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检索条件"任意字段=IEEE International Conference on Distributed Computing in Sensor Systems"

共 30822 条记录，以下是1551-1560 订阅

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SMA-NBO: A Sequential Multi-Agent Planning with Nominal Belief-State Optimization in Target Tracking

SMA-NBO: A Sequential Multi-Agent Planning with Nominal Beli...

引用

ieee/RSJ international conference on Intelligent Robots and systems (IROS)

作者： Li, Tianqi Krakow, Lucas W. Gopalswamy, Swaminathan Texas A&M Univ Dept Mech Engn College Stn TX 77840 USA Texas A&M Univ BCDC Bryan TX 77807 USA

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

In target tracking with mobile multi-sensor systems, sensor deployment impacts the observation capabilities and the resulting state estimation quality. Based on a partially observable Markov decision process (POMDP) formulation comprised of the observable sensor dynamics, unobservable target states, and accompanying observation laws, we present a distributed information-driven solution approach to the multi-agent target tracking problem, namely, sequential multi-agent nominal belief-state optimization (SMA-NBO). SMA-NBO seeks to minimize the expected tracking error via receding horizon control including a heuristic expected cost-to-go (HECTG). SMA-NBO incorporates a computationally efficient approximation of the target belief-state over the horizon. The agent-byagent decision-making is capable of leveraging on-board (edge) compute for selecting (sub-optimal) target-tracking maneuvers exhibiting non-myopic cooperative fleet behavior. The optimization problem explicitly incorporates semantic information defining target occlusions from a world model. To illustrate the efficacy of our approach, a random occlusion forest environment is simulated. SMA-NBO is compared to other baseline approaches. The simulation results show SMA-NBO 1) maintains tracking performance and reduces the computational cost by replacing the calculation of the expected target trajectory with a single sample trajectory based on maximum a posteriori estimation;2) generates cooperative fleet decision by sequentially optimizing single-agent policy with efficient usage of other agents' policy of intent;3) aptly incorporates the multiple weighted trace penalty (MWTP) HECTG, which improves tracking performance with a computationally efficient heuristic.

关键词： Reactive and sensor-based planning cooperating robots policy of intent random occlusion forest heterogeneous fleet

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Robustifying cooperative awareness in autonomous vehicles through local information diffusion 20

Robustifying cooperative awareness in autonomous vehicles th...

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20th ieee international conference on Industrial Informatics (INDIN)

作者： Piperigkos, Nikos Lalos, Aris S. Berberidis, Kostas Univ Patras Comp Engn & Informat Dept Patras Greece Athena Res Ctr Ind Syst Inst Patras Sci Pk Patras Greece

ISBN: (数字)9781728175683

ISBN: (纸本)9781728175683

Cooperative Intelligent Transportation systems envision the integration of cooperative intelligence as a key operational part of autonomous driving. In this way, a fleet or swarm of Connected and Automated Vehicles collectively coordinates its driving actions in order to maximize its performance. To realize this ambition, vehicles need to be fully location-aware of their surrounding environment, through distributed AI intelligence. Motivated by this requirement, we develop in this paper a distributed cooperative awareness scheme which performs multimodal fusion of heterogeneous sensor sources along with V2V communication information, using graph Laplacian matrix and Least-Mean-Squares algorithm. The intuition behind our approach is that neighboring vehicles are interested in estimating common positions of other vehicles. We build upon our previous work on global awareness though local information diffusion, and prove that the proposed distributed framework is able to address highly efficient the case of lacking any information about other networked vehicles. More specifically, our approach achieves high enough convergence speed as well as location accuracy. The evaluation study has been performed in CARLA autonomous driving simulator and verifies the proposed method's benefits over other related solutions.

关键词： Localization Cooperative Awareness Least-Mean-Squares Information diffusion sensor fusion

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Machine Learning Technique to Monitor Heartbeat using Amalgamated Data of Multi-sensor Stream 3

Machine Learning Technique to Monitor Heartbeat using Amalga...

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3rd international conference on Communication, computing and Digital systems, C-CODE 2023

作者： Hayat, Umar Iqbal, Zahid Mumtaz, Anam Abbas, Sara Bahria University Islamabad Pakistan Air University Islamabad Pakistan

ISBN: (纸本)9798350332391

The use of wearable devices in healthcare has become increasingly prevalent, with a focus on monitoring chronic diseases such as heart rate. Researchers have employed various methods, including machine learning, to analyze and predict personal activities. This study aims to predict abnormal behavior patterns within a FitBit dataset to anticipate potential diseases. The methodology involves using classification models such as Long Short-Term Memory (LSTM), Deep Neural network (DNN), and Support Vector Memory (SVM), as well as feature selection techniques such as Recursive Feature Elimination (RFE) and Random Forest (RF). The proposed system achieved a high accuracy rate of 85% using Random Forest. This research can aid in predicting and preventing future diseases, as well as providing behavior advice to help individuals achieve their fitness goals. © 2023 ieee.

关键词： Support vector machines

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Grey Wolf Optimization Algorithm based Combined Economic and Emission Dispatch Problem 2

Grey Wolf Optimization Algorithm based Combined Economic and...

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2nd international conference on Applied Artificial Intelligence and computing, ICAAIC 2023

作者： Manikandan, K. Swapna, Kesamreddy Narendra Naik, J. Kumar, K Naveen Rakesh, Kaku Vaishnavi, Kamisetty Sree Vidyanikethan Engineering College Department of Eee Tirupati517102 India

ISBN: (纸本)9781665456302

Economic dispatch for the microgrid (MG) is better adapted to the needs of a system in actual operation in the current scenario because it not only takes into account the scheduling cycle's lowest cost but also coordinates between several distributed generations (DGs) over a long period of time. Due of the unpredictable fluctuations and intervals that wind and solar energy are subject to, the economic dispatch problem is quite challenging to resolve. Intelligent algorithms and multi-objective optimum dispatching systems are acknowledged as excellent strategies for enhancing the economics and environmental friendliness of microgrid applications. The Multi Objective Optimal Dispatching System is developed for microgrids made up of photovoltaic cells (PV), wind turbines (WT), micro turbines (MT), fuel cells (FC), and battery storage (BT). The microgrid's dispatching problems might be solved and its dispatching convergence accuracy., stability., and speed all increased by using optimization techniques. © 2023 ieee.

关键词： distributed power generation

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distributed Primal-Dual Interior Point Framework for Analyzing Infeasible Combined Transmission and Distribution Grid Networks 58

Distributed Primal-Dual Interior Point Framework for Analyzi...

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58th Hawaii international conference on System Sciences, HICSS 2025

作者： Ali, Muhammad Hamza Pandey, Amritanshu University of Vermont United States

ISBN: (纸本)9780998133188

The proliferation of distributed energy resources has heightened the interactions between transmission and distribution (T&D) systems, necessitating novel analyses for the reliable operation and planning of interconnected T&D networks. A critical gap is an analysis approach that identifies and localizes the weak spots in the combined T&D networks, providing valuable information to system planners and operators. The research goal is to efficiently model and simulate infeasible (i.e. unsolvable in general settings) combined positive sequence transmission and three-phase distribution networks with a unified solution algorithm. We model the combined T&D network with the equivalent circuit formulation. To solve the overall T&D network, we build a Gauss-Jacobi-Newton (GJN) based distributed primal dual interior point optimization algorithm capable of isolating weak nodes. We validate the approach on large combined T&D networks with 70k+ T and 15k+ D nodes and demonstrate performance improvement over the alternating direction method of multipliers (ADMM) method. © 2025 ieee Computer Society. All rights reserved.

关键词： Grid computing

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Arithmetic Average Based Multi-sensor TPHD Filter for distributed Multi-target Tracking

Arithmetic Average Based Multi-sensor TPHD Filter for Distri...

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ieee international conference on Multisensor Fusion and Integration for Intelligent systems (MFI)

作者： Fu, Jiazheng Chai, Lei Zhang, Boxiang Yi, Wei Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu Peoples R China

ISBN: (数字)9781665460262

ISBN: (纸本)9781665460262

Compared with the probability hypothesis density (PHD) filter for sets of targets, the trajectory probability hypothesis density (TPHD) filter can estimate the sets of trajectories in a principle way and has better target tracking performance. This paper aims at extending the TPHD filter to distributed multi-target tracking (MTT) for the multi-sensor system. However, in the trajectory set based distributed fusion implementation, the trajectory state difference phenomenon makes the clustering and merging techniques unfeasible in trajectory state space. To address this problem, this paper studies the space decomposition of the TPHD and proposes a distributed MTT method based on the TPHD filter with the weighted arithmetic average (WAA) fusion rule. First, we prove the rationality of the space decomposition in the posterior density of the TPHD filter. Then, based on the proposed property, we derive the WAA fusion formulation of the TPHD filter by minimizing the weighted sum of Kullback-Leibler divergences (KLD) from local posterior densities, and develop the analytical Gaussian mixture (GM) implementation with the L-scan approximation. Numerical results demonstrate the efficacy of the proposed fusion method.

关键词： distributed multi-target tracking trajectory probability hypothesis density filter information fusion weighted arithmetic average

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Situation Theory Based Query Generation for Determining Situation Awareness Across distributed Data Streams 4

Situation Theory Based Query Generation for Determining Situ...

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4th ieee international conference on Human-Machine systems, ICHMS 2024

作者： Jia, Lesong Peng, Anfeng Li, Huao Guo, Xuehang Lewis, Michael University Of Pittsburgh School Of Computing And Information PittsburghPA15260 United States

ISBN: (纸本)9798350315790

While conventional measures of Situation Awareness (SA) focus on its adequacy in supporting decisions, fully exploiting information being returned by teams of unmanned aerial vehicles (UAVs) requires close attention to the sources as well as the impact of information. The problem of measuring SA for UAV teams lies in determining the extent to which information is being integrated from across the team. To address this problem, we are developing a Situation Theory based method for spatially and temporally indexing relevant situations. Observations from each UAV are treated as 'infons' indexed by their particular time and place. By maintaining provenance on individual observations, we can trace their participation in supporting operator SA and use these data to evaluate the effects of alternative data presentations for multi-UAV surveillance. A wildfire monitoring application domain is introduced, and an example developed from a wildfire training scenario for Great Sand Dunes National Park. © 2024 ieee.

关键词： Antennas

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Intelligent Islanding Classification with MLPNN for Hybrid distributed Energy Generations in Microgrid System

Intelligent Islanding Classification with MLPNN for Hybrid D...

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2023 ieee international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, ICIITCEE 2023

作者： Saifi, Izhar Ahmad Haque, Ahteshamul Amir, Mohammad Bharath Kurukuru, V.S. Jamia Millia Islamia Department of Electrical Engineering India Silicon Austria Labs Power Electronics Research Division Austria

ISBN: (纸本)9781665462631

Due to the rise in penetration of distributed energy resources (DERs) and energy storage systems (ESSs) into the microgrid (μG) system, the abrupt disconnections of DERs and ESSs might have an effect on the stability and dependability of the entire μG system. It is important to take into account the low-voltage ride-through (LVRT) capabilities to keep the μG system operating steadily. In order to quickly identify grid abnormalities and categorize islanding scenarios, this paper attempts to develop an islanding detection technique. The procedure involves generation of data samples corresponding to different grid abnormalities and training them with a machine learning based classifier. To achieve this process, a grid-connected (GC) three-phase μG system is simulated and compiled in Typhoon HIL application software to get distinct data sets for different grid fault conditions. Additionally, the data is trained using the multilayered perceptron neural network (MLPNN) classifier to create the islanding classification process. The trained classifier has 99.5% effectiveness and can classify data at a rate of about 170000 observations per second. © 2023 ieee.

关键词： Classification (of information)

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Optimizing 3D object detection for embedded systems in automated vehicles using sensor data fusion and CUDA computing 18

Optimizing 3D object detection for embedded systems in autom...

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ieee 18th international conference on Intelligent Computer Communication and Processing (ICCP)

作者： Miekkala, Topi Kutila, Matti Schneider, Mathias Hoess, Alfred VTT Techincal Res Ctr Finland Ltd Tampere Finland Tech Univ Appl Sci Amberg Weiden Germany

ISBN: (纸本)9781665464376

This article explores the utilization of the processing power of GPUs using CUDA computation for real-time aggregation of multi-sensor data and detection of 3D objects using parallel clustering algorithms. The purpose is to implement an algorithm that fuses raw lidar point cloud data and 2D camera image object detections to produce 3D object clusters in a lidar point cloud. Most of the computation has been implemented using CUDA parallelism to investigate the capability of GPU devices in this task, which is a common challenge in automated driving. The results indicate that processing times can be optimized within the algorithm, which is crucial when considering the large amounts of data provided by lidar and camera-based systems. The algorithm can perform inference on the Jetson Xavier AGX at rates of similar to 20 to similar to 220 ms depending on the number of objects and their corresponding point amounts in the KITTI dataset.

关键词： 3D object detection CUDA sensor data fusion automated driving

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Multicriteria Data Processing Management in the Geographically distributed computing systems with QoS Time Requirements 16

Multicriteria Data Processing Management in the Geographical...

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16th international conference Management of Large-Scale System Development, MLSD 2023

作者： Klimenko, Anna Institute of It and Security Technologies Russian State University for Humanities Moscow Russia

ISBN: (纸本)9798350337907

This paper is devoted to the problem of data processing management in fog- and edge-computing environments. The main issue of task planning is that the environments of the fog and edge network tiers are dynamic and heterogeneous in terms of optimization criteria. Previously published papers do not consider the heterogeneity of the criteria in the tasks of data processing, although the heterogeneity of the network generates a wide range of criteria and constraints for the workload distribution. The main contribution of this paper is as follows: the general model of a multicriteria workload distribution problem, which differs from previously proposed ones by the heterogeneous criteria usage, and by the integration of the reconfiguration process into the problem description, taking into account the main QoS time constraint. The basic method of the problem solution is proposed, too, with paying attention to the data transit extra-costs. Some selected simulation examples are described as well, which present the possibility to achieve the solution of the problem formulated. © 2023 ieee.

关键词： Fog computing

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