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Sports injury surveillance practices and data collection methods in university student athletes:A systematic review 认领 引用
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作者 Raven Chriscendo Schippers Barry Andrews +4 位作者 Romain Meeusen Evert Verhagen Jo Verschueren Bruno Tassignon Lloyd Leach 《Journal of Sport and Health Science》 SCIE CAS CSCD 2026年第7期81-93,共13页
Background:Injury surveillance is essential for the safety and protection of athletes'health.Consistent data collection methods are needed in sports injury surveillance and reporting.This systematic review aimed t... Background:Injury surveillance is essential for the safety and protection of athletes'health.Consistent data collection methods are needed in sports injury surveillance and reporting.This systematic review aimed to identify the injury surveillance practices and data collection methods in university student athletes and to evaluate the extent to which these injury surveillance practices and data collection methods align with the International Olympic Committee(IOC)consensus statement.Methods:A systematic review was conducted to identify studies describing injury surveillance practices and data collection methods in university student athletes.Studies not describing university injury surveillance or that described non-athlete populations were excluded,as well as case-control,cross-sectional,retrospective cohort studies,interventions,reviews,grey literature,and non-primary research.Four databases(Pub Med,SPORTDiscus,Scopus,and Web of Science)were searched from January 2000 to August 2024.Potential references were recorded through Mendeley and exported to Covidence.Two reviewers(RCS and JV)independently screened studies and assessed risk of bias using the Newcastle-Ottawa Scale.References were managed using Mendeley and Covidence.Data were analyzed descriptively,synthesized,and summarized.Results:A total of 11,188 records were identified.After screening the titles,abstracts,and full texts,50 were eligible for the systematic review.The studies were conducted across 9 countries and included a total number of 11,182 participants.Fifty-four percent of the included studies used a time-loss definition of injury,while an athletic trainer recorded the injury data(62%),and an electronic tool/web system was used to collect injury data(30%).Only 3 studies aligned with the IOC consensus statement.Conclusion:This review highlighted the necessity for consistent,standardized injury surveillance practices and data collection methods in university sport.Only 3 of the included studies adhered to the IOC consensus statement,which provides a methodological framework to guide injury surveillance with appropriate contextual adaptation to facilitate injury prevention at the university level. 展开更多
关键词 Data collection Methods Surveillance University
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Importance of data collection and subgroup analyses in research methodology 认领 引用
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作者 Sunny Chi Lik Au 《World Journal of Meta-Analysis》 2025年第2期98-101,共4页
Data collection serves as the cornerstone in the study of clinical research questions.Two types of data are commonly utilized in medicine:(1)Qualitative;and(2)Quantitative.Several methods are commonly employed to gath... Data collection serves as the cornerstone in the study of clinical research questions.Two types of data are commonly utilized in medicine:(1)Qualitative;and(2)Quantitative.Several methods are commonly employed to gather data,regardless of whether retrospective or prospective studies are used:(1)Interviews;(2)Observational methods;(3)Questionnaires;(4)Investigation parameters;(5)Medical records;and(6)Electronic chart reviews.Each source type has its own advantages and cons in terms of the accuracy and availability of the data to be extracted.We will focus on the important parts of the research methodology:(1)Data collection;and(2)Subgroup analyses.Errors in research can arise from various sources,including investigators,instruments,and subjects,making the validation and reliability of research tools crucial for ensuring the credibility of findings.Subgroup analyses can either be planned before or emerge after(post-hoc)treatment.The interpretation of subgroup effects should consider the interaction between treatment effect and various patient variables with caution. 展开更多
关键词 Data collection Methodology Research Journal Academic
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Hybrid Teaching Reform and Practice in Big Data Collection and Preprocessing Courses Based on the Bosi Smart Learning Platform 认领 引用 被引量：1
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作者 Yang Wang Xuemei Wang Wanyan Wang 《Journal of Contemporary Educational Research》 2025年第2期96-100,共5页
This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model... This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model follows a“three-stage”and“two-subject”framework,incorporating a structured design for teaching content and assessment methods before,during,and after class.Practical results indicate that this approach significantly enhances teaching effectiveness and improves students’learning autonomy. 展开更多
关键词 Big Data Collection and Preprocessing Bosi smart learning platform Hybrid teaching Teaching reform
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Energy-efficient data collection for UAV-assisted IoT: Joint trajectory and resource optimization 认领 引用 被引量：7
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作者 Xiao TANG Wei WANG +1 位作者 Hongliang HE Ruonan ZHANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2022年第9期95-105,共11页
Internet of Things(IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. As energyefficient operations are critical to ... Internet of Things(IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. As energyefficient operations are critical to prolong the lifetime of the energy-constrained IoT devices, the Unmanned Aerial Vehicle(UAV) can be dispatched to geographically approach the IoT clusters towards energy-efficient IoT transmissions. This paper intends to maximize the system energy efficiency by considering both the IoT transmission energy and UAV propulsion energy, where the UAV trajectory and IoT communication resources are jointly optimized. By applying largesystem analysis and Dinkelbach method, the original fractional optimization is approximated and reformulated in the form of subtraction, and further a block coordinate descent framework is employed to update the UAV trajectory and IoT communication resources iteratively. Extensive simulation results are provided to corroborate the effectiveness of the proposed method. 展开更多
关键词 Block coordinate descent Data collection Dinkelbach method Energy efficiency Internet of Things(IoT) Unmanned aerial vehicle
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Energy Aware Data Collection with Route Planning for 6G Enabled UAV Communication 认领 引用 被引量：3
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作者 Mesfer Al Duhayyim Marwa Obayya +3 位作者 Fahd N.Al-Wesabi Anwer Mustafa Hilal Mohammed Rizwanullah Majdy M.Eltahir 《Computers, Materials & Continua》 SCIE EI 2022年第4期825-842,共18页
With technological advancements in 6G and Internet of Things(IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellularnetworks has become a hot research topic. At present, the proficient evolution of 6G ... With technological advancements in 6G and Internet of Things(IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellularnetworks has become a hot research topic. At present, the proficient evolution of 6G networks allows the UAVs to offer cost-effective and timelysolutions for real-time applications such as medicine, tracking, surveillance,etc. Energy efficiency, data collection, and route planning are crucial processesto improve the network communication. These processes are highly difficultowing to high mobility, presence of non-stationary links, dynamic topology,and energy-restricted UAVs. With this motivation, the current research paperpresents a novel Energy Aware Data Collection with Routing Planning for6G-enabled UAV communication (EADCRP-6G) technique. The goal of theproposed EADCRP-6G technique is to conduct energy-efficient cluster-baseddata collection and optimal route planning for 6G-enabled UAV networks.EADCRP-6G technique deploys Improved Red Deer Algorithm-based Clustering (IRDAC) technique to elect an optimal set of Cluster Heads (CH) andorganize these clusters. Besides, Artificial Fish Swarm-based Route Planning(AFSRP) technique is applied to choose an optimum set of routes for UAVcommunication in 6G networks. In order to validated whether the proposedEADCRP-6G technique enhances the performance, a series of simulationswas performed and the outcomes were investigated under different dimensions.The experimental results showcase that the proposed model outperformed allother existing models under different evaluation parameters. 展开更多
关键词 Unmanned aerial vehicle 6G networks artificial intelligence energy efficiency clustering route planning data collection metaheuristics
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UAV trajectory planning algorithmfor data collection in wireless sensor networks 认领 引用 被引量：2
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作者 Yan Feng Chen Jiahui +5 位作者 Wu Tao Li Hao Pang Jingming Liu Wanzhu Xia Weiwei Shen Lianfeng 《Journal of Southeast University(English Edition)》 EI CAS 2020年第4期376-384,共9页
In order to maximize the value of information(VoI)of collected data in unmanned aerial vehicle(UAV)-aided wireless sensor networks(WSNs),a UAV trajectory planning algorithm named maximum VoI first and successive conve... In order to maximize the value of information(VoI)of collected data in unmanned aerial vehicle(UAV)-aided wireless sensor networks(WSNs),a UAV trajectory planning algorithm named maximum VoI first and successive convex approximation(MVF-SCA)is proposed.First,the Rician channel model is adopted in the system and sensor nodes(SNs)are divided into key nodes and common nodes.Secondly,the data collection problem is formulated as a mixed integer non-linear program(MINLP)problem.The problem is divided into two sub-problems according to the different types of SNs to seek a sub-optimal solution with a low complexity.Finally,the MVF-SCA algorithm for UAV trajectory planning is proposed,which can not only be used for daily data collection in the target area,but also collect time-sensitive abnormal data in time when the exception occurs.Simulation results show that,compared with the existing classic traveling salesman problem(TSP)algorithm and greedy path planning algorithm,the VoI collected by the proposed algorithm can be improved by about 15%to 30%. 展开更多
关键词 unmanned aerial vehicle wireless sensor networks trajectory planning data collection value of information
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Traffic Scheduling Mechanism Based on Interference Avoidance for Meter Data Collection in Wireless Smart Grid Communication Networks 认领 引用 被引量：1
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作者 SHAO Sujie GUO Shaoyong +2 位作者 QIU Xuesong MENG Luoming LEI Min 《China Communications》 SCIE CSCD 2015年第7期142-153,共12页
Meter Data Collection Building Area Network(MDCBAN) deployed in high rises is playing an increasingly important role in wireless multi-hop smart grid meter data collection. Recently, increasingly numerous application ... Meter Data Collection Building Area Network(MDCBAN) deployed in high rises is playing an increasingly important role in wireless multi-hop smart grid meter data collection. Recently, increasingly numerous application layer data traffic makes MDCBAN be facing serious communication pressure. In addition, large density of meter data collection devices scattered in the limited geographical space of high rises results in obvious communication interference. To solve these problems, a traffic scheduling mechanism based on interference avoidance for meter data collection in MDCBAN is proposed. Firstly, the characteristics of network topology are analyzed and the corresponding traffic distribution model is proposed. Next, a wireless multi-channel selection scheme for different Floor Gateways and a single-channel time unit assignment scheme for data collection devices in the same Floor Network are proposed to avoid interference. At last, a data balanced traffic scheduling algorithm is proposed. Simulation results show that balanced traffic distribution and highly efficient and reliable data transmission can be achieved on the basis of effective interference avoidance between data collection devices. 展开更多
关键词 smart grid communication meter data collection traffic scheduling interference avoidance building area network
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Optimizing Data Collection Path in Sensor Networks with Mobile Elements 认领 引用 被引量：2
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作者 Liang He Zhi Chen Jing-Dong Xu 《International Journal of Automation and computing》 2011年第1期69-77,共9页
Exploiting mobile elements （MEs） to accomplish data collection in wireless sensor networks （WSNs） can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large dat... Exploiting mobile elements （MEs） to accomplish data collection in wireless sensor networks （WSNs） can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large data collection latency for the network, which is unacceptable for data-critical applications. In this paper, we address this problem by minimizing the traveling length of MEs. Our methods mainly consist of two steps： we first construct a virtual grid network and select the minimal stop point set （SPS） from it; then, we make optimal scheduling for the MEs based on the SPS in order to minimize their traveling length. Different implementations of genetic algorithm （GA） are used to solve the problem. Our methods are evaluated by extensive simulations. The results show that these methods can greatly reduce the traveling length of MEs, and decrease the data collection latency. 展开更多
关键词 Mobile element data collection genetic algorithm sensor network data latency.
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Energy-Efficient Underwater Data Collection:A Q-Learning Based Approach 认领 引用 被引量：1
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作者 Haiyan Zhao Jing Yan +2 位作者 Tao Wu Aihong Li Xiaoyuan Luo 《Journal of Marine Science and Application》 CSCD 2022年第3期204-218,共15页
Underwater data collection is an importance part in the process of network monitoring,network management and intrusion detection.However,the limited-energy of nodes is a major challenge to collect underwater data.The ... Underwater data collection is an importance part in the process of network monitoring,network management and intrusion detection.However,the limited-energy of nodes is a major challenge to collect underwater data.The solution of this problem are not only in the hands of network topology but in the hands of path of autonomous underwater vehicle(AUV).With the problem in hand,an energy-efficient data collection scheme is designed for mobile underwater network.Especially,the data collection scheme is divided into two phases,i.e.,routing algorithm design for sensor nodes and path planing for AUV.With consideration of limited-energy and network robustness,Q-learning based dynamic routing algorithm is designed in the first phase to optimize the routing selection of nodes,through which a potential-game based optimal rigid graph method is proposed to balance the trade-off between the energy consumption and the network robustness.With the collected data,Q-learning based path planning strategy is proposed for AUV in the second phase to find the desired path to gather the data from data collector,then a mode-free tracking controller is developed to track the desired path accurately.Finally,the performance analysis and simulation results reveal that the proposed approach can guarantee energy-efficient and improve network stability. 展开更多
关键词 Underwater data collection Q-learning Energy efficient Path planning Autonomous underwater vehicle
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Design and implementation of railway green performance basic data collection system 认领 引用 被引量：2
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作者 Xiangru Lyu Hui Li 《High-Speed Railway》 2023年第4期265-272,共8页
This study addressed the issues related to the collection and management of basic data for railway green performance. A railway green performance basic database has been constructed based on metadata and data exchange... This study addressed the issues related to the collection and management of basic data for railway green performance. A railway green performance basic database has been constructed based on metadata and data exchange schemas. A data classification system has been established from the perspectives of businesses, processes,and entities. A BIM(Building Information Modelling) model data extraction scheme is proposed based on field similarity matching and a document content extraction scheme is proposed based on image recognition. A railway green performance basic data collection system has been developed, achieving efficient collection and integrated management of railway green performance basic data. This system can provide data support for applications such as railway carbon emissions accounting, green cost-benefit analysis, and evaluation of green design solutions. 展开更多
关键词 Railway Green performance Data collection Metadata Data classifcation BIM Image recognition
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Guidance of development,validation,and evaluation of algorithms for populating health status in observational studies of routinely collected data(DEVELOP-RCD) 认领 引用 被引量：1
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作者 Wen Wang Ying-Hui Jin +8 位作者 Mei Liu Qiao He Jia-Yue Xu Ming-Qi Wang Guo-Wei Li Bo Fu Si-Yu Yan Kang Zou Xin Sun 《Military Medical Research》 SCIE CAS CSCD 2025年第5期788-798,共11页
Background:In recent years,there has been a growing trend in the utilization of observational studies that make use of routinely collected healthcare data(RCD).These studies rely on algorithms to identify specific hea... Background:In recent years,there has been a growing trend in the utilization of observational studies that make use of routinely collected healthcare data(RCD).These studies rely on algorithms to identify specific health conditions(e.g.,diabetes or sepsis)for statistical analyses.However,there has been substantial variation in the algorithm development and validation,leading to frequently suboptimal performance and posing a significant threat to the validity of study findings.Unfortunately,these issues are often overlooked.Methods:We systematically developed guidance for the development,validation,and evaluation of algorithms designed to identify health status(DEVELOP-RCD).Our initial efforts involved conducting both a narrative review and a systematic review of published studies on the concepts and methodological issues related to algorithm development,validation,and evaluation.Subsequently,we conducted an empirical study on an algorithm for identifying sepsis.Based on these findings,we formulated specific workflow and recommendations for algorithm development,validation,and evaluation within the guidance.Finally,the guidance underwent independent review by a panel of 20 external experts who then convened a consensus meeting to finalize it.Results:A standardized workflow for algorithm development,validation,and evaluation was established.Guided by specific health status considerations,the workflow comprises four integrated steps:assessing an existing algorithm’s suitability for the target health status;developing a new algorithm using recommended methods;validating the algorithm using prescribed performance measures;and evaluating the impact of the algorithm on study results.Additionally,13 good practice recommendations were formulated with detailed explanations.Furthermore,a practical study on sepsis identification was included to demonstrate the application of this guidance.Conclusions:The establishment of guidance is intended to aid researchers and clinicians in the appropriate and accurate development and application of algorithms for identifying health status from RCD.This guidance has the potential to enhance the credibility of findings from observational studies involving RCD. 展开更多
关键词 Routinely collected healthcare data(RCD) Algorithms Health status Guidance
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Towards Task-Free Privacy-Preserving Data Collection 认领 引用
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作者 Zhibo Wang Wei Yuan +2 位作者 Xiaoyi Pang Jingxin Li Huajie Shao 《China Communications》 SCIE CSCD 2022年第7期310-323,共14页
With the rapid developments of Internet of Things(IoT)and proliferation of embedded devices,large volume of personal data are collected,which however,might carry massive private information about attributes that users... With the rapid developments of Internet of Things(IoT)and proliferation of embedded devices,large volume of personal data are collected,which however,might carry massive private information about attributes that users do not want to share.Many privacy-preserving methods have been proposed to prevent privacy leakage by perturbing raw data or extracting task-oriented features at local devices.Unfortunately,they would suffer from significant privacy leakage and accuracy drop when applied to other tasks as they are designed and optimized for predefined tasks.In this paper,we propose a novel task-free privacy-preserving data collection method via adversarial representation learning,called TF-ARL,to protect private attributes specified by users while maintaining data utility for unknown downstream tasks.To this end,we first propose a privacy adversarial learning mechanism(PAL)to protect private attributes by optimizing the feature extractor to maximize the adversary’s prediction uncertainty on private attributes,and then design a conditional decoding mechanism(ConDec)to maintain data utility for downstream tasks by minimizing the conditional reconstruction error from the sanitized features.With the joint learning of PAL and ConDec,we can learn a privacy-aware feature extractor where the sanitized features maintain the discriminative information except privacy.Extensive experimental results on real-world datasets demonstrate the effectiveness of TF-ARL. 展开更多
关键词 IoT privacy protection data collection adversarial learning deep learning
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Energy Optimization in Multi-UAV-Assisted Edge Data Collection System 认领 引用
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作者 Bin Xu Lu Zhang +4 位作者 Zipeng Xu Yichuan Liu Jinming Chai Sichong Qin Yanfei Sun 《Computers, Materials & Continua》 SCIE EI 2021年第11期1671-1686,共16页
In the IoT(Internet of Things)system,the introduction of UAV(Unmanned Aerial Vehicle)as a new data collection platform can solve the problem that IoT devices are unable to transmit data over long distances due to the ... In the IoT(Internet of Things)system,the introduction of UAV(Unmanned Aerial Vehicle)as a new data collection platform can solve the problem that IoT devices are unable to transmit data over long distances due to the limitation of their battery energy.However,the unreasonable distribution of UAVs will still lead to the problem of the high total energy consumption of the system.In this work,to deal with the problem,a deployment model of a mobile edge computing(MEC)system based on multi-UAV is proposed.The goal of the model is to minimize the energy consumption of the system in the process of data transmission by optimizing the deployment of UAVs.The DEVIPSK(differential evolution algorithm with variable population size based on a mutation strategy pool initialized by K-Means)is proposed to solve the model.In DEVIPSK,the population is initialized by K-Means to obtain better initial positions of UAVs.Besides,considering the limitation of the fixed mutation strategy in the traditional evolutionary algorithm,a mutation strategy pool is used to update the positions of UAVs.The experimental results show the superiority of the DEVIPSK and provide guidance for the deployment of UAVs in the field of edge data collection in the IoT system. 展开更多
关键词 UAV mobile edge computing differential evolution algorithm K-Means edge data collection
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Anonymous data collection scheme for cloud-aided mobile edge networks 认领 引用
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作者 Anxi Wang Jian Shen +2 位作者 Chen Wang Huijie Yang Dengzhi Liu 《Digital Communications and Networks》 SCIE EI 2020年第2期223-228,共6页
With the rapid spread of smart sensors,data collection is becoming more and more important in Mobile Edge Networks(MENs).The collected data can be used in many applications based on the analysis results of these data ... With the rapid spread of smart sensors,data collection is becoming more and more important in Mobile Edge Networks(MENs).The collected data can be used in many applications based on the analysis results of these data by cloud computing.Nowadays,data collection schemes have been widely studied by researchers.However,most of the researches take the amount of collected data into consideration without thinking about the problem of privacy leakage of the collected data.In this paper,we propose an energy-efficient and anonymous data collection scheme for MENs to keep a balance between energy consumption and data privacy,in which the privacy information of senors is hidden during data communication.In addition,the residual energy of nodes is taken into consideration in this scheme in particular when it comes to the selection of the relay node.The security analysis shows that no privacy information of the source node and relay node is leaked to attackers.Moreover,the simulation results demonstrate that the proposed scheme is better than other schemes in aspects of lifetime and energy consumption.At the end of the simulation part,we present a qualitative analysis for the proposed scheme and some conventional protocols.It is noteworthy that the proposed scheme outperforms the existing protocols in terms of the above indicators. 展开更多
关键词 Cloud-aided mobile edge networks Anonymous data collection Communication model Path selection
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Flight Time Minimization of UAV for Cooperative Data Collection in Probabilistic LoS Channel 认领 引用
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作者 Yan Li Shaoyi Xu +1 位作者 Yunpu Wu Dongji Li 《China Communications》 SCIE CSCD 2024年第2期210-226,共17页
This paper investigates the data collection in an unmanned aerial vehicle(UAV)-aided Internet of Things(IoT) network, where a UAV is dispatched to collect data from ground sensors in a practical and accurate probabili... This paper investigates the data collection in an unmanned aerial vehicle(UAV)-aided Internet of Things(IoT) network, where a UAV is dispatched to collect data from ground sensors in a practical and accurate probabilistic line-of-sight(LoS) channel. Especially, access points(APs) are introduced to collect data from some sensors in the unlicensed band to improve data collection efficiency. We formulate a mixed-integer non-convex optimization problem to minimize the UAV flight time by jointly designing the UAV 3D trajectory and sensors’ scheduling, while ensuring the required amount of data can be collected under the limited UAV energy. To solve this nonconvex problem, we recast the objective problem into a tractable form. Then, the problem is further divided into several sub-problems to solve iteratively, and the successive convex approximation(SCA) scheme is applied to solve each non-convex subproblem. Finally,the bisection search is adopted to speed up the searching for the minimum UAV flight time. Simulation results verify that the UAV flight time can be shortened by the proposed method effectively. 展开更多
关键词 data collection flight time probabilistic line-of-sight channel unlicensed band unmanned aerial vehicle
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An Anonymous Data Collection Framework for Digital Community 认领 引用
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作者 LI Hongtao MA Jianfeng FU Shua 《Wuhan University Journal of Natural Sciences》 CAS 2013年第5期385-392,共8页
Collected data in digital community containing sensitive information about individuals or corporations and such information should be protected. In this paper, a security framework based on （a, k）-anonymity for priv... Collected data in digital community containing sensitive information about individuals or corporations and such information should be protected. In this paper, a security framework based on （a, k）-anonymity for privacy preserving data collection in digital community is proposed. In our framework, aggregation nodes anonymize the collected data to a basic privacy level. Then, the base stations further anonymize the data to a deeper privacy level with encryption-generalizaiton operations. Experimental results and detailed theory analysis demonstrate that this method is effective in terms of privacy levels and data quality with low resource consumption. 展开更多
关键词 anonymity digital community data collection privacy
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Autonomous UAV 3D trajectory optimization and transmission scheduling for sensor data collection on uneven terrains 认领 引用
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作者 Andrey V.Savkin Satish C.Verma Wei Ni 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2023年第12期154-160,共7页
This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors ha... This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm. 展开更多
关键词 Unmanned aerial system UAS Unmanned aerial vehicle UAV Wireless sensor networks UAS-Assisted data collection 3D trajectory optimization Data transmission scheduling
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Joint UAV 3D deployment and sensor power allocation for energy-efficient and secure data collection 认领 引用
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作者 王东 LI Guizhi +1 位作者 SUN Xiaojing WANG Changqing 《High Technology Letters》 EI CAS 2023年第3期223-230,共8页
Unmanned aerial vehicles(UAVs) are advantageous for data collection in wireless sensor networks(WSNs) due to its low cost of use,flexible deployment,controllable mobility,etc. However,how to cope with the inherent iss... Unmanned aerial vehicles(UAVs) are advantageous for data collection in wireless sensor networks(WSNs) due to its low cost of use,flexible deployment,controllable mobility,etc. However,how to cope with the inherent issues of energy limitation and data security in the WSNs is challenging in such an application paradigm. To this end,based on the framework of physical layer security,an optimization problem for maximizing secrecy energy efficiency(EE) of data collection is formulated,which focuses on optimizing the UAV’s positions and the sensors’ transmit power. To overcome the difficulties in solving the optimization problem,the methods of fractional programming and successive convex approximation are then adopted to gradually transform the original problem into a series of tractable subproblems which are solved in an iterative manner. As shown in simulation results,by the joint designs in the spatial domain of UAV and the power domain of sensors,the proposed algorithm achieves a significant improvement of secrecy EE and rate. 展开更多
关键词 physical layer security energy efficiency(EE) power allocation unmanned aerial vehicle(UAV) data collection wireless sensor network(WSN)
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Uncertainties in stormwater runoff data collection from a small urban catchment, Southeast China 认领 引用 被引量：4
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作者 Jinliang Huan Zhenshun Tu +2 位作者 Pengfei Du Jie Lin Qingsheng Li 《Journal of Environmental Sciences》 SCIE EI CAS 2010年第11期1703-1709,共7页
Monitoring data are often used to identify stormwater runoff characteristics and in stormwater runoff modelling without consideration of their inherent uncertainties. Integrated with discrete sample analysis and error... Monitoring data are often used to identify stormwater runoff characteristics and in stormwater runoff modelling without consideration of their inherent uncertainties. Integrated with discrete sample analysis and error propagation analysis, this study attempted to quantify the uncertainties of discrete chemical oxygen demand （COD）, total suspended solids （TSS） concentration, stormwater flowrate, stormwater event volumes, COD event mean concentration （EMC）, and COD event loads in terms of flow measurement, sample collection, storage and laboratory analysis. The results showed that the uncertainties due to sample collection, storage and laboratory analysis of COD from stormwater runoff are 13.99%, 19.48% and 12.28%. Meanwhile, flow measurement uncertainty was 12.82%, and the sample collection uncertainty of TSS from stormwater runoff was 31.63%. Based on the law of propagation of uncertainties, the uncertainties regarding event flow volume, COD EMC and COD event loads were quantified as 7.03%, 10.26% and 18.47%. 展开更多
关键词 urban stormwater runoff in-situ monitoring data uncertainty data collection
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Artificial Intelligence-Enabled Cooperative Cluster-Based Data Collection for Unmanned Aerial Vehicles 认领 引用 被引量：2
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作者 R.Rajender C.S.S.Anupama +3 位作者 G.Jose Moses E.Laxmi Lydia Seifedine Kadry Sangsoon Lim 《Computers, Materials & Continua》 SCIE EI 2022年第11期3351-3365,共15页
In recent times,sixth generation(6G)communication technologies have become a hot research topic because of maximum throughput and low delay services for mobile users.It encompasses several heterogeneous resource and c... In recent times,sixth generation(6G)communication technologies have become a hot research topic because of maximum throughput and low delay services for mobile users.It encompasses several heterogeneous resource and communication standard in ensuring incessant availability of service.At the same time,the development of 6G enables the Unmanned Aerial Vehicles(UAVs)in offering cost and time-efficient solution to several applications like healthcare,surveillance,disaster management,etc.In UAV networks,energy efficiency and data collection are considered the major process for high quality network communication.But these procedures are found to be challenging because of maximum mobility,unstable links,dynamic topology,and energy restricted UAVs.These issues are solved by the use of artificial intelligence(AI)and energy efficient clustering techniques for UAVs in the 6G environment.With this inspiration,this work designs an artificial intelligence enabled cooperative cluster-based data collection technique for unmanned aerial vehicles(AECCDC-UAV)in 6G environment.The proposed AECCDC-UAV technique purposes for dividing the UAV network as to different clusters and allocate a cluster head(CH)to each cluster in such a way that the energy consumption(ECM)gets minimized.The presented AECCDC-UAV technique involves a quasi-oppositional shuffled shepherd optimization(QOSSO)algorithm for selecting the CHs and construct clusters.The QOSSO algorithm derives a fitness function involving three input parameters residual energy of UAVs,distance to neighboring UAVs,and degree of UAVs.The performance of the AECCDC-UAV technique is validated in many aspects and the obtained experimental values demonstration promising results over the recent state of art methods. 展开更多
关键词 6G unmanned aerial vehicles resource allocation energy efficiency artificial intelligence clustering data collection
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