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Artificial Intelligence (AI)-Enabled Unmanned Aerial Vehicle (UAV) Systems for Optimizing User Connectivity in Sixth-Generation (6G) Ubiquitous Networks 认领 引用 被引量：1
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作者 Zeeshan Ali Haider Inam Ullah +2 位作者 Ahmad Abu Shareha Rashid Nasimov Sufyan Ali Memon 《Computers, Materials & Continua》 SCIE EI 2026年第1期534-549,共16页
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-gener... 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.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment. 展开更多
关键词 6G networks UAV-based communication cooperative reinforcement learning network optimization user connectivity energy efficiency
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Criticality and fragility in a quantum neural memory 认领 引用
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作者 Inam Ullah Subhanullah Khan +1 位作者 Muhammad Noman Minglin Lang 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第5期315-325,共11页
We theoretically investigate a neural transverse-field Hopfield(NTFH)model that realizes a minimal quantum neural memory by encoding patterns in the low-energy spectrum and stationary correlations of coupled qubits.At... We theoretically investigate a neural transverse-field Hopfield(NTFH)model that realizes a minimal quantum neural memory by encoding patterns in the low-energy spectrum and stationary correlations of coupled qubits.At the level of a two-neuron open quantum system,we analyze how entanglement of formation,geometric quantum discord and quantum-memory-assisted entropic uncertainty evolve under the combined action of memory interactions,transverse fields,local imperfections and Markovian dephasing.This reveals a robust trade-off:transverse driving enhances coherent processing but destabilizes stored patterns,while local asymmetries and noise rapidly erase quantum correlations.Extending the model to a four-neuron network,we show that entanglement fluctuations peak at a transverse-field-driven quantum phase transition between a memory-ordered and a paramagnetic phase,thereby linking the fragility of quantum neural memory to standard notions of quantum criticality. 展开更多
关键词 quantum neural networks hopfield model quantum correlations entanglement open quantum systems entropic uncertainty
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Edge-intelligent semantic aggregation in blockchainsecured 6G UAV-assisted Internet of vehicles 认领 引用
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作者 Zeeshan Ali Haider Inam Ullah +3 位作者 Akmalbek Abdusalomov Mohsin Shah Muhammad Zubair Khan Basem Abu Zneid 《Journal of Electronic Science and Technology》 EI CAS CSCD 2026年第1期14-28,共15页
The intelligent transportation systems require secure,low-latency,and reliable communication architectures to enable the real-time vehicular application.This paper proposes an edge-intelligent semantic aggregation(EIS... The intelligent transportation systems require secure,low-latency,and reliable communication architectures to enable the real-time vehicular application.This paper proposes an edge-intelligent semantic aggregation(EISA)framework for 6G unmanned aerial vehicle(UAV)-assisted Internet of vehicles(IoV)networks that integrates task-driven semantic communication,deep reinforcement learning(DRL)-based edge intelligence,and blockchain-based semantic validation across 6G terahertz(THz)links.UAVs in the proposed architecture serve as adaptive edge nodes that receive semantically vital information about the vehicle at any given stage,optimize aggregation and transmission parameters dynamically,and guarantee data integrity through a structured,lightweight consortium blockchain that signs semantically detailed representations rather than raw packets.Simulation results from a hybrid NS-3,MATLAB,and Python environment indicate that the proposed framework can achieve up to 45%reduction in end-to-end latency,an approximately 70%increase in throughput,and semantic efficiency with blockchain verification delays of less than 20 ms(more than 98%).These findings support the effectiveness of the proposed co-design for achieving context-aware,energy-efficient,and reliable communication under heavy-traffic conditions.The proposed framework provides a flexible and scalable foundation for next-generation 6G-enabled automotive networks,with subsequent growth toward federated learning-based collaborative intelligence,digital-twinassisted traffic modeling,and quantum-safe blockchain mechanisms to enhance scalability,intelligence,and long-term security. 展开更多
关键词 Blockchain Edge intelligence Internet of vehicles(IoV) Reinforcement learning Semantic communication Unmanned aerial vehicle(UAV) 6G
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Integration of data science with the intelligent IoT(IIoT):Current challenges and future perspectives 认领 引用 被引量：7
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作者 Inam Ullah Deepak Adhikari +3 位作者 Xin Su Francesco Palmieri Celimuge Wu Chang Choi 《Digital Communications and Networks》 SCIE EI CSCD 2025年第2期280-298,共19页
The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,s... The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,such as Artificial Intelligence(AI)and machine learning,to make accurate decisions.Data science is the science of dealing with data and its relationships through intelligent approaches.Most state-of-the-art research focuses independently on either data science or IIoT,rather than exploring their integration.Therefore,to address the gap,this article provides a comprehensive survey on the advances and integration of data science with the Intelligent IoT(IIoT)system by classifying the existing IoT-based data science techniques and presenting a summary of various characteristics.The paper analyzes the data science or big data security and privacy features,including network architecture,data protection,and continuous monitoring of data,which face challenges in various IoT-based systems.Extensive insights into IoT data security,privacy,and challenges are visualized in the context of data science for IoT.In addition,this study reveals the current opportunities to enhance data science and IoT market development.The current gap and challenges faced in the integration of data science and IoT are comprehensively presented,followed by the future outlook and possible solutions. 展开更多
关键词 Data science Internet of things(IoT) Big data Communication systems Networks Security Data science analytics
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Autonomous network management for 6G communication:A comprehensive survey 认领 引用 被引量：1
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作者 Inam Ullah Ali Arishi +5 位作者 Sushil Kumar Singh Faisal Alharbi Anwar Hassan Ibrahim Muhammad Islam Yousef Ibrahim Daradkeh Chang Choi 《Digital Communications and Networks》 SCIE EI CSCD 2025年第6期1917-1940,共24页
The rapid advancement of 6G communication networks presents both considerable problems and opportunities in network management,necessitating sophisticated solutions that extend beyond conventional methods.This study s... The rapid advancement of 6G communication networks presents both considerable problems and opportunities in network management,necessitating sophisticated solutions that extend beyond conventional methods.This study seeks to investigate and evaluate autonomous network management solutions designed for 6G communication networks,highlighting their technical advantages and potential implications.We examine the role of Artificial Intelligence(AI),Machine Learning(ML),and network automation in facilitating self-organization,optimization,and decision-making within critical network domains,including spectrum management,traffic load balancing,fault detection,and security and privacy.We examine the integration of edge computing and Distributed Ledger Technologies(DLT),specifically blockchain,to improve trust,transparency,and security in autonomous networks.This study provides a comprehensive understanding of the technological developments driving fully autonomous,efficient,and resilient 6G network infrastructures by methodically analyzing existing methodologies,identifying significant research gaps,and exploring potential prospects.The results offer significant insights for researchers,engineers,and industry experts involved in the development and deployment of advanced autonomous network management systems. 展开更多
关键词 Autonomous network management AI 6G communication NFV SDN Networks Machine learning
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Extended Kalman Filter-based localization algorithm by edge computing in Wireless Sensor Networks 认领 引用 被引量：14
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作者 Inam Ullah Siyu Qian +1 位作者 Zhixiang Deng Jong-Hyouk Lee 《Digital Communications and Networks》 SCIE EI CSCD 2021年第2期187-195,共9页
The Extended Kalman Filter(EKF)has received abundant attention with the growing demands for robotic localization.The EKF algorithm is more realistic in non-linear systems,which has an autonomous white noise in both th... The Extended Kalman Filter(EKF)has received abundant attention with the growing demands for robotic localization.The EKF algorithm is more realistic in non-linear systems,which has an autonomous white noise in both the system and the estimation model.Also,in the field of engineering,most systems are non-linear.Therefore,the EKF attracts more attention than the Kalman Filter(KF).In this paper,we propose an EKF-based localization algorithm by edge computing,and a mobile robot is used to update its location concerning the landmark.This localization algorithm aims to achieve a high level of accuracy and wider coverage.The proposed algorithm is helpful for the research related to the use of EKF localization algorithms.Simulation results demonstrate that,under the situations presented in the paper,the proposed localization algorithm is more accurate compared with the current state-of-the-art localization algorithms. 展开更多
关键词 Extended Kalman filter Edge computing Kalman filter Localization Robots State estimation
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Efficacy of an adjusted treatment strategy on the management and in-hospital outcome of patients with STEMI during the COVID-19 pandemic 认领 引用
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作者 Jing Wang Inam Ullah +11 位作者 Zhou Dong Zekang Ye Qian Gu Chuchu Tan Jiazheng Ma Jianzhen Teng Lu Shi Xiaoxuan Gong Yong Li Liang Yuan Zhihui Xu Chunjian Li 《Journal of Biomedical Research》 CAS CSCD 2022年第1期80-82,共3页
Dear Editor,The coronavirus disease 2019(COVID-19) broke out in early December 2019 in Wuhan, China~([1]), which put tremendous pressure on the medical system. A nationwide lockdown and strict quarantine measures prov... Dear Editor,The coronavirus disease 2019(COVID-19) broke out in early December 2019 in Wuhan, China~([1]), which put tremendous pressure on the medical system. A nationwide lockdown and strict quarantine measures proved effective in reducing the spread of the pandemic. However, it might have affected the management of time-dependent diseases such as STelevation myocardial infarction(STEMI)~([2]). 展开更多
关键词 STEMI treatment nationwide
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Climate Factors of Vapour Pressure and Diurnal Temperature Influenced on Radial Growth of Scots Pine in Northeastern Mongolia 认领 引用
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作者 Sumaira Yasmeen Farah Perveen +1 位作者 Inam Ullah Xiaochun Wang 《Open Journal of Ecology》 2019年第9期401-412,共12页
To find out the optimum conditions of growth in Scots pine (Pinus sylvestris var. mongolica), we analyzed the radial growth response relationship to climate factors in boreal forests. We present growth response from 3... To find out the optimum conditions of growth in Scots pine (Pinus sylvestris var. mongolica), we analyzed the radial growth response relationship to climate factors in boreal forests. We present growth response from 3-sites Mg (Mangui), KYH (kheyihe), NM (Nanmu) from central Daxing’an mountains. Drought observed in 1920s-1930s years. We analyzed growth response from 1920-2016. Results specified that growth of scots pine did not vary with variation in sites. We measure the influence of vapour pressure and mean maximum and mean minimum diurnal temperature have been shown by correlations of different growing seasons. Most of warm temperature during June to September and growth of Scots pine show a significantly positive increase during winter season. Overall inconsistency in climate conditions of Daxing’an mountains due to Atlantic and Pacific oceans, affects the Asian moon soon and alternatively changes the local temperature and precipitation and vapour pressure and increases the drought severity. 展开更多
关键词 Climate Variables Scots Pine Vapour Pressure Radial Growth Diurnal Temperature
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