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A Novel ZigBee Routing Algorithm Based on Shortcut Routing and Energy Cost Function 3

A Novel ZigBee Routing Algorithm Based on Shortcut Routing a...

引用

3rd IEEE international conference on computer Communication and Artificial Intelligence, CCAI 2023

作者： Yao, XiaoFeng Xu, HuiPu Yang, Lu Xue, Xu DaLian JiaoTong University School of Automation and Electrical Engineering Dalian city China DaLian Maritime University College of Marine Electrical Engineering Dalian city China

ISBN: (纸本)9798350335262

ZigBee routing protocol adopted hybrid routing approach which combined AODVjr and cluster-tree algorithm to better adapt to different network topology. However, the simple combination of two algorithms cannot play a very good role in reduce energy consumption. In this paper, a novel ZigBee routing algorithm based on shortcut routing and energy cost function was introduced after exhaustive research on ZigBee cluster-tree algorithm and routing discovery process of AODVjr algorithm, the new algorithm applied shortcut routing concept based on the cluster-tree neighbor table, find out the nodes among neighbor nodes which can reach to destination nodes with the least hops. Then energy costs of various paths were work out through applying the energy cost function, and then a high reliable path which consumed the minimum energy was selected, which can reduce energy consumption efficiently and prolong the network lifetime. Performance simulation and results analysis were implemented by using the NS-2 network simulation platform, and the simulation results indicated that the improved algorithm has better advantage on average delay and average route cost rate. © 2023 IEEE.

关键词： Zigbee

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Design and Optimization of Intelligent Sorting and Disassembling Equipment for High-Efficiency Lithium Battery 4

Design and Optimization of Intelligent Sorting and Disassemb...

引用

4th international conference on New Energy and Power engineering, ICNEPE 2024

作者： Zhuang, Zhipeng Liu, Xiaoshan Li, Ziwen Luo, Weiqi Jin, Jing Gao, Ge Zhuhai College of Science and Technology College of Life Sciences Guangdong Zhuhai China Zhuhai College of Science and Technology School of Computer Science Guangdong Zhuhai China Zhuhai College of Science and Technology College of Electronic Information Engineering Guangdong Zhuhai China Zhuhai College of Science and Technology College of Business Guangdong Zhuhai China

ISBN: (纸本)9798331516086

The aim of this thesis is to solve the complex exhaust gas problem generated during the dismantling of lithium batteries, and to explore a reasonable, economical and safe exhaust gas treatment process. To this end, a new type of intelligent sorting and dismantling equipment for power batteries has been developed, which combines a variety of advanced technologies in order to improve the effect of exhaust gas treatment. The comprehensive treatment program adopted in this equipment includes several treatment units such as cyclone dust collector, CFB semi-dry deacidification tower, cartridge dust collector, wet deacidification tower, gas-water separator, RTO combustion furnace, rapid cooling tower, alkali washing tower and water washing tower. The synergistic work of these equipments can effectively remove chlorine- and fluorine-containing organic waste gases and ensure that the waste gas emissions during the dismantling process comply with environmental protection standards. Specifically, the design of the equipment is divided into the end-of-life, transit, recycling, treatment and application ends, through the introduction of visual recognition technology to improve sorting accuracy, the use of exhaust gas purification technology and dust automatic collection devices to ensure the efficiency of the treatment, combined with the MES system and Automated Guided Vehicle to achieve a high degree of automation. © 2024 IEEE.

关键词： Dust collectors

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Attention-Based Randomized Ensemble Multi-Agent Q-Learning 23

Attention-Based Randomized Ensemble Multi-Agent Q-Learning

引用

23rd international conference on Control, automation and Systems, ICCAS 2023

作者： Park, Jeongho Kwon, Obin Oh, Songhwai Seoul National University Department of Electrical and Computer Engineering and Asri Seoul08826 Korea Republic of

ISBN: (纸本)9788993215274

Cooperative multi-agent scenarios are prevalent in real-world applications. Optimal coordination of agents requires appropriate task allocation, considering each task's complexity and each agent's capability. This becomes challenging under decentralization and partial observability, as agents must self-allocate tasks using limited state information. We introduce a novel multi-agent environment in which effective sub-task assignment is crucial for high-scoring performance. In addition, we propose a new multi-agent reinforcement learning framework named as attention-based randomized ensemble multi-agent Q-learning, or AREQ for short. This approach integrates a unique network structure using a multi-head attention mechanism, efficiently extracting task-related information from observations. AREQ also incorporates a randomized ensemble method, enhancing sample efficiency. We explore the impact of this attention-based structure and the random ensemble method through an ablation study and show AREQ's superiority compared to existing MARL methods within our proposed environment. © 2023 ICROS.

关键词： Reinforcement learning

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Automated Smart Home Security System Using Biometric Solution 7

Automated Smart Home Security System Using Biometric Solutio...

引用

2023 7th international conference On Computing, Communication, Control And automation, ICCUBEA 2023

作者： Bhardwaj, Rishabh Kothiyal, Raj Sharma, Sachin Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350304268

Security is a process;it's an ongoing endeavor to keep one step ahead of threats and safeguard what matters most. Security is not a product. Everybody can find shelter in a home, which offers a sense of security and stability. Its security is crucial for defending belongings against potential dangers including break-ins and burglaries, which may increase the risk of theft, burglary, and property damage, resulting in financial and emotional suffering. In this study, we analyze these issues, pinpoint potential remedies, and offer predictions about the development of smart home security. In order to improve the safety and security of houses more effectively than some of the current accessible alternatives, an effective home security system technology is a crucial first step. This investigation assesses the current state of IoT security, identifies the issues encountered, and proposes workable solutions in order to increase the security of IoT systems and devices. A person is found using a PIR motion sensor. The YOLO method is used to identify the images that are captured by the camera module. Depending on the circumstance, electromagnetism is opened using a Raspberry Pi. The user is received the last notification regarding cloud-based door opening. © 2023 IEEE.

关键词： automated biometric Internet of Things Privacy security Smart home

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Weather Prediction on Different LSTM Techniques for Time Series Data in Chennai, India

Weather Prediction on Different LSTM Techniques for Time Ser...

引用

2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Tk, Harikishan Sasikiran, S. Manoj Kumar, G. Joseph, Ferdin Joe John Sathiyanarayanan, Mithileysh Srm Institute of Science and Technology Student of Computer Science and Engineering Ramapuram Campus Chennai India Thai-Nichi Institute of Technology Thai-Nichi International College Bangkok Thailand Research & Innovation Mit Square London United Kingdom

ISBN: (纸本)9798350317060

The prediction of weather has always been an integral factor in our lives as it determines if the day of activity leads to favorable or unfavorable conditions. The existence of different deep learning models has facilitated several major problems which without such techniques would have been a very time-consuming and exhaustive process. In this following paper, we explore various types of LSTM models and analyze which among them provides the best fit for the Time Series data that is present in the Weather data. Upon gathering the datasets, a strategy called Long Short-Term Memory (LSTM) is carried out. LSTM is a deep learning model which is primarily focused on time-series data. By employing such technical improvisations on the same data with multiple models each with their own unique characteristics, we can ultimately determine the best model which has an overall better accuracy. Based on the metrics produced by employing each technique, it is found that our LSTM model which proposed here has the best performance in terms of predicting the data with an overall low error rate and loss during the training phase. © 2023 IEEE.

关键词： Long short-term memory

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SFMatting-800: A Multi-Scene Smoke and Fire Image Matting Dataset for Fine-Grained Fire Detection 4

SFMatting-800: A Multi-Scene Smoke and Fire Image Matting Da...

引用

4th international conference on Artificial Intelligence and computer engineering, ICAICE 2023

作者： Ma, Shihui Ding, Kun Yan, Hongping School of Information Engineering China University of Geosciences Beijing Beijing China Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400708831

Fire is a disastrous event that causes immense dangers. Conventional fire detection methods use sensors in indoor settings. By contrast, computer vision-based methods have made substantial advancements in terms of detection accuracy, speed, and versatility. However, existing approaches often treat fire detection as image classification, image segmentation, and object detection problems, overlooking the characteristic of smoke, including its floatability, ambiguity, and transparency. To foster advancements in this field, we formalize fire detection as the image matting problem and introduce a novel smoke and fire matting dataset SFMatting-800. This dataset not only features high-quality annotations on transparency but also encompasses diverse information regarding scene types and fire attributes. These annotations serve as valuable resources for training, evaluating image matting models, and expanding data through compositing with a substantial background dataset. With SFMatting-800, we have conducted comprehensive evaluations using traditional image matting methods, trimap-based and trimap-free deep image matting methods. The experimental results not only demonstrate the value of our dataset for the fine-grained fire detection task, but also help to expose the problem of existing matting methods in processing extensive regions with high transparency and misidentification between background and targets. The dataset will be made publicly available. © 2023 Owner/Author.

关键词： Fires

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Research on High Precision Point Cloud Registration Algorithm in Dynamic Environment 3

Research on High Precision Point Cloud Registration Algorith...

引用

3rd international conference on computer, Control and Robotics, ICCCR 2023

作者： Li, Hao Qian, Donghai Liu, Guangyin Zhao, Wei School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9781665492126

The localization technology based on Lidar is an important method to realize the precise localization and navigation of unmanned vehicle, and it is also the premise to realize the application of unmanned vehicle in more fields. In many application scenarios, dynamic objects may interfere with precise localization, resulting in degeneration of Lidar localization accuracy or even failure. This paper proposes an accurate point cloud registration algorithm for dynamic environment. Firstly, the point cloud is roughly registrated to obtain the rough pose estimation, and the potential dynamic object point cloud is segmented, then it is removed from the original point cloud. Finally, based on the corrected point cloud, the high-precision point cloud registration is performed with the pose obtained by the rough pose estimation as the initial pose, so as to obtain the accurate pose estimation of the unmanned vehicle. The method is applied to Lidar to realize the fast and high-precision lidar localization of Ackerman unmanned vehicle in dynamic environment. The algorithm is verified in the campus environment. The results show that the algorithm is reliable and effective in the dynamic environment, and is superior to the common point cloud registration algorithm. © 2023 IEEE.

关键词： Optical radar

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Design and PID Control of a Lower Limb Exoskeleton for Virtual Reality-Based Telerehabilitation 11

Design and PID Control of a Lower Limb Exoskeleton for Virtu...

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11th international conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Aktan, Mehmet Emin Falkowski, Piotr Zawalski, Krzysztof Jeznach, Kajetan Ömürlü, Vasfi Emre Akdoǧan, Erhan Bartin University Department of Mechatronics Engineering Bartin Turkey Health Institutes of Türkiye Istanbul Turkey Industrial Research Institute for Automation and Measurements Piap Lukasiewicz Research Network Warsaw Poland Yildiz Technical University Department of Mechatronics Engineering Istanbul Turkey

ISBN: (纸本)9798331509293

Rehabilitation is a critical process that enables people who have lost motor skills to regain their physical abilities. Exoskeletons offer innovative solutions to accelerate the functional recovery of patients and increase the effectiveness of treatment. The integration of virtual reality and biological signal processing technologies into such systems allows the user's movements to be detected in real time with high accuracy, enabling remote and personalised treatment. This study explains the working principle and control structure of a 4-degree-of-freedom lower limb exoskeleton robot developed for virtual reality-based telerehabilitation. The details of the electrical components of the system such as controller, input and output units, motor, sensor, virtual reality goggles, EEG and EMG devices and their interrelationships are explained. The position control performance for each joint using the PID control method is analysed. The results show that the exoskeleton can follow the given target trajectories with different error values depending on the period and joint. A maximum position error of 0.659 degrees was observed in the hip flexion-extension joint, while the average error for this joint was recorded as 0.385 degrees. © 2025 IEEE.

关键词： Functional neural stimulation

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A 5G-TSN Joint Scheduling Mechanism Considering Finite Buffer in DS-TT 9

A 5G-TSN Joint Scheduling Mechanism Considering Finite Buffe...

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9th international conference on computer and Communications, ICCC 2023

作者： Hu, Xinyu Sun, Lei Li, Wei Wang, Jianquan University of Science and Technology Beijing Insititute of Industrial Internet Beijing100083 China University of Science and Technology Beijing School of Computing and Communication Engineering Beijing100083 China University of Science and Technology Beijing School of Automation and Electrical Engineering Beijing100083 China

ISBN: (纸本)9798350317251

With the advent of Industry 4.0, 5G and Time Sensitive Networking (TSN) are emerging as wireless deterministic communication network to provide solid QoS guarantee for industrial automation services. For 5G-TSN collaboration system, two important gateways are introduced in both network and end device side to support TSN protocols, named as Network-side TSN Translator (NW-TT) and Device-side TSN Translator (DS-TT) respectively. However, 5G and TSN are totally different in terms of resource type, scheduling methodology and management protocols, in order to provide latency guarantee for time-triggered flows across 5G and TSN, as well as to make two different scheduling of 5G and TSN coordinately, a 5G-TSN joint scheduling mechanism based on enhanced Maximum Latency Weighted Delay First (eMLWDF) is proposed and analyzed in this paper. The proposed mechanism designs an adaptive factor in scheduling procedure to make well balance between achieving low latency in 5G and avoiding buffer overflow in DS-TT. Furthermore, some packet will arrival at the priority queue in DS-TT later than the period of "ON"for that queue due to fluctuations of radio channel, to avoid this situation, a frame preemption scheme is adopted to provide latency guarantee. Simulation results demonstrate that the proposed mechanism can satisfy the latency requirements of time-triggered flows as well as reduce data buffer volumes in DS-TT, aiming to provide deterministic communication guarantee for data transmission across 5G and TSN. © 2023 IEEE.

关键词： Machine design

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Dynamic Modeling of Strip Rolling Process Using Probabilistic Neural Network

Dynamic Modeling of Strip Rolling Process Using Probabilisti...

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18th IEEE international conference on Advanced Motion Control, AMC 2024

作者： Deng, Jifei Sierla, Seppo Sun, Jie Vyatkin, Valeriy Northeastern University State Key Laboratory of Rolling and Automation Shenyang China Aalto University Department of Electrical Engineering and Automation Espoo Finland Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden

ISBN: (纸本)9798350342819

This paper proposes an intelligent dynamic modeling method for strip rolling process. Actuators of a cold rolling mill perform actions, including work roll bending, intermediate roll bending, and roll gap tilting, to regulate the product quality. Conventional first-principles modeling necessitates intricate mathematical equations derived from process analysis and action evaluation. However, the complexity of the model increases the difficulty of upgrading the model. To address this limitation, a novel approach involving a deep neural network with a Gaussian distribution layer is proposed to effectively capture the process dynamics. A negative log likelihood is established as the loss function for the model using real-world industrial data. Experiment outcomes demonstrate the efficacy of the proposed method in achieving an accurate dynamic model. © 2024 IEEE.

关键词： Deep neural networks

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