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Design of Integrated Robotic System for Object Recognition and intelligent Grasping based on STM32 4

Design of Integrated Robotic System for Object Recognition a...

引用

4th ieee international conference on Power, intelligent Computing and systems, ICPICS 2022

作者： Gu, Zhihao Wang, Meng Peng, Huaibo School of Electrical Engineering and Automation Harbin Institute of Technology Institute of Technology Harbin China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

With the development of intelligent robots and the proposal of 'Industry 5.0', the intelligent robotic systems have been increasingly used in industrial scenarios. However, the current robotic grasping system is facing a series of problems, including low integration, low movability and limited application scenarios. To counter these problems, this paper designs an integrated robotic system for object recognition and intelligent grasping, consisting of an STM32F405RGT6 microcontroller board, path planning module, object recognition and intelligent grasping module, and environmental monitoring and communication module. This paper details the framework, the hardware and software design of the robotic system respectively. The results show that the robotic system achieves the design goal and realizes robust intelligent recognition and automatic grasping in a constantly moving process with high accuracy, stability and information-based degree. © 2022 ieee.

关键词： Internet of things

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intelligent Route Planning for Post-Earthquake Rescues Using IoT 6

Intelligent Route Planning for Post-Earthquake Rescues Using...

引用

6th international conference on Electrical Engineering and Information and Communication technology, ICEEICT 2024

作者： Tamzid, Rahat Mahee, Ehfaz Faisal Rahman, Ashikur Tamanna, Tahira Akhtar Rahman, Muntasir Hossain, Md. Mamun Bangladesh University of Business and Technology Dept. of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350385779

Starting rescue operations quickly after an earth-quake is the best way to save lives in such disasters. In the case of large-scale earthquakes, current post-earthquake response systems cannot determine which building or rescue route would save the most lives due to the lack of real-time data availability. Research gaps include a lack of automation in earthquake damage assessment of buildings, location identification, and estimation of the number of trapped people. To fill these gaps, this article proposed an innovative solution using advanced sensors and cloud services for post-earthquake rescue route planning systems. This system aims to improve rescue operations to save the maximum number of lives in the shortest time and minimize impacts by optimizing resource allocation and overall response efficiency. By filling the existing research gap, our system seeks to provide more responsive and effective solutions to post-earthquake emergencies. Tested in a simulated environment with 16 samples, our system successfully collects and processes data from IoT devices deployed in buildings, classifies structural damage, and estimates the number of people affected. Our approach significantly reduces the time required to initiate rescue operations by providing rescuers with optimized routes to disaster sites, which has potential implications for disaster management strategies. © 2024 ieee.

关键词： Earthquakes

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Prediction of Silicon Content in Molten Iron of Blast Furnace Based on Multi-dimensional Sequential Characteristic Reconstruction

Prediction of Silicon Content in Molten Iron of Blast Furnac...

引用

Industrial cyber-Physical systems (ICPS)

作者： Zhuofu Zhang Weihua Cao Jie Hu Qifu Chen Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Molten iron is the primary output of blast furnace production. The content of silicon in molten iron clearly correlates with blast furnace temperature. However, due to the intricate conditions of blast furnace production, the silicon content in molten iron is nonlinear and unstable. Therefore, this paper adopts variational mode decomposition (VMD) to decompose and extract the feature information of the real silicon content data of LY Steel in March 2022, then uses Grey Wolf optimization (GWO) algorithm to optimize the parameters of the support vector regression (SVR) prediction model, and takes the decomposed data as model input for experimental verification. By comparing the predicted results with the real historical data of blast furnace production, it is found that the degree of fit is about 94.2%, which offers a new idea for the prediction of silicon content.

关键词： Support vector machines Production Predictive models Blast furnaces Prediction algorithms Feature extraction Silicon

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Risk Assessment for Power Grid Infrastructure Projects based on Graph Attention Networks 3

Risk Assessment for Power Grid Infrastructure Projects based...

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3rd ieee international conference on intelligent technology and Embedded systems, ICITES 2023

作者： Han, Bin Sun, Bo Yu, Lei Qiu, Xin Liu, Kun Huang, Hao Peng, Qiwei Hao, Xiaolong State Grid Electric Power Research Institute Nanjing NARI Information and Communication Technology Co. Ltd Nanjing China State Grid Shanghai Electric Power Company Engineering Construction Consulting Branch State Grid Shanghai Municipal Electric Power Company Shanghai China

ISBN: (纸本)9798350343755

Current risk assessment methods of power grid infrastructure projects are limited to the post-incident stage, while less research has been conducted on the pre-construction risk assessment for power grid infrastructure projects. To address this limitation, this paper proposed a pre-construction risk assessment method based on the Graph Attention Networks (GAT) model, which can consider the coupling relationship between projects. Firstly, a pre-construction risk assessment index system for power grid infrastructure projects was constructed to extract their nodal features. Secondly, we built the relationship network to extract two types of relationships between projects. Thirdly, we proposed the GAT model based on each type of relationship to predict the risk level of the project. Finally, the final evaluation results were obtained after combining model outputs based on each edge type. The empirical results showed that this method can quickly and accurately evaluate the risk level of power grid infrastructure projects before construction. © 2023 ieee.

关键词： Risk assessment

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A UAV Communication System Based on Anti-Interception and Anti-Interferencetechnology

A UAV Communication System Based on Anti-Interception and An...

引用

2023 ieee international conference on Unmanned systems, ICUS 2023

作者： Liu, Xin Li, Rong Li, Pengjie Chen, Xiaofei Li, Sha Wang, Fei Space Star Technology CO. LTD. Market Department Beijing China Xi'an Aerospace Remots Sensing Data Technology Corporation Information Transmission and Processing Business Division Xi'an China Space Star Technology CO. LTD. Information Transmission and Processing Business Division Beijing China

ISBN: (纸本)9798350316308

The application scenarios of unmanned aerial vehicle(UAV) systems require higher requirements for payload miniaturization, range time, beyond line of sight communication, and low-cost. The advancement of intelligent technologies such as unmanned aerial vehicle system cluster technology, autonomous control technology, and collaborative technology has become the main direction of battlefield confrontation for unmanned aerial vehicle systems. The unmanned aerial vehicle communication system based on Tactical Targeting Network technology (TTNT) has the advantages of no center, multi hop communication, distributed deployment, and flexible networking, making it an important communication method for unmanned platform digital battlefield. This article is based on the TTNT unmanned aerial vehicle system, adopting a frequency hopping and time hopping(FHTH) anti-interception and anti-interference communication system to improve information transmission rate. Combining with actual communication scenarios, a physical testing environment is built to complete anti-interception and anti-interference performance experiments and transmission performance analysis. © 2023 ieee.

关键词： Unmanned aerial vehicles (UAV)

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Short-Term Multivariate Load Forecasting for Integrated Energy systems Based on BIGRU-AM and Multi-Task Learning 1

Short-Term Multivariate Load Forecasting for Integrated Ener...

引用

1st international conference on cyber-Energy systems and intelligent Energy, ICCSIE 2022

作者： Sun, Qianxiang Ma, Hongyuan Li, Guangdi Li, Ziwen Wang, Yining Northeastern University School of Information Science and Engineering Shenyang China

ISBN: (纸本)9781665452151

Complex strong coupling relationships may exist among multiple loads in an integrated energy system, and accurate multivariate load forecasting plays an important role in energy scheduling and operation planning of integrated energy systems. Therefore, this paper proposes a short-term multivariate load forecasting model for integrated energy systems based on bidirectional gated cycle unit (BIGRU), multi-task learning (MTL) and attention mechanism (AM). Firstly, considering the coupling characteristics between the electric, heating and cooling loads of the integrated energy system, the PCC method is used to screen the input variables of the prediction model and reduce the dimensionality of the input features of the prediction model;then the attention mechanism is introduced into the BIGRU model based on multi-task learning, which further mines the coupling features between loads through multi-task learning, compensates for the insufficient mining and utilization of coupling features between loads, and achieves the differentiated extraction of important features in the shared layer by each sub-task through the attention mechanism, which improves the prediction accuracy of the model;finally, using the historical data of electric, cooling and heating loads of Arizona State University Tempe campus as the actual arithmetic example, the reasonableness and validity of the model were verified by simulation comparison. © 2023 ieee.

关键词： Learning systems

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IoT Enabled Hybrid PV Powered PMSM Drive for E-Compressor systems 3

IoT Enabled Hybrid PV Powered PMSM Drive for E-Compressor Sy...

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3rd ieee international conference on intelligent Technologies, CONIT 2023

作者： Byri Manoj, S. Sanjay, K. Banerjee, Swapnil Dattatarya, K. Raja Singh, R. Vellore Institute of Technology Vellore Dept. of Electrical and Electronic Engg. Vellore India Cognizant Pune India Vellore Institute of Technology Vellore Dept. of Energy and Power Electronics Vellore India

ISBN: (纸本)9798350338607

Solar PV powered air conditioning system provides an effective means to minimize energy usage and foster sustainability. While also reducing their environmental impact by utilizing renewable energy sources. This paper presents a novel approach for designing an Internet of Things (IoT) enabled hybrid photovoltaic (PV) powered permanent magnet synchronous motor drive for E-compressor systems. The IoT-enabled system allows for real-time monitoring and control of the available solar energy. The system is designed to improve the efficiency and reliability of E-compressor systems. The work includes IoT integrated Matlab simulation for a hybrid PV powered E-compressor system. The system is analyzed with a 1.5-ton PMSM driven compressor system and their results are demonstrated in terms of performance and energy savings. © 2023 ieee.

关键词： Permanent magnets

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Innovative Approach to Supernumerary Teeth Identification: CNN-Based intelligent Medical Auxiliary System for Occlusal Radiographs 11

Innovative Approach to Supernumerary Teeth Identification: C...

引用

11th ieee international conference on cyber Security and Cloud Computing, CSCloud 2024

作者： Chen, Tsung-Yi Wu, Hung-I Li, Zhi-Han Fu, Jui-An Chen, Chiung-An Li, Kuo-Chen Liong, Sze-Teng Chi, Tsun-Kuang Chen, Shih-Lun Feng Chia University Department of Electronic Engineering Taichung40724 Taiwan Chang Gung Memorial Hospital Department of Pediatric Dentistry Linkou Taoyuan City33305 Taiwan Ming Chi University of Technology Department of Electrical Engineering New Taipei City243303 Taiwan Chung Yuan Christian University Department of Information Management Taoyuan City320317 Taiwan Chung Yuan Christian University Department of Electronic Engineering Taoyuan City320314 Taiwan

ISBN: (纸本)9798350376982

Supernumerary teeth (ST) not only commonly obstruct adjacent permanent teeth, causing ectopic eruption, rotation, and root absorption but also present the potential for cystic lesions extending into the nasal cavity. Early intervention is crucial to avoid severe complications like periodontal abscesses and severe dental caries. However, ST may occur in any oral region with variable shapes and growth directions, posing a significant challenge for image recognition. This prevalent dental condition in the Asian population (3-5%) lacks sufficient representation in AI-assisted systems. Given this, the study suggests a system reliant on Convolutional Neural Network (CNN) for identifying supernumerary teeth in occlusal radiographs. The algorithm incorporates feature enhancement and AI integration methods. Additionally, the study introduces a color mapping approach to address the variability in ST shape and growth direction, significantly improving recognition accuracy from 63.16% to 76.32%. The result of this research demonstrates an improvement of 18.43% in accuracy and 78.95% in recall rate for supernumerary tooth detection compared to existing technology. This study successfully addresses the challenge of identifying supernumerary teeth, which were previously difficult to recognize. To ensure compliance with ethical and regulatory standards, the proposal has obtained certification from the Institutional Review Board (IRB) with the reference number 202400084B0. © 2024 ieee.

关键词： Convolutional neural networks

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Automated Mobile Energy Storage systems Based cyber-Physical Coordinated Restoration of Distribution Networks Supported by intelligent Transportation systems

Automated Mobile Energy Storage Systems Based Cyber-Physical...

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Power systems and Smart Grid Technologies (PSSGT), ieee international conference on

作者： Wentao Shen Jian Zhong Chen Chen Ziwen Xu Quan Liu Jingxuan Zhu Zhaohong Bie School of Electrical Engineering Xi’an Jiaotong University Xi’an China National Innovation Platform Xi’an Jiaotong University Xi’an China

ISBN: (数字)9798331511401

ISBN: (纸本)9798331511418

Post-disaster power distribution network (PDN) restoration is critical for recovering power supply and should be completed quickly. However, the post-disaster restoration process is often hindered by poor road conditions, posing safety risks to maintenance personnel. The development of distribution automation (DA), intelligent transportation systems (ITSs) and autonomous driving technology has made unmanned post-disaster restoration of PDN feasible. This paper proposes a post-disaster restoration scheme for PDNs based on DA and automated mobile energy storage systems (MESSs), supported by ITS. The scheme is based on cyber-physical integrated restoration of the PDN, and comprehensively considers the optimization effect of road intelligent networked devices and road communication restoration on the dispatch of automated MESSs. Case studies on a power distribution network, transportation network, and communication network integrated test system are conducted to verify the effectiveness of the proposed scheme. The results demonstrate that this scheme improves the efficiency of post-disaster load recovery, highlighting the advantages of using ITS to enhance the resilience of PDNs.

关键词： Wireless communication Power supplies Roads Transportation Smart grids Safety Optimization Autonomous vehicles Resilience Energy storage

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MobileNet-Based Garbage Classification: Enhancing Recycling with Machine Learning

MobileNet-Based Garbage Classification: Enhancing Recycling ...

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2024 ieee international conference on intelligent Computing and Emerging Communication Technologies, ICEC 2024

作者： Soni, Tanishq Gupta, Deepali Uppal, Mudita Chitkara University Chitkara University Institute of Engineering and Technology Punjab India

ISBN: (纸本)9798331508432

Effective waste management depends critically on garbage classification, which tries to improve recycling procedures and lessen environmental effect. automation garbage sorting systems now operate with far higher precision and efficiency thanks to recent developments in machine learning. The performance of two widely used convolutional neural network (CNN) architectures, MobileNet and ResNet50, in categorizing different kinds of waste is assessed in this paper. We contrast the more intricate and deeper ResNet50 model with MobileNet, which is renowned for its light weight structure and high computing efficiency. Results from experiments show that MobileNet outperforms ResNet50 in terms of accuracy and computing efficiency by classifying garbage into predetermined categories with an accuracy of 80%. The effective model architecture of MobileNet is responsible for its better performance since it enables it to keep high accuracy while using less processing power. This qualifies MobileNet especially for use in practical applications where processing speed and resource limitations are important factors. The results open the door to more successful waste management solutions by demonstrating the feasibility of leveraging MobileNet for scalable and effective Garbage classification. © 2024 ieee.

关键词： Convolutional neural networks

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