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Innovative System for Environmental Monitoring with Connected Sensors and Data Analysis for Chemical Pollutants

Innovative System for Environmental Monitoring with Connecte...

引用

2024 ieee international conference on intelligent systems and Advanced Applications, ICISAA 2024

作者： Suganya, A. Suryawanshi, Mahesh A. Bagal, Manisha V. Rawat, Ruchira Kaliappan, S. Manikandan, G. Karpagam College of Engineering Department of Information Technology Tamil Nadu Coimbatore India Bharati Vidyapeeth College of Engineering Department of Chemical Engineering CBD Navi Mumbai India Graphic Era Deemed to be University Department of Computer Science and Engineering Uttarakhand Dehradun India Lovely Professional University Division of Research and Development Punjab Phagwara India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331539948

The Chemical Pollutants system, which combines sophisticated data processing capabilities with networked sensors to identify and control chemical pollutants, transforms environmental monitoring. It collects real-time data on pollutants using extremely accurate sensors, which are then evaluated using cloud infrastructure and a reliable wireless connection. Predictive insights using machine learning algorithms provide notable improvements: 97% accuracy in sensor data, 3 seconds of data transmission latency, and 99.5% system uptime. There are now 1200 daily active users, and the prediction model's accuracy is 92%. Environmentally, it resulted in a 30% decrease in PM2.5 levels, a halving of high pollution alerts to 10 per month, and an 85% increase in public awareness. The number of policy changes tripled to four each year, while community engagement quadrupled to twelve. The results highlight the system's contribution to improving the timeliness and quality of environmental data, influencing public health and policy, and highlighting its efficacy and potential for wider environmental management use. © 2024 ieee.

关键词： Volatile organic compounds

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VESC-SLAM: A Visual Information Enhanced Multi-Robot Synchronous Collaborative SLAM

VESC-SLAM: A Visual Information Enhanced Multi-Robot Synchro...

引用

2024 ieee international conference on Unmanned systems, ICUS 2024

作者： Yu, Jingyu Cheng, Longbo Zhou, Jianshan Duan, Xuting Ren, Chenghao Chen, Ken State Key Lab of ITS Beihang University Beijing China Zibo Vaucrefly Intel. Tech. Co. Ltd. Zibo China Zhejiang Rongqe Technology Co. Ltd. Zhejiang China

ISBN: (纸本)9798350384185

The collaborative Simultaneous Localization and Mapping (SLAM) system between unmanned aerial vehicles and unmanned ground vehicles in low-light environments faces the problem of poor quality such as blurred and missing visual information. This study constructs a collaborative SLAM system based on deep neural networks to solve this problem. The system significantly i mproves t he p ositioning a ccuracy and map construction quality of unmanned aerial vehicles and unmanned ground vehicles under low-light conditions through the cooperation of the front-end image enhancement module, the collaborative SLAM core processing module, and the intelligent data collaboration and resource optimization module. The system has been validated on the Euroc dataset processed by darkening and its performance has been compared with other robot cluster collaborative SLAM. © 2024 ieee.

关键词： Deep neural networks

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Constraint-Forcing Recursive Generalized Maximum Correntropy Algorithm with Forgetting Factor for Adaptive Filtering 29

Constraint-Forcing Recursive Generalized Maximum Correntropy...

引用

29th ieee international conference on Parallel and Distributed systems, ICPADS 2023

作者： Li, Wenyue Zhao, Ji Li, Qiang Tang, Lingli Zhang, Hongbin Southwest University of Science and Technology School of Information Engineering Mianyang621010 China Southwest University of Science and Technology Department of Social Sciences Mianyang621010 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China

ISBN: (纸本)9798350330717

In this paper, jointly with the exponential weighted generalized maximum correntropy (GMC) criterion and the linear constraint framework, we derive a recursive constrained adaptive filtering algorithm named recursive constrained GMC with forgetting factor (FF-RCGMC). In addition, due to a lack of constraint information during the learning process, FF-RCGMC will diverge or even fail to work after some iterations. Therefore, we propose a more stable version by introducing a constraint-forcing strategy into FF-RCGMC and call this robust type as constraint-forcing FF-RCGMC (CFFF-RCGMC). Some simulation results in system identification under non-Gaussian noisy environments validate the effectiveness of CFFF-RCGMC. © 2023 ieee.

关键词： Constrained adaptive filtering generalized correntropy non-Gaussian noise system identification

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Research on Medical Equipment Operation State Monitoring and Early Warning technology of Failure

Research on Medical Equipment Operation State Monitoring and...

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2024 international conference on Power, Electrical Engineering, Electronics and control, PEEEC 2024

作者： Huang, Hangliang Shengzhou Hospital of Traditional Chinese Medicine Zhejiang Shengzhou312400 China

ISBN: (数字)9798350378917

ISBN: (纸本)9798350378917

With the continuous advancement of medical technology, medical devices play a crucial role in clinical diagnosis and treatment. However, malfunctioning of medical equipment may lead to serious medical accidents and affect the health and safety of patients. Therefore, how to effectively monitor the operation status of medical devices and realize early warning of failures has become an urgent problem. This study is dedicated to exploring and developing advanced monitoring techniques and early warning systems to improve the reliability and safety of medical equipment. This paper firstly reviews the existing medical device monitoring technologies and their limitations, and then explores the application of sensor technology, data acquisition and processing, machine learning and artificial intelligence in medical device monitoring, and analyzes the integration of remote monitoring and Internet of Things (IoT) technologies. Subsequently, the paper describes the construction method of the early warning system for failures, including the establishment of warning models, data analysis and prediction techniques. Through specific case studies, the paper demonstrates the practical application effects of these technologies. Finally, the paper discusses the challenges that may be faced during the implementation of these technologies and looks forward to the future development direction. The study shows that the combination of advanced monitoring technologies and intelligent warning systems can significantly improve the operational efficiency and safety of medical devices and provide strong support for the medical industry. © 2024 ieee.

关键词： Patient treatment

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A Novel Approach to Malicious Code Detection Using CNN-BiLSTM and Feature Fusion 6

A Novel Approach to Malicious Code Detection Using CNN-BiLST...

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6th international conference on Robotics, intelligent control and Artificial Intelligence, RICAI 2024

作者： Zhang, Lixia Liu, Tianxu Shen, Kaihui Chen, Cheng Xi’an XD Power Systems Co. Ltd. Xi'an China Hangzhou Research Institute Xidian University Hangzhou China Xidian Digital Technology Xi'an China Harbin Engineerning University Harbin China

ISBN: (纸本)9798331541699

With the rapid advancement of Internet technology, the threat of malware to computer systems and network security has intensified. Malware affects individual privacy and security and poses risks to critical infrastructures of enterprises and nations. The increasing quantity and complexity of malware, along with its concealment and diversity, challenge traditional detection techniques. Static detection methods struggle against variants and packed malware, while dynamic methods face high costs and risks that limit their application. Consequently, there is an urgent need for novel and efficient malware detection techniques to improve accuracy and robustness. This study first employs the minhash algorithm to convert binary files of malware into grayscale images, followed by the extraction of global and local texture features using GIST and LBP algorithms. Additionally, the study utilizes IDA Pro to decompile and extract opcode sequences, applying N-gram and tf-idf algorithms for feature vectorization. The fusion of these features enables the model to comprehensively capture the behavioral characteristics of malware. In terms of model construction, a CNN-BiLSTM fusion model is designed to simultaneously process image features and opcode sequences, enhancing classification performance. Experimental validation on multiple public datasets demonstrates that the proposed method significantly outperforms traditional detection techniques in terms of accuracy, recall, and F1 score, particularly in detecting variants and obfuscated malware with greater stability. The research presented in this paper offers new insights into the development of malware detection technologies, validating the effectiveness of feature and model fusion, and holds promising application prospects. © 2024 ieee.

关键词： Critical infrastructures

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Development of a PID controller-Based Portable Seeder Design for Corn Seeds 11

Development of a PID Controller-Based Portable Seeder Design...

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11th international conference on cyber and IT Service Management, CITSM 2023

作者： Boonkon, Somsamai Maungmeesri, Benchalak Maneetham, Dechrit Valaya Alongkorn Rajabhat University Industrial of Technology Faculty Technology Management Department Khlong Luang Thailand Rajamangala University of Technology Thanyaburi Mechatronics Engineering Department Thanyaburi Thailand

ISBN: (纸本)9798350305968

Corn is a major crop in Thailand and plays a crucial role in feeding people locally and being sold to other countries. Because of its importance, farmers focus a lot on growing corn. Nowadays, many farmers are growing corn to earn more money from their land. As more land is used for corn, there's a growing need for new ways to plant the seeds. This is where a special machine comes in, a seeder that carefully places corn seeds in the ground according to how they should be planted in fields where corn is grown. In one seeding pass, the machine will press the center and form two rows of mounds with a distance of 25-50 cm between them. In these two mounds, corn seeds will be placed at intervals of 6-8 cm for each row. The design of this seeder machine is made portable so that it can adapt to all types of tractors used as propulsion. © 2023 ieee.

关键词： Three term control systems

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Legal Driving for Autonomous Vehicles Through Law-Compliance Potential Fields 27

Legal Driving for Autonomous Vehicles Through Law-Compliance...

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27th ieee international conference on intelligent Transportation systems, ITSC 2024

作者： Song, Lei Zhang, Lingjun Zhao, Chengxiang Ma, Xiaohan Liu, Jiaxin Wu, Siyu Wang, Zixuan Yu, Wenhao Wang, Hong School of Vehicle and Mobility Tsinghua University Beijing10081 China School of Mechanical Engineering Beijing Institute of Technology Beijing10081 China

ISBN: (纸本)9798331505929

The widespread adoption of autonomous vehicles necessitates their compliance with existing traffic laws. However, while safety-oriented decision-making methods have matured, shortcomings in law compliance persist. To ensure that autonomous vehicles drive legally while prioritizing safety, a law-compliance potential fields-based approach is introduced. Firstly, this paper discusses the classification and constraints of traffic laws on vehicle states, outlining five principles for legal driving. Subsequently, law-compliance potential fields are established, incorporating factors related to roads, obstacles, and vehicle speeds. The potential fields-based model predictive control (MPC) controller is then employed to generate feasible trajectories, thereby enabling legal driving. Finally, the effectiveness of the proposed approach is verified through three representative scenarios including the intersection, the highway and the urban road. The results demonstrate that the method can ensure law compliance of autonomous vehicles in complex scenarios and can prioritize safety in extreme situations. © 2024 ieee.

关键词： Autonomous vehicles

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Coordinated Optimal Scheduling of Power System with Wind Power Considering the Flexibility Space of Energy-intensive Load and Pumped Storage 3

Coordinated Optimal Scheduling of Power System with Wind Pow...

引用

3rd international conference on Power systems and Electrical technology, PSET 2024

作者： Li, Lingfang Yue, Xiaoyu He, Xuehao Yang, Jiaquan Pan, Ruxiang Liao, Siyang Yunnan Power Grid Corporation Ltd Power Grid Planning and Construction Center Yunnan China Wuhan University Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network School of Electrical Engineering and Automation Wuhan China Electric Power Research Institute Yunnan Power Grid Corporation Ltd Kunming China

ISBN: (纸本)9798350353204

Insufficient peak regulation capacity in the power system limits wind power integration. Energy-intensive industrial loads and pumped storage stations offer substantial capacity and rapid adjustment, yet their potential remains underutilized. This study proposes a coordinated optimization method considering both factors. It analyzes the flexible regulation of energy-intensive loads, establishes their regulation model, and similarly for pumped storage, considering its flexibility margin. Additionally, it creates a multi-resource coordination optimization model, factoring in the economic aspects of thermal power deep peak shaving. Tested on a typical system, the proposed model can significantly reduce the wind curtailment rate of the system, greatly reduce the total operating cost of the system, and improve the economy of thermal power. Meanwhile, the utilization rate of the pumped storage unit is improved, the potential of energy-intensive load regulation is excavated, and the peak load regulation structure of the system is reasonably optimized. © 2024 ieee.

关键词： Wind power integration

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intelligent Integration of IoT and cyber-Physical systems: Empowering the Next Generation of AI-Enabled Smart Environments

Intelligent Integration of IoT and Cyber-Physical Systems: E...

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international conference on Computing Communication control and automation (ICCUBEA)

作者： Usman Ahmad Usmani Suliana Sulaiman Junzo Watada Universiti Pendidikan Sultan Idris Tanjong Malim Perak Waseda University Shinjuku City Tokyo Japan

ISBN: (数字)9798350391770

ISBN: (纸本)9798350391787

ObjectivesThis research aims to examine the integration of Artificial Intelligence (AI), Internet of Things (IoT), and cyber-Physical systems (CPS), focusing on their synergistic manifestations and transformative potential. It explores how AI enhances the capabilities of IoT devices and enables intelligent decision-making in CPS *** study involves an in-depth analysis of the integration challenges such as data protection, scalability, and interoperability. It presents possible solutions like edge computing and secure communication protocols. Real-world examples and case studies are used to illustrate the practical benefits of AI-based *** research demonstrates that AI technology significantly enhances resource allocation, predictive maintenance, and energy efficiency in IoT and CPS applications. It also addresses the integration challenges and provides solutions to improve system performance and *** paper highlights future directions for the industry, emphasizing ethical aspects and the role of AI in enabling autonomous systems. It provides comprehensive guidance for researchers, practitioners, and decision-makers involved in technology-enabled environmental design, offering valuable insights into leveraging AI, IoT, and CPS integration.

关键词： Privacy Protocols System performance Scalability Internet of Things Resource management Artificial intelligence Next generation networking Interoperability Predictive maintenance

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Health Care Data Mining using intelligent Classification Techniques 5

Health Care Data Mining using Intelligent Classification Tec...

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5th ieee international conference on Advances in Computing, Communication control and Networking, ICAC3N 2023

作者： Antil, Jyoti Rishi, Rahul Sharma, Sonia Yadav, Rajkumar University Institute Of Engineering And Technology Mdu Dept. Of Computer Science Engineering Hrayana Rohtak India University Institute Of Engineering And Technology Mdu Dept. Of Electronic And Communication Engineering Hrayana Rohtak India

ISBN: (纸本)9798350330861

Classification models can be learned from complicated multivariate temporal data and this is a topic we investigate in electronic health record systems. The difficulty is to come up with a collection of attributes that accurately reflect the data's temporal nature. Using temporal abstractions and pattern mining, we extract the classification features from the data. There are frequently a lot of temporal patterns that aren't related to the classification job that are returned by temporal pattern mining. © 2023 ieee.

关键词： Classification (of information)

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