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2022 IEEE International Conference on Smart Internet of Things (SmartIoT)最新文献

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Towards Smart Home Data Interpretation Using Analogies to Natural Language Processing 使用自然语言处理类比的智能家居数据解释
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00020
Matthias Melzer, Jan Dünnweber, Timo Baumann
Recent advances in the development of smart homes have led to the availability of a wide variety of devices providing a high level of convenience via gesture and speech control or fully automated operation. Many smart home appliances also address the aspects of safety and electricity savings by automatically powering themselves off after not being used for a while. However, many devices remain in a typical household that are not themselves “smart”, or are not primarily electric (such as heating systems). We address the savings aspect by identifying processes involving the use of multiple devices in the electrical flow data, as captured by a smart meter in a modern household, rather than focusing on a single appliance. Therefore, we introduce a novel approach to usage pattern analysis based on the idea that a pattern of device usages as a result of a resident's ‘routine’ (such as making breakfast) can be interpreted similarly to a natural language ‘sentence’; Natural Language Processing (NLP) algorithms can then be used for interpreting the residents' behavior. We introduce the notion of bag-oj-devices (BoD), derived from the bag-of-words model used in document classification. In an experiment, we show how we use this model to infer predictions about the inhabitants from device usage, such as the resident leaving for the day or just to fetch the newspaper.
智能家居发展的最新进展导致了各种各样的设备的可用性,通过手势和语音控制或全自动操作提供了高水平的便利。许多智能家电还通过在一段时间不使用后自动关闭电源来解决安全性和节电问题。然而,在一个典型的家庭中,仍有许多设备本身并不“智能”,或者主要不是电动的(比如供暖系统)。我们通过识别涉及在电流数据中使用多个设备的过程来解决节约方面的问题,正如现代家庭中的智能电表所捕获的那样,而不是专注于单个电器。因此,我们引入了一种新的使用模式分析方法,该方法基于这样一种想法,即由居民的“日常”(如做早餐)导致的设备使用模式可以类似于自然语言的“句子”来解释;自然语言处理(NLP)算法可以用来解释居民的行为。我们引入了从用于文档分类的词袋模型衍生出来的词袋装置(BoD)的概念。在一个实验中,我们展示了如何使用这个模型从设备使用情况推断出对居民的预测,比如居民当天离开或只是去取报纸。
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引用次数: 1
Intelligent system in the management and control of transportation companies: A systematic review 智能系统在运输公司管理和控制中的应用:系统综述
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00031
Mauro Raul Lopez-Noa, Hugo Eladio Chumpitaz-Caycho, Ericka Nelly Espinoza-Gamboa, Manuel Alberto Espinoza-Cruz, Franklin Cordova-Buiza
The study aimed to know how the intelligent transportation system improves the management and control of passenger transportation companies between 2016 and 2021. An adaptation of the Prisma methodology was used, which poses a system for evaluating the systematic review of scientific literature on its relationship with the objective and the research question. The databases used were Scopus, Ebsco, ProQuest and Scielo. A total of 52 scientific articles were found; and after applying the selection criteria,11 original studies were obtained. It is concluded that the intelligent systems were implemented with the aim of improving the management and control of transportation, through the new experience of traveling in these units allowing an important advantage for passengers. In the studies reviewed, the effectiveness of having accurate information regarding the route, stations, trunk lines and, above all, reducing obstacles and collisions due to drivers' lack of attention is exposed. Consequently, in the research reviewed, it has been found that these systems provide the user with real-time information on the various schedules, routes and delays of the units, helping to make decisions.
该研究旨在了解智能交通系统如何在2016年至2021年期间改善客运公司的管理和控制。本文采用了棱镜方法论的一种改编方法,该方法提出了一个系统,用于评估科学文献的系统综述与目标和研究问题的关系。使用的数据库为Scopus、Ebsco、ProQuest和Scielo。共发现科学论文52篇;应用选择标准后,得到11项原始研究。结论是,实施智能系统的目的是改善运输的管理和控制,通过在这些单位旅行的新体验,为乘客提供重要的优势。在审查的研究中,获得关于路线、车站、干线的准确信息的有效性,以及最重要的是,减少由于驾驶员缺乏注意力而造成的障碍和碰撞的有效性。因此,在审查的研究中发现,这些系统向用户提供有关各单位的各种时间表、路线和延误的实时信息,有助于作出决定。
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引用次数: 0
Roadmap-Restricted Multi-Robot Collaborative Hunting Method Based on Improved Artificial Potential Field 基于改进人工势场的路线图约束多机器人协同搜索方法
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00021
Xinzhi Gao, Shoucan Wang, N. Ding
How to design a multi-robot collaborative hunting method according to the local roadmap has become a key issue in the field of Multi-Robot Systems (MRS). This paper firstly establishes a robot potential field model based on the characteristics of the local roadmap, combined with the basic idea of the artificial potential field method. Then a multi-robot collaborative hunting strategy called Mobile Prediction Collaborative Interception (MPCI) is proposed based on the robot potential field model. The Adaptive Artificial Potential Field (AAPF) and the constraints are proposed to improve the MPCI to solve the three main problems of Target Loss, Target Unreachable, and Following Deadlock in the hunting process. On this basis, AAPF-MPCI collaborative hunting algorithm is proposed to improve the efficiency and stability of the system. The final simulation results show that the AAPF-MPCI algorithm is more stable and effectively shortens the time spent for MRS to hunt prey robots in roadmap-restricted scenes.
如何根据局部路线图设计多机器人协同狩猎方法已成为多机器人系统(MRS)领域的一个关键问题。本文首先根据局部路线图的特点,结合人工势场法的基本思想,建立了机器人势场模型。然后,基于机器人势场模型,提出了一种多机器人协同狩猎策略——移动预测协同拦截(MPCI)。提出了自适应人工势场(AAPF)和约束条件对MPCI进行改进,解决了搜索过程中目标丢失、目标不可达和跟随死锁三个主要问题。在此基础上,提出了AAPF-MPCI协同搜索算法,提高了系统的效率和稳定性。最后的仿真结果表明,AAPF-MPCI算法更加稳定,有效地缩短了路径受限场景下MRS捕捉猎物机器人的时间。
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引用次数: 0
Design of Vehicle Profile for Autonomous Vehicles in Roundabouts used to improve Lane Change Strategy based on Multi-vehicle Collaboration 基于多车协同的环形交叉口自动驾驶车辆轮廓设计改进变道策略
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00029
D. Cao, C. Hu, N. Ding
Intelligent and connected vehicles (ICVs) is developed based on Internet of Vehicles (IOV) and intelligent vehicles, has become an effective solution to optimize vehicle traffic and alleviate traffic congestion based on the collaborative strategy of vehicle - road - environment. This paper proposes a lane-changing strategy of vehicles at the exit of roundabout based on the Vehicle Profile(VP) which achieved by the driving characteristics of vehicles in traffic roundabout. Initially, Vehicle Profile(VP) is defined due to the hybrid problem of multi-source heterogeneous data existing in ICVs, then the multi-source heterogeneous data is represented by VP. Moreover, the random forest algorithm is used to dynamically obtain and update the label weight of Vehicle Profile because of the problem of label weight existing in the practical application. In addition, the dynamic weight of the Vehicle Profile is introduced into the design of the vehicle payoff function involved in lane change decision, which solves the problem that the weight of each part of the payoff function is used as a parameter. Finally, the performance of the algorithm is tested and verified by SUMO in roundabout general traffic conditions, congested traffic conditions and sparse traffic conditions. The experimental results show that this algorithm can improve the Efficiency and comfort of vehicle driving in general traffic environment more greatly compared with the situation of traffic congestion and sparse traffic flow. Meanwhile, this algorithm verifies the optimization effect of introducing Vehicle Profile on roundabout traffic strategy.
智能网联汽车(ICVs)是在车联网(IOV)和智能汽车的基础上发展起来的,基于车辆-道路-环境协同策略,已成为优化车辆交通、缓解交通拥堵的有效解决方案。本文根据交通环形交叉口车辆的行驶特性,提出了一种基于车辆轮廓(VP)的环形交叉口出口车辆变道策略。针对icv中存在的多源异构数据混合问题,首先定义了车辆轮廓(Vehicle Profile, VP),然后将多源异构数据用VP表示。针对实际应用中存在的标签权重问题,采用随机森林算法动态获取和更新车辆轮廓的标签权重。此外,将车辆轮廓的动态权值引入到变道决策中车辆收益函数的设计中,解决了以收益函数各部分的权值作为参数的问题。最后,通过SUMO在环形交叉口一般交通工况、拥挤交通工况和稀疏交通工况下对算法的性能进行了测试和验证。实验结果表明,与交通拥堵和稀疏交通流情况相比,该算法能更大程度地提高车辆在一般交通环境下的行驶效率和舒适性。同时,该算法验证了引入车辆轮廓对环形交叉口交通策略的优化效果。
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引用次数: 0
Lightweight Federated Reinforcement Learning for Independent Request Scheduling in Microgrids 面向微电网独立请求调度的轻量级联邦强化学习
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00041
Zhuoxi Duan, Yufei Qiao, Sheng Chen, Xinying Wang, Guoliang Wu, Xiaofei Wang
With the development of technology and society, the traditional energy system has become difficult to meet the demand. Applying Deep Reinforcement Learning (DRL) to solve scheduling problems in microgrid cluster edge-cloud collaborative architecture provides a new solution. However, there is no research work has been completed to address the independent training, deployment, and inference of DRL in the microgrid cluster scenario. In this paper, we propose a federated DRL-based request scheduling algorithm for distributed microgrid cluster scenarios with the goal of maximizing the long-term utility of the system. In addition, we prune the DRL model to make it more applicable to resource-constrained edge nodes. The experimental results show that the proposed algorithm has more stable performance and better adaptability to the dynamic system environment compared to the traditional centralized training. In addition, the pruning of the model compresses the size of the model to 50.4% with a 4% loss of accuracy.
随着科技和社会的发展,传统的能源系统已经难以满足需求。应用深度强化学习(DRL)解决微电网集群边缘云协同架构中的调度问题提供了一种新的解决方案。然而,目前还没有针对微网集群场景下DRL的独立训练、部署和推理的研究工作。在本文中,我们提出了一种基于联邦drl的分布式微电网集群请求调度算法,其目标是最大化系统的长期效用。此外,我们对DRL模型进行了精简,使其更适用于资源受限的边缘节点。实验结果表明,与传统的集中训练相比,该算法具有更稳定的性能和对动态系统环境更好的适应性。此外,模型的修剪将模型的大小压缩到50.4%,精度损失4%。
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引用次数: 1
Light Pollution Monitoring Using A Modular IoT Sensor Platform 基于模块化物联网传感器平台的光污染监测
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00014
Reiner N. Dizon-Paradis, Oliver Ferrigno, Ishamor Reid, S. Bhunia
Light pollution, caused by indiscriminate use of artificial lighting at night, is a growing threat to astronomy, the environment, and other fields. Monitoring light pollution can help inform local communities on its impact on their environment, especially nocturnal plants and animals, such as sea turtles. However, existing systems for light pollution monitoring are expensive, non-scalable, and uni-directional, while others are inaccurate and cannot be deployed at a large scale. In this paper, we propose a modular IoT sensor platform called Pasteables with reconfigurable and easily replaceable components. We tailor this sensor platform to use many of the sensors related to monitoring light pollution. It builds upon our previous work that shares the idea of a generic modular sensing platform [1]. Unlike the previous work, we created new designs for the Components for Uniform Interface (CUI) with sensors, including light sensor, temperature/pressure sensor, and GPS. We fabricated PCB proto-types of this Pasteables platform using FR-4 material and surface mount components. Each CUI connects to the base pad using edge connectors to make the CUIs reconfigurable during installation. With these prototypes, we evaluated its responsiveness and sensitivity at two different locations of varying heights for the light source against the least expensive existing solution.
由于夜间不加选择地使用人工照明而造成的光污染,对天文学、环境和其他领域构成了日益严重的威胁。监测光污染可以帮助当地社区了解其对环境的影响,特别是夜间活动的植物和动物,如海龟。然而,现有的光污染监测系统价格昂贵、不可扩展、单向,而其他系统则不准确,无法大规模部署。在本文中,我们提出了一个模块化的物联网传感器平台,称为Pasteables,具有可重构和易于更换的组件。我们定制了这个传感器平台,以使用许多与监测光污染相关的传感器。它建立在我们以前的工作基础上,共享通用模块化传感平台的想法[1]。与之前的工作不同,我们为具有传感器的统一接口组件(CUI)创建了新的设计,包括光传感器,温度/压力传感器和GPS。我们使用FR-4材料和表面贴装组件制作了该Pasteables平台的PCB原型。每个CUI通过边缘连接器连接到底座,使gui在安装过程中可重新配置。通过这些原型,我们评估了它在不同高度的光源的两个不同位置的响应性和灵敏度,而不是最便宜的现有解决方案。
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引用次数: 0
Intelligent Reflecting Surface Enabled in D2D Millimeter Wave Communication 智能反射面在D2D毫米波通信中启用
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00023
Bingjie Han, Xin Chen, D. Guo, Libo Jiao
We propose an intelligent reflecting surface (IRS) enabled millimeter wave (MMW) deviceto-device (D2D) communication in the future B5G/6G scenario to improve throughput. This scheme not only maintains the high transmission rate and low transmitting power of MMW D2D communication, but it also greatly reduces the blocking probability in the presence of assisting IRS. In this paper, we build the system model of IRS-enabled MMW D2D communication and convert it into an IRS activation and selection (IAS) problem which is to find the maximize effective transmission rate through the IRS distribution, then prove that the IAS problem is an NP-hard problem. In addition, we propose an approximation solution named after IAS-A to solve IAS problem efficiently. The experimental results show that the IRS-enabled D2D MMW communication outperforms other cases in terms of throughput and blocking probability, demonstrating the superiority of IAS-A algorithm. The experiment results show that our proposed IAS-A algorithm is 16.59% and 76.17% higher than the shortest distance and random strategies with respect to the total throughput.
在未来的B5G/6G场景中,我们提出了一种智能反射面(IRS)支持的毫米波(MMW)设备对设备(D2D)通信,以提高吞吐量。该方案既保持了毫米波D2D通信的高传输速率和低发射功率,又大大降低了辅助IRS存在下的阻塞概率。本文建立了基于IRS的毫米波D2D通信系统模型,并将其转化为IRS激活与选择(IAS)问题,即通过IRS分布找到最大的有效传输速率,证明了IAS问题是np困难问题。此外,我们提出了一个以IAS- a命名的近似解来有效地解决IAS问题。实验结果表明,支持irs的D2D毫米波通信在吞吐量和阻塞概率方面优于其他情况,证明了IAS-A算法的优越性。实验结果表明,本文提出的IAS-A算法在总吞吐量方面比最短距离策略和随机策略分别提高16.59%和76.17%。
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引用次数: 1
An Algorithm with Smooth Filtering Based on LPC 一种基于LPC的平滑滤波算法
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00028
Yan He, Yaqi Cheng, Weihua Liu, Xingguang Li
Many professions rely on disguised voice techniques. In contrast to the conventional linear prediction-based modification technique, we propose a disguised voice algorithm with smoothing filtering to improve the modification effect by smoothing the changed pitch period. This paper is based on linear prediction. The cepstrum method is used to obtain and change the pitch period of the speech residual signal, applying the smoothing process on the obtained pitch period, and the speech synthesis is realized using a linear prediction synthesis filter to achieve the pitch change with the same speech rate. The results show that the synthesized signal tends to be more clear and natural and the modification effect is better than no smoothing.
许多职业都依赖于伪装的声音技巧。与传统的基于线性预测的修改技术相比,我们提出了一种带有平滑滤波的伪装语音算法,通过平滑变化的音高周期来提高修改效果。本文基于线性预测。利用倒谱法获取并改变语音残差信号的基音周期,对得到的基音周期进行平滑处理,利用线性预测合成滤波器实现语音合成,实现相同语音速率下的基音变化。结果表明,经过滤波处理后的信号更加清晰、自然,滤波后的信号比不滤波效果更好。
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引用次数: 0
Dual Resource Joint Auction Algorithm For 5G Multiple Access Edge Computing With System Utility Guarantee 基于系统效用保障的5G多址边缘计算双资源联合竞价算法
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00039
Zhitian Sun, Xin Chen, Bo Yin, Yijie Wang
Multiple Access Edge Computing (MEC) can provide efficient and low latency computing services for computing tasks generated by mobile devices. How to formulate reasonable and effective resource allocation strategy and pricing strategy to ensure the maximization of overall system utility is a very challenging problem. In order to solve this problem, a dual resource joint auction algorithm (DRJAA) is proposed in this paper. The joint allocation of communication resources and computing resources is modeled as a three-stage parallel auction process considering resource constraints and distance, and a prioritization algorithm is designed to maximize the utility of resource suppliers. Simulation results show that DRJAA algorithm is superior to other existing algorithms in convergence speed, iteration times and transaction success rate, and can effectively reduce user delay.
MEC (Multiple Access Edge Computing)可以为移动设备产生的计算任务提供高效、低延迟的计算服务。如何制定合理有效的资源配置策略和定价策略,以保证系统整体效用的最大化,是一个非常具有挑战性的问题。为了解决这一问题,本文提出了一种双资源联合拍卖算法(DRJAA)。将通信资源和计算资源的联合分配建模为考虑资源约束和距离的三阶段并行拍卖过程,并设计了以资源提供者效用最大化为目标的优先排序算法。仿真结果表明,DRJAA算法在收敛速度、迭代次数和交易成功率等方面优于现有算法,并能有效降低用户延迟。
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引用次数: 1
Co-Scheduling of Quay Cranes and RTGs in the Container Terminal 集装箱码头码头起重机与RTGs的协同调度
Pub Date : 2022-08-01 DOI: 10.1109/SmartIoT55134.2022.00027
L. Chu, Dong Liang, Yupei Zhou, Xiaowei Xu, Yiming Zhang, Zhiying Ruan, Huanbin Xiao, Shiping Zuo
As quay cranes and RTGs are vital handling equipment at container terminals, their scheduling optimization would significantly affect the terminal's operation efficiency and costs. Most of the existing literature mainly studies a single quay crane, RTG dispatch, or the joint dispatch of handling equipment and horizontal transportation equipment, and rarely combines handling equipment at both ends for research. This paper breaks through the traditional scheduling mode of quay cranes or RTGs and takes the integrated and coordinated scheduling of quay cranes and RTGs as the research object. The objective is to minimize the operating cost, waiting for time penalty cost of container trucks, and re-stow cost, establish a comprehensive scheduling optimization mathematical model. Firstly, according to the features of the optimization model, this paper will use GA (Genetic algorithm) method to calculate withMATLAB2018b designing its program. Additionally, data collecting is based on the survey of actual operations in the terminal. Lastly, all data analysis will be under the computer experiment, compared to the actual operations data to identify the operating cost of the collaborative scheduling model is greatly reduced, the feasibility of the optimization model, and the reliability of its algorithm.
作为集装箱码头重要的装卸设备,码头起重机和码头装卸车的调度优化将对码头的运行效率和成本产生重要影响。现有文献大多以单岸起重机、RTG调度或装卸设备与水平运输设备联合调度为主,很少将两端装卸设备结合进行研究。本文突破了传统的码头起重机或码头起重机的调度模式,以码头起重机与码头起重机的集成协调调度为研究对象。以集装箱货车的运行成本、等待时间惩罚成本和再积成本最小为目标,建立综合调度优化数学模型。首先,根据优化模型的特点,本文将使用GA(遗传算法)方法进行计算,并用matlab2018b设计其程序。此外,数据的收集是基于对终端实际操作的调查。最后,将所有的数据分析在计算机下进行实验,与实际运行数据进行对比,确定协同调度模型的运行成本大大降低,优化模型的可行性,以及其算法的可靠性。
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引用次数: 1
期刊
2022 IEEE International Conference on Smart Internet of Things (SmartIoT)
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