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Smart Water Taps Using IoT Sensors and Deep Reinforcement Learning for Personalized Consumption control 6

Smart Water Taps Using IoT Sensors and Deep Reinforcement Le...

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6th international conference on Energy, Power and Environment, ICEPE 2024

作者： Varadarajan, Mageshkumar Naarayanasamy Vinya, Viyyapu Lokeshwari Prabhu, R. Jenin Swathi, G. Mohankumar, N. Velmurugan, S. Capital One Tamil Nadu Chennai India Vardhaman College of Engineering Department of Computer Science and Engineering Telangana Ranga Reddy India Vel Tech Multi Tech Dr. Rangarajan Dr. Sakundhala Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Cmr Technical Campus Department of Computer Science and Engineering Telangana Hyderabad India Maharashtra Nagpur India T.J.S. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350379297

this research introduces an innovative approach to water conservation and personalized consumption management by combining Internet of things (IoT) sensors with Deep Reinforcement Learning (DRL) methods. the suggested approach aims to give people more control over their water use in response to water shortages and the need for sustainable resource management. It installs IoT sensors on taps to track water use in real time. A DRL framework is fed data that these sensors have collected. the DRL algorithm develops individual consumption profiles for each user by factoring in past water use, environmental conditions, and personal tastes. Using this unique profile, water efficiency may be improved instantly. Users may easily enter their water conservation choices, budgets, and the system's user interface. Adjusting the water's flow rate by the user profiles learned by the DRL actively regulates water use while keeping people happy. the results of the experiments reveal that our method effectively reduces both water use and waste. Integrating IoT sensors with DRL methods provides a flexible and scalable answer for smart water management that economically benefits the environment and consumers. © 2024 IEEE.

关键词： Deep reinforcement learning

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MR Meets Robotics: A Review of Mixed Reality Technology in Robotics 6

MR Meets Robotics: A Review of Mixed Reality Technology in R...

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6th international conference on Robotics, control and automation (ICRCA)

作者： Yu, Jiawei Wang, Tengyue Shi, Yunze Yang, Liangjing Zhejiang Univ Zhejiang Univ Univ Illinois Urbana Champaign Inst Haining Peoples R China

ISBN: (纸本)9781665481748

the rising interest in Mixed Reality (MR) technology in robotics and the lack of prior work in the literature of this subject motivate this review paper. Our purpose is to discuss current research and the advancement of MR applications in the context of robotics. Development in modern robots towards a more human-centric role is driven largely by enabling technology including, but not limited to, machine vision, cobots, virtual reality, and more recently, MR technology. the scope encompasses MR technology in various aspects of robotics, namely, robot vision, control and planning, human-robot interaction, multi-user collaborations, and swarm robotics. through discussions of the benefits and knowledge gaps in contemporary development, the review is expected to provide readers with an in-depth appreciation of the state-of-the-art technology and the possibility of MR technology in robotics.

关键词： mixed reality robotics visualization teleoperation and control

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Research on Depth Estimation Method of Single Aerial Image 6

Research on Depth Estimation Method of Single Aerial Image

引用

6th IEEE Information Technology, Networking, Electronic and automation control conference, ITNEC 2023

作者： Gao, Wang Pu, Lin Li, Lei Deng, Fei Bie, Lingzhi Beijing Institute of Mechanical and Electrical Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Wuhan University School of Geodesy and Geomatics Wuhan China Wuhan Tianjihang Information Technology Co. Ltd Wuhan China

ISBN: (纸本)9781665460033

Aiming at the problem that the current depth estimation of single image mostly uses the ground public data set, and there is less research on aerial images, this paper uses the collected visible and infrared aerial image data sets to study the depth estimation. We used FCRN and LapDRN to extract the depth estimation results of visible aerial image and infrared aerial image under global and single object respectively, and compared the results extracted from the two types of networks by qualitative and quantitative methods. the results show that the depth estimation accuracy of visible aerial image is higher than that of infrared image, but the increase rate of infrared image accuracy index is higher than the increase rate of image depth range. the image depth estimation results extracted by LapDRN method are superior to FCRN in accuracy, structure consistency and edge clarity, which indicates that LapDRN is more effective in the estimation of aerial image depth information. © 2023 IEEE.

关键词： Antennas

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Research on Multi-operating Point control Strategy of Extended Range Electric Vehicle Engine 6

Research on Multi-operating Point Control Strategy of Extend...

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6th international conference on Energy, electrical and Power engineering, CEEPE 2023

作者： Wang, Wei Li, Wenbo Qu, Fufan Cai, Jiawen Wang, Penglong Zheng, Hong Co. Ltd. Dongli District Tianjin300300 China College of Mechanical Engineering Tianjin University of Science and Technology Tianjin300000 China

ISBN: (纸本)9798350348279

Aiming at the problem of the influence of the control of the operating state of the extended-range electric vehicles (EREVs) engine on the fuel economy of the whole vehicles, this paper studies the multi-operating point control strategy of the extended-range electric vehicles engine. Firstly, the driving motor model, generator model, engine model and power battery model of extended range electric vehicles are established. Further, the vehicle control model and engine multi-operating point control model are built on the MATLAB/Simulink platform. through co-simulation with VPAT, the effectiveness of vehicle control strategy and engine multi-point control strategy is verified in WLTC operating condition. the results show that the fuel consumption per 100 km is about 2% lower and the comprehensive energy utilization efficiency is 3% higher than that of the single working point control strategy under WLTC condition, and the expected effect is achieved. © 2023 IEEE.

关键词： Fuel economy

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A Universal control Strategy Enabling 1-ph/3-ph Operation for three-Phase Four-Wire PFC Rectifier in On-Board Chargers 6

A Universal Control Strategy Enabling 1-ph/3-ph Operation fo...

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6th IEEE international electrical and Energy conference, CIEEC 2023

作者： Yuan, Ziheng Chen, Peng Wu, Zhouyu Li, Helong Yang, Zhiqing Zhao, Shuang Yu, Zixiang Ding, Lijian Wang, Lijun Huo, Wei School of Electrical Engineering and Automation Hefei University of Technology Hefei China Oakforesee Intellimobile Tech CO. Ltd Hefei China

ISBN: (纸本)9798350346671

To enable operation with both three-phase and single-phase power grid, three-phase (3-ph) four-wire power factor correction rectifiers (PFCs) are widely used for on-board chargers. Conventionally, the PFC rectifier is regulated with three independent boost modes for the three-phase operation, while with totem-pole mode for the single-phase (1-ph) one. the control structure for the 1-ph/3-ph are different, which leads to additional effort for the control design. In this work, a universal control strategy enabling 1-ph/3-ph operations for three-phase four-wire PFC rectifiers is proposed. When switching to the single-phase operation, the third phase is modulated with the switching frequency, which is able to regulate the current distribution between the phase and neutral line. As a result, the current stress on the cables and power devices can be balanced, leading to a more efficient design. Besides, the voltage feedforward and deadtime compensation are also considered to improve the dynamics and increase the input power quality. Finally, the feasibility of the proposed control strategy is verified by simulation. © 2023 IEEE.

关键词： Power quality

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PIGWN: Physics-Informed Graph WaveNet for Airport Flight Traffic Flow Prediction 6

PIGWN: Physics-Informed Graph WaveNet for Airport Flight Tra...

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6th international conference on Industrial Artificial Intelligence, IAI 2024

作者： Yang, Zhichao Zhu, Yinghao Niu, Ziyue Huang, Yanru Pan, Chengwei Dong, Xiwang School of Artificial Intelligence Beihang University Beijing China China Academy of Launch Vehicle Technology Beijing China School of Artificial Intelligence Institute of Unmanned System School of Automation Science and Electrical Engineering Beijing China Beihang University Science and Technology on Aircraft Control Laboratory Beijing China

ISBN: (纸本)9798350356618

the continuous growth of global travel demand leads to the continuous rise of airport flight flow, leading a rising need to accurately predict the airport flight traffic flow. Current research predominantly employs Graph Convolutional Neural Networks (GCN) to model intra-airport traffic changes, but overlooks comprehensive modeling of air traffic routes and temporal dimensions. Furthermore, existing models rely on data-driven approaches lacking a deep understanding of traffic change mechanisms, resulting in poor performance in new scenarios. To solve these problems, we propose a deep learning network framework Physics-Informed Graph WaveNet (PIGWN) based on multi-scale feature data fusion and constructs two new airport domain data sets. We integrated a physics-based module prior to GraphWaveNet to learn and integrate multi-scale spatio-temporal information of airports, embedding physical formulas reflecting airport traffic changes. the physics learning module fuses multi-scale spatio-temporal feature data considering the time delay and traffic conservation relationship between different airports. the Graph WaveNet (GWN) structure learns and predicts multi-scale spatio-temporal feature data, and uses the time-space convolution block model to capture and model spatio-temporal features. PIGWN model has certain theoretical significance and practical application value in the field of airport flight flow prediction, which realizes the accurate prediction of airport flight flow and provides certain decision support and reference for air traffic management. We have made the code publicly available at https://***/yzc0912/PIGWN. © 2024 IEEE.

关键词： Data fusion

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Calculation Method and Verification of Short-circuit Current for Energy Storage System Connected to Power Grid Considering Fault Ride through control 6

Calculation Method and Verification of Short-circuit Current...

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6th international conference on electrical engineering and control Technologies, CEECT 2024

作者： Huo, Qidi Tang, Xiaojun Xu, Wenjia Wang, Ziqi Xie, Yan Wang, Qing Power System Research Institute China Electric Power Research Institute Co. Ltd. Beijing China

ISBN: (纸本)9798331528096

Under the guidance of the '3060 carbon peak and carbon neutrality' policy, new energy capacity has developed. the scale of energy storage installed capacity is also rapidly increasing in sync. Electrochemical energy storage has increased rapidly by more than 90 % in two years. the proportion of energy storage in the power system is increasing, which makes it difficult to obtain the short-circuit current accurately, and seriously affects the protection setting and the verification of switch safety breaking ability. the principle of providing current of BESS is very different from that of traditional synchronous units, and cannot be simply copied from the calculation method of traditional synchronous generators. the widely used national standard system for short-circuit current calculation based on IEC 60909 standard has not yet taken into account the contribution of BESS to AC short-circuit current. At the same time, lack of short-circuit current calculation methods for switch selection and safety verification of energy storage power stations and access systems. this section intends to propose current calculation model and method for BESS and access systems, in order to work our accuracy of calculation for BESS and access systems, and provide support for switch selection, safety verification, and other work © 2024 IEEE.

关键词： Short circuit currents

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Online Evolutionary Maximum Power Point Tracking for Photovoltaic Grid-connected System 6

Online Evolutionary Maximum Power Point Tracking for Photovo...

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6th IEEE international electrical and Energy conference, CIEEC 2023

作者： Tian, Luyu Dong, Chaoyu Xiong, Bingyu Li, Xiangke Mu, Yunfei Jia, Hongjie School of Electrical and Information Engineering Tianjin University Tianjin300072 China Nanyang Technological University Agency for Science Technology and Research 639798 Singapore School of Automation Wuhan University of Technology Wuhan430072 China The Hong Kong Polytechnic University Department of Electrical Engineering Hong Kong

ISBN: (纸本)9798350346671

the utilization of clean energy is increasing because of energy shortage. Meanwhile, the advancement of photovoltaic grid-connected technology has emerged as one widespread approach both domestically and internationally as a crucial component of microgrids. thus, this study proposes an online evolutionary strategy for photovoltaic maximum power point tracking to fully utilize the solar energy in grid-connected photovoltaic and realize adaptive adjustment of maximum power point tracking control facing environmental dynamics. In this study, the conventional regulation is upgraded into an online evolutionary approach, which deploys incremental adjustment and deep learning. A deep neural network is proposed to continuously modify the weight matrix, which adaptively tunes tracking parameters. In addition, a two-stage single-phase grid-connected photovoltaic inverter is designed with environmental dynamics. the proposed strategy of online evolutionary maximum power point tracking is demonstrated on photovoltaic panels under different solar conditions. the experimental results present that the developed evolutionary approach can overcome the shortcomings of traditional maximum power point tracking, which accelerates the response speed and reduces the power fluctuation under external disturbances. © 2023 IEEE.

关键词： Solar energy

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PM2.5 Concentration Prediction Based on Coupling Multivariable Parameters LSTM 6

PM2.5 Concentration Prediction Based on Coupling Multivariab...

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6th international conference on Information science, electrical, and automation engineering, ISEAE 2024

作者： Zheng, Dezhi Zheng, Jinxiong Lu, Shijia Li, Zhongxiang Peng, Peng Liu, Bei Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology Beijing100081 China Yangtze Delta Region Academy Beijing Institute of Technology Jiaxing314019 China MIIT Key Laboratory of Complex-Field Intelligent Exploration Beijing Institute of Technology Beijing100081 China Chongqing Caeri Robot Technology Co. Ltd. Chongqing400722 China Beijing Research Institute of Telemetry Beijing100076 China

ISBN: (纸本)9781510682924

As one of the major air pollutants, PM2.5 poses serious threats to human health and daily life. Improving the accuracy of PM2.5 predictions is of significant importance for pollution control, as it can effectively reduce its harmful impact. Long Short-Term Memory (LSTM) networks are capable of handling long-term dependencies and are commonly used for modeling and remembering long sequence data, making them a key tool for PM2.5 prediction. Existing LSTM models often use a single parameter for PM2.5 prediction, without considering the coupling effects of multiple meteorological factors with different pollutants and their concentrations. Additionally, using a single optimization algorithm may lead to optimization parameters getting stuck in local optimal solutions, disrupting the optimization results. In this study, multiple meteorological factors highly correlated with PM2.5 data using Pearson correlation coefficients (PCCs) and pollutants with concentrations were selected to construct a coupled correlation model. Furthermore, to improve the reliability of optimization results, the Sparrow Search Algorithm (SSA) with strong local search capability and the Particle Swarm Optimization algorithm (PSO) with strong global search capability were employed to simultaneously optimize LSTM hyperparameters and obtain the optimal solution. Using hourly meteorological data from multiple stations in Beijing from March 1, 2013, to February 28, 2017, as the data source, the SSA-PSO algorithm was used to obtain the optimal solution for network hyperparameters. the coupled correlation model of multiple meteorological parameters with multiple pollutants and concentrations was established. the research results indicate that considering the coupled correlation model of meteorological parameters with pollutants and concentrations can effectively improve the prediction accuracy of PM2.5, and the more types of input parameters, the higher the model prediction accuracy. the R2 of the coupled

关键词： Health risks

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Dynamic Modeling and Strategic Prioritization of Sustainable Development Goals 6

Dynamic Modeling and Strategic Prioritization of Sustainable...

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6th international conference on Software engineering and Computer science, CSECS 2023

作者： Gao, Yixin Huang, Fanding Wang, Xinhua Qiu, Zheyong School of Information Management Hangzhou Dianzi University Hangzhou China School of Automation Hangzhou Dianzi University Hangzhou China School of Computer Hangzhou Dianzi University Hangzhou China School of Science Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9798350306378

this paper introduces a novel dynamic modeling framework that integrates nonlinear programming and state transition graph algorithms to analyze the temporal progress and prioritization of Sustainable Development Goals (SDGs). the framework takes into account the complex interdependencies among SDGs to minimize the overall completion time while max-imizing policy balance. the state transition graph algorithm enhances the widely used Analytic Hierarchy Process (AHP) model by simulating network dynamics and optimizing the activation or introduction of goals. Empirical findings demonstrate a notable shift in prioritization, with SDG3 (Good Health and Well-being) emerging as the foremost priority by the year 2027. Additionally, the study proposes the incorporation of biodiversity conservation as an objective in the year 2031 to further bolster the achievement of SDGs. By providing valuable insights, this research offers a robust decision-making framework that facilitates informed policy formulation for policymakers and stakeholders engaged in sustainable development initiatives. Moreover, it contributes to a deeper understanding of the progress of SDGs, enabling more effective interventions and fostering sustainable development. © 2023 IEEE.

关键词： Nonlinear programming

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