work, we introduce an AI-enabled Software-Defined Network (SDN)- driven framework to provide secure communication, trusted behavior, and effective route maintenance. By considering multiple parameters in the forwarder selection process, the proposed framework enhances network More >