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Deep Learning Utility for Gas/Odor Sensor Signature Analysis

Deep Learning Utility for Gas/Odor Sensor Signature Analysis

引用

Machine Learning and Autonomous systems (ICMLAS), International conference on

作者： Yashasvi Raut Shiv Nath Chaudhri Department of Computer Science and Engineering Faculty of Engineering and Technology DMIHER (DU) Maharashtra India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

Gas/odor sensors are integral components of sensor systems used in diverse applications such as food quality control, environmental monitoring, medical diagnostics, odor profiling, industrial safety, agriculture, explosives detection, wine tasting, pharmaceutical quality control, and toxic gas detection. Traditional approaches in this domain of gas/odor sensing technologies face challenges related to accuracy, cross-sensitivity, and drifted real-time performance. The integration of deep learning techniques with gas sensors has shown promise in overcoming these limitations. Moreover, this amalgamation of gas sensing and deep learning strategies enables accurate identification of gases/odors, handling complex patterns, and leading optimal consumption of resources. In this paper, an overview of advancements in deep learning-enabled gas sensing has been presented that focused on methodologies, sensor types, and applications. This review also highlights the state-of-the-art techniques and identifies gaps for future directions for research.

关键词： Deep learning Accuracy Hydrogen Quality control Real-time systems Sensor systems Sensors Protection Gas detectors Petroleum

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Simulation-Based Design of DDS Ownership QoS for Autonomous Driving control systems

Simulation-Based Design of DDS Ownership QoS for Autonomous ...

引用

Mechatronics and Robotics Engineering (ICMRE), International conference on

作者： Sung Keun Cha Sung Bhin Oh Hyeong Keun Hong Jae Wook Jeon Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea

ISBN: (数字)9798331509293

ISBN: (纸本)9798331509309

In this study, we designed a control management mechanism for autonomous vehicles by utilizing the ownership Quality of Service (QoS) of Data Distribution Service (DDS) and implemented and experimentally verified it based on FastDDS. By setting priorities among the three control modes of manual control, Advanced Driver Assistance System (ADAS) control, and emergency control based on ownership strength, we prevented data conflicts and enabled fast and accurate control switching even in emergency situations. The experimental results show that the proposed system minimizes the control transition latency. Also, it effectively guarantees the message throughput and demonstrates its practical applicability in safety-centric systems such as autonomous driving. This research will provide future possibilities for extending ownership QoS in complex environments such as multi-vehicle cooperative driving and vehicle-infrastructure communication. It also aims to contribute to improving the reliability and efficiency of autonomous driving technologies.

关键词： System performance Scalability Quality of service Switches control systems Throughput Reliability Vehicle dynamics Autonomous vehicles Robots

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StreamTag: A Platform for Flexible Tagged Data Management 11

StreamTag: A Platform for Flexible Tagged Data Management

引用

11th International conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Díaz-Jiménez, David Mata-Mata, Francisco López, José L. Pérez-Cordón, Luis G. Serrano, José-María Martínez-Cruz, Carmen Morcillo-Martínez, Juana M. Verdejo-Espinosa, Ángeles Cuevas-Martínez, Juan C. Viciana-Abad, Raquel Reche-López, Pedro J. Pérez-Lorenzo, José M. Gaitán-Guerrero, Juan F. Espinilla, Macarena Department of Computer Science University of Jaén Jaén23071 Spain Department of Languages and Computer Systems University of Granada Granada18071 Spain Psycology Department Faculty of Social Work University of Jaén Jaén23071 Spain Electrical Engineering Department University of Jaén Jaén23071 Spain Telecommunication Engineering Department University of Jaén Jaén23071 Spain

ISBN: (纸本)9789897587436

This paper presents StreamTag, a platform designed for the efficient management of labeled data in healthcare environments, particularly for activity recognition systems in residential and nursing home settings. Human Activity Recognition (HAR) is crucial for monitoring patient behaviors and supporting personalized care, and this field has evolved significantly with advances in IoT and AI. StreamTag integrates a flexible data labeling structure and a modular architecture, enabling data collection, labeling, and secure management of activity data. The system leverages non-relational databases for scalable data handling, along with secure protocols to ensure data integrity and privacy. This work examines existing approaches in HAR, including data-driven, knowledge-based, and hybrid models, and situates StreamTag as a versatile solution that combines flexible user-controlled labeling with high adaptability for diverse healthcare contexts. future directions are suggested for enhancing system functionality and integration with more advanced analytical tools. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Information management

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Research on the Collaborative Mechanism of P4Runtime and SAI in White Box Switches Based on the SONiC System

Research on the Collaborative Mechanism of P4Runtime and SAI...

引用

Power Electronics, computer Applications (ICPECA), IEEE International conference on

作者： Zhuyu Pan Hongchao Wang Chen Yan Zishi Zhang School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

With the advancement of Software-Defined Networking (SDN) technology, network programmability and flexibility have been significantly enhanced. However, effectively integrating traditional network systems with emerging programmable platforms remains a critical research challenge. This paper proposes a fusion architecture based on the P4Runtime protocol to achieve deep integration of SONiC white box switches and the P4 platform. By introducing SDN programmability, we design and implement a hybrid model that enables traditional network architectures to achieve advanced functionalities with the assistance of external SDN controllers. This paper provides a detailed discussion of the architecture design and implementation process, including P4 code development, compilation, target configuration file generation, and interaction mechanisms between the control plane and the data plane. Furthermore, we validate the applicability and performance of the architecture in various scenarios, offering robust support for future research and applications in programmable networks.

关键词： Protocols Process control computer architecture Switches Network architecture Programming control systems Power electronics Software defined networking Glass box

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Smart Interaction: Merging Augmented Reality and Internet of Things for Seamless Device control

Smart Interaction: Merging Augmented Reality and Internet of...

引用

International conference on ent Computing and control systems (ICICCS)

作者： J. R. V. Jeny B. Sai Mahitha M. Shashank N. Vamsi Krishna Department of Computer Science and Engineering(AI & ML) Vignan Institute of Technology and Science

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

The combination of Augmented Reality (AR) and Internet of Things (IoT), often referred to as AR + IoT, offers exciting possibilities for future research and development. IoT serves as a platform for communication and remote control of connected devices, while AR provides an intuitive interface for visualizing and managing these devices through enhanced, information-rich displays. This research aims to develop an interactive and accessible home automation system that integrates IoT and AR technologies, enabling seamless remote control of electrical devices. Utilizing an ESP32/NodeMCU board interfaced with the Blynk IoT platform, the system supports device management through a mobile application and an AR interface designed in Unity. The AR interface facilitates intuitive interactions via URL-based signals, which are transmitted to the IoT hardware for execution. This dual-control mechanism enhances user flexibility and convenience, making smart home automation more accessible to users with varying technical expertise. The proposed system not only improves user interaction and control efficiency but also demonstrates the potential of AR in augmenting IoT applications, bridging the gap between physical and virtual control environments. future enhancements could include advanced AR features, voice control, and cloud-based analytics to further optimize system performance and scalability.

关键词： Visualization System performance Scalability Smart homes systems support Internet of Things Augmented reality Remote control Wireless fidelity Research and development

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Intelligent Power Consumption Measurement and control System Based on C/S and Euclidean Distance

Intelligent Power Consumption Measurement and Control System...

引用

Power Electronics, computer Applications (ICPECA), IEEE International conference on

作者： Yuanzheng Xiao Huawei Hong Feifei Chen Xiaorui Qian Ming Xu Huang Feng State Grid Fujian Marketing Service Center (Metering Center and Integrated Capital Center) Fuzhou Fujian China State Grid Info-telecom Great Power Science and Technology Co. Ltd. Fuzhou China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

With the rapid development of smart grids, intelligent power measurement and control systems have become a key technology for achieving efficient energy management and energy conservation and emission reduction. Traditional measurement and control systems often have problems such as low data processing efficiency and poor real-time performance, which makes it difficult to meet the needs of modern power grids for precise control and intelligent management. In response to the above problems, this paper aims to explore an intelligent electricity measurement and control system based on C/S (Client/Server) architecture and Euclidean distance algorithm to improve data processing efficiency and system real-time performance. This paper elaborates on the application of C/S algorithm and Euclidean distance in intelligent power measurement and control system, including system architecture design, data processing flow and algorithm implementation. Then, through system performance testing and experimental results analysis, the effectiveness and reliability of the proposed system are verified. Finally, the research content, experimental results and shortcomings of this paper are summarized, and directions for future improvement are proposed. The experimental results show that the intelligent electricity measurement and control system based on C/S and Euclidean distance can significantly improve data processing efficiency and system real-time performance. The highest speed of data processing in the system is 200, reducing energy consumption and operating costs, providing strong support for the intelligent management of smart grids.

关键词： Power measurement Power demand Scalability systems architecture Euclidean distance control systems Data processing Real-time systems Smart grids Testing

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Integration of Chemometric Analysis and Machine Learning for Predictive Classification of Raisin Quality

Integration of Chemometric Analysis and Machine Learning for...

引用

Visual Analytics and Data Visualization (ICVADV), International conference on

作者： Gokul Padmanaban Princy Suganthi Bai S Department of Computer Application Hindustan Institute of Technology & Science Chennai India Department of Computer Science Hindustan Institute of Technology & Science Chennai India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The integration of chemometric analysis and machine learning techniques to enhance the predictive classification of raisin quality, a vital task for agricultural and food processing industries. The study employs chemometrics to analyze physical and chemical characteristics, selecting critical features such as color, texture, and chemical composition to reduce data redundancy and optimize model accuracy. Various machine learning algorithms, including Support Vector Machines (SVM), and Artificial Neural Networks (ANN), are applied and compared to predict raisin quality. By merging chemometric approaches with advanced machine learning methods, the proposed framework demonstrates improved classification accuracy over traditional techniques, showcasing its potential for real-world applications in quality control and automated sorting systems. future efforts will aim to expand the dataset, refine model performance, and explore new feature selection techniques to further boost classification accuracy.

关键词： Support vector machines Accuracy Visual analytics Machine learning Quality control Artificial neural networks Real-time systems Data models Chemicals Sorting

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Improving Robotic Arms Through Natural Language Processing, computer Vision, and Edge Computing

Improving Robotic Arms Through Natural Language Processing, ...

引用

Mechatronics, control and Robotics (ICMCR), International conference on

作者： Pascal Sikorski Kaleb Yu Lucy Billadeau Flavio Esposito Hadi AliAkbarpour Madi Babaias Undergraduate Research Assistant Computer Science Department Saint Louis University Saint Louis USA Undergraduate Research Assistant Aerospace & Mechanical Engineering Department Saint Louis University Saint Louis USA Associate Professor Computer Science Department Saint Louis University Saint Louis USA Assistant Professor Computer Science Department Saint Louis University Saint Louis USA CBL Assistant Professor of Robotics Aerospace & Mechanical Engineering Department Saint Louis University Saint Louis USA

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

This paper introduces a prototype for a new approach to assistive robotics, integrating edge computing with Natural Language Processing (NLP) and computer vision to enhance the interaction between humans and robotic systems. Our proof of concept demonstrates the feasibility of using large language models (LLMs) and vision systems in tandem for interpreting and executing complex commands conveyed through natural language. This integration aims to improve the intuitiveness and accessibility of assistive robotic systems, making them more adaptable to the nuanced needs of users with disabilities. By leveraging the capabilities of edge computing, our system has the potential to minimize latency and support offline capability, enhancing the autonomy and responsiveness of assistive robots. Experimental results from our implementation on a robotic arm show promising outcomes in terms of accurate intent interpretation and object manipulation based on verbal commands. This research lays the groundwork for future developments in assistive robotics, focusing on creating highly responsive, user-centric systems that can significantly improve the quality of life for individuals with disabilities. For video demonstrations and source code, please refer to: https://***/EnhancedArmEdgeNLP.

关键词： computer vision Mechatronics Source coding Machine vision Large language models Prototypes Focusing Manipulators Natural language processing Edge computing

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A Novel Wi-Fi Mesh Network Framework for Efficient Mobile Data Transmission

A Novel Wi-Fi Mesh Network Framework for Efficient Mobile Da...

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10th International conference on Internet of Things, Big Data and Security, IoTBDS 2025

作者： Ou, Yu-Jie Chen, Yan-Ming Yeh, Chun-Chao Department of Computer Science and Engineering National Taiwan Ocean University Keelung202301 Taiwan

ISBN: (纸本)9789897587504

The current trend involves the use of robots and various IoT devices to assist in production and development. In the future, with the integration of AI technology, related applications will become even more widespread. Within this context, whether it is command transmission, equipment status reporting, or equipment condition monitoring, a stable network environment is essential. Presently, the technology can be mainly categorized into wired networks, wireless networks (Wi-Fi), and mobile networks. While wired networks are fast and stable, they are constrained by physical lines and cannot be used in environments requiring interlaced movement. Wireless networks face disconnection issues when crossing different APs. While mobile networks, particularly those using 5G, offer excellent real-time performance, the establishment of private networks is expensive and the signal sources are relatively singular. This study proposes the use of Wi-Fi technology combined with the UDP (User Datagram Protocol) and QUIC (Quick UDP Internet Connections) protocols to create a new type of multipath network system. This system aims to reduce the adverse effects of physical environmental changes and wireless access point (AP) device transitions, achieving a low-cost, high-speed, highly mobile, and secure network environment in specific settings. The proposed scheme leverages the encryption and security features of the QUIC protocol to protect data privacy while supporting the needs of high-mobility applications. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Wireless mesh networks (WMN)

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Enhancing Two-Area Interconnected Power systems Using Model Predictive and PID control Approaches

Enhancing Two-Area Interconnected Power Systems Using Model ...

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Advances in computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), International conference on

作者： Ritesh Kumar Kushwaha Ram PrakashYadava Monu Malik Monauwer Alam Isarar Ahamad DivyanshuNaugai Dept. of Electronic and Communication Engineering Chandigarh University Mohali Punjab Deptt. of Electrical Engineering Integral University Lucknow U.P. India Electronics and Electrical Engg Deptt Maharaja SurajMal institute of Technology Deptt. of Electrical Engineering Integral University Lucknow Dept. of Electronics and Communication Engineering BTKIT Dwarahat Almora Uttarakhad india

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

This research represents a comparative study of Load Frequency control (LFC) using Model Predictive control (MPC). The results have also been compared with Proportional-Integral-Derivative (PID) controllers. LFC is evident for power system stability which keeps equilibrium between generation and load. PID controllers are widely employed, however in the modern-day power systems which are complex in nature the performance of the PID controllers is not as par. Therefore, different control schemes have and are being explored. MPC is one of them techniques. The aim of this research is to evaluate and compare the effectiveness of MPC and PID controllers, in two-area system. A case study featuring a two-area system is presented to illustrate how the controllers respond to load conditions and disturbances. This paper aims to provide insights into the merits and limitations of each controller. The results contribute to a more profound comprehension of the practical implications associated with implementing MPC in LFC systems, thereby influencing future research and practical applications.

关键词： PI control Perturbation methods Power system stability Predictive models Regulation PD control Frequency control Oscillators Predictive control Genetic algorithms

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