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50th Euromicro conference on Software Engineering and advanced applications

作者： Czyzewski, Adam Stepien, Krzysztof Poniszewska-Maranda, Aneta Lodz Univ Technol Inst Informat Technol Lodz Poland

ISBN: (纸本)9798350380279;9798350380262

Currently, the IT market is promoting the use of cloud resources to build solutions using machine learning. Some projects require full independence from external resources, mainly due to the volatility of prices for renting computing power and services provided by the cloud. The paper presents the creation process of scalable "on-premise" environment enabling the construction and development of artificial intelligence systems in the field of natural language processing. The proposed approach was based on aspects related to containerization, scalability, and automation of the machine learning process. Therefore, the created "on-premise" environment can be used in the implementation and delivery of systems based on artificial intelligence.

关键词： Distributed systems Automation process Containerization Kubernetes Kubeflow Machine learning

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Development of Machine Intelligence for Self-Driving Vehicles Through Video Capturing 20

Development of Machine Intelligence for Self-Driving Vehicle...

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20th IEEE/ASME International conference on Mechatronic and Embedded systems and applications (MESA)

作者： Lowe, Jordon Kuru, Kaya Univ Cent Lancashire Sch Engn & Comp Preston Lancs England

ISBN: (纸本)9798331516246;9798331516239

The automation of vehicles is progressing through several automation levels, with the goal of reaching full autonomy, i.e. level 5, which involves no steering wheel, brakes, pedals, or windshield. This is achieved by the vehicle taking on an increasing number of autonomous decision-making tasks under the guidance of smart control systems that are instilled with Artificial Intelligence (AI) and equipped with advanced sensor and actuator technologies. Major vehicle companies are competing to build the most talented driver, i.e. AI-agent. In this report, how the intelligence of Self-Driving Vehicles (SDVs) is being built by the automotive industry for the efficient deployment of handover wheels is analysed and applications of machine intelligence for SDVs are implemented through video capturing using Deep Learning (DL). The results show that i) the use of DL techniques as well as reinforcement learning (RL) - Deep RL approaches - can contribute to the intelligence of SDVs significantly and ii) SDVs, equipped with advanced mechatronics systems, can be fully autonomous with the level-5 automation as they are trained appropriately with proper datasets.

关键词： Autonomous driving self-driving vehicles Autonomous vehicles driverless vehicles sensor fusion vehicle automation deep learning neural networks

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MoDD : A Model-Driven Framework For Data Collection In Drone-Based systems 50

MoDD : A Model-Driven Framework For Data Collection In Drone...

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50th Euromicro conference on Software Engineering and advanced applications

作者： Habouche, Manele Ait Kerboeuf, Mickael Guillou, Goulven Babau, Jean-Philippe Univ Bretagne Occidentale Brest France

ISBN: (纸本)9798350380279;9798350380262

Nowadays, Cyber-Physical systems (CPS), particularly drones, play a pivotal role in environmental research. Scientists depend on these platforms to monitor various sensor data and ensure comprehensive data archiving. However, despite their advantages, researchers encounter several challenges, including communication limitations and the complexity of setting up systems tailored to their needs. To address these issues, we propose MoDD, a model-driven data collection framework based on a customized publish/subscribe model. MoDD simplifies the development and configuration of data collection systems. It offers scientists a solution that meets their specific needs, allowing them to focus on high-level requirements while the framework manages the underlying complexities. We demonstrate the effectiveness of MoDD through practical evaluations on an actual Unmanned Surface Vehicle. Additionally, results show a 79% reduction in throughput (drone to base station link) compared to existing publish/subscribe systems.

关键词： model-driven engineering drone data communications architecture optimization

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Wireless sensor Nodes for Condition Based Maintenance in Railway systems

Wireless Sensor Nodes for Condition Based Maintenance in Rai...

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2024 IEEE sensors conference

作者： Kersten, Philipp Buzin, Johannes Hirsch, Soeren Brandenburg Univ Appl Sci Dept Engn Brandenburg Germany

Ensuring the reliability, safety, and efficiency of railway systems is increasingly critical in global transportation networks. This paper addresses the necessity for advanced monitoring systems by introducing a multi... 详细信息

ISBN: (纸本)9798350363524;9798350363517

关键词： Wireless sensor node railway monitoring

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Smart Lighting systems, Controls, and Communication Protocols

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IEEE INDUSTRY applications MAGAZINE 2025年第2期31卷 68-79页

作者： Parise, Giuseppe Zissis, Georges Martirano, Luigi Sapienza Univ Rome I-00184 Rome Italy Univ Toulouse III Paul Sabatier F-31062 Toulouse France

Intelligent lighting systems use various methodologies comprising both standard protocols, intelligent methods, control systems and sensors. These protocols define the communication among lighting devices and control systems that many open standards allow interoperability among products from different manufacturers. They offer flexibility and a wide simplified selection in updates and implementations to installed systems. The control systems or transmission means of the protocols have characteristics of efficiency, distance limits and communication speed. They are wired, wireless or a combination of the two (hybrid). This paper deals with a presentation of open communication protocols wired and wireless. Wired solutions are more stable in terms of efficiency, speed and are not subject to interference, while wireless networks are easily extendable, easily scalable and lower cost. Control systems allow users to monitor and adjust lighting levels, color and other settings. sensors are used in smart lighting systems to detect and respond to changes in the environment. The various intelligent systems applied to lighting systems can make a significant contribution to safety and energy saving. In fact, energy efficiency is a primary goal, as smart lighting systems use advanced technologies to optimize energy consumption, reduce waste and costs. The combination of LED luminaires with smart lighting controls permits the maximum optimization of the energy efficiency of the system. Safety and reliability are also essential, as intelligent lighting systems offer better illumination, reducing the risk of accidents and improve safety, increasing the safety of people and property.

关键词： Protocols Standards Smart lighting Actuators sensors Buildings Control systems Intelligent sensors Europe Wireless sensor networks

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How can sensor data accessibility be enhanced in IoT-based health monitoring systems? 19

How can sensor data accessibility be enhanced in IoT-based h...

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IEEE 19th conference on Industrial Electronics and applications (ICIEA)

作者： Wang, Ting Pileno, Adrian Amatriain Monacelli, Eric Univ Gustave Eiffel CNRS ESIEE Paris LIGM Marne La Vallee France Univ Publ Navarra ETSIIIT Navarra Spain Univ Versailles St Quentin En Yvelines LISV Velizy Villacoublay France

ISBN: (纸本)9798350360875;9798350360868

This paper outlines the development of an economical Internet of Things (IoT)-based real-time health monitoring system. The prototype integrates a microcontroller and various sensors to monitor essential health parameters, including temperature, heart rate (HR), electrocardiogram (ECG), blood oxygen saturation (SpO2), and blood pressure (BP). With a focus on enhancing the accessibility of sensor data, diverse access options were implemented using advanced technical methodologies. The collected sensor data was efficiently stored, uploaded to the cloud, and visualized through tools such as HTML, Blynk, PAX-DAQ, and PuTTY, enabling seamless access via mobile devices or laptops. The paper concludes with the presentation of measurement results and an initial analysis of the sensor data, affirming the practicality and effectiveness of the proposed methods.

关键词： IoT-based Health Monitoring microcontroller sensor data accessibility data visualization

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Design and Optimization of High-Performance Health Monitoring systems Using advanced sensor Networks 2

Design and Optimization of High-Performance Health Monitorin...

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2nd International conference on advanced Computing and Communication Technologies, ICACCTech 2024

作者： Mehta, Heena Singla, Mukesh Baba Mastnath University Dept. of Computer Science and Engineering Haryana Rohtak India

ISBN: (纸本)9798331519056

This research elucidates the development and optimization of advanced sensor network-based health monitoring systems. In response to the increasing need for accurate health data in real-time, advanced gadgets capable of continuously monitoring essential indicators have been created. Contemporary sensor technologies, such as biosensors, IoT devices, and WSN s, enable these systems to facilitate data collection and processing with little disturbance. Optimization techniques like PSO, including machine learning algorithms and energy conservation procedures, are used to enhance the system's performance, reliability, and battery longevity. The study focuses on developing robust and scalable systems suitable for various healthcare applications, while also investigating data processing, communication protocols, network architecture, and sensor selection. advanced sensor networks will be crucial for future health monitoring, as research indicates substantial improvements in monitoring accuracy, system efficiency, and patient outcomes. Present approach is supposed to provide scalable and efficient solution. Moreover, it would support privacy in order to provide secure solution. © 2024 IEEE.

关键词： Electronic health record

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pH- and Saccharide-Responsive Cyclometalated Iridium(iii) Complexes with Boronic Acid Moieties Displaying a Wide Range of Phosphorescence Colors

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CHEMISTRY-A EUROPEAN JOURNAL 2025年第16期31卷 e202404010页

作者： Suzuki, Yota Imanishi, Ikumi Shiba, Koki Furuichi, Shino Takata, Mari Sugaya, Tomoaki Ishihara, Koji Waseda Univ Sch Adv Sci & Engn Dept Chem & Biochem Shinjuku Ku Tokyo 1698555 Japan Saitama Univ Grad Sch Sci & Engn Sakura Ku Saitama 3388570 Japan Chiba Inst Technol Fac Engn Educ Ctr Narashino Chiba 2750023 Japan

Single compounds displaying a wide range of luminescent colors are attractive optical materials for sensor applications. In this study, we present the beneficial combination of a cyclometalated iridium(iii) complex scaffold and boronic acid units for designing stimulus-responsive luminescent materials with various emission colors. Five iridium(iii) complexes bearing a diboronic acid ligand (bpyB2) were synthesized: Ir(C<^>N)bpyB2 (C<^>N=2-phenylpyridine (1), 2-(2,4-difluorophenyl)pyridine (2), 2-(4-methoxyphenyl)pyridine (3), benzo[h]quinoline (4), 1-phenylisoquinoline (5)). The luminescence color of Complexes 1-4 changed in response to the solution pH or saccharide concentration. Complex 1 exhibited a color change from orange to green-blue due to structural alteration of the boronic acid moiety from trigonal to tetrahedral. Furthermore, the luminescence color of Complex 1 changed reversibly due to repetitive changes in the solution pH between 5 and 10, enabling tuning of the luminescence color and pH tracking. Furthermore, the color range was tuned by selecting an appropriate C<^>N ligand. Time-dependent density functional theory investigations revealed that the dramatic and reversible color changes could be ascribed to a switch in the electronic distribution in the lowest excited state from bpyB2 to C<^>N. The stimulus-responsive iridium(iii) complexes provide a prospective scaffold for future applications in color-tunable optical devices and chemosensing systems.

关键词： Iridium Complex Boronic Acid Phosphorescence Stimulus-responsive Acid Dissociation

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Distributed sapphire fiber sensors for steel-making industrial applications 3

Distributed sapphire fiber sensors for steel-making industri...

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conference on Optical Waveguide and Laser sensors iii

作者： Mumtaz, Farhan Tekle, Hanok Zhang, Bohong Smith, Jeffrey D. O'Malley, Ronald J. Gerald, Rex. E., II Huang, Jie Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65409 USA Missouri Univ Sci & Technol Dept Mat Sci & Engn Rolla MO USA

ISBN: (纸本)9781510674073;9781510674066

This research demonstrates femtosecond (FS) laser-written distributed fiber Bragg gratings (FBGs) sensors within sapphire crystalline fiber, tailored for steelmaking applications. The study precisely assesses sensor stability during a 72-hour exposure to severe conditions, including temperatures reaching 1600 degrees C. The FBGs exhibit excellent signal strength and a maintained high signal-to-noise ratio (SNR) by averting external surface reactions with the sapphire fiber. Extensive annealing at 1600 degrees C purifies the sheathing material. By utilizing an extended 1-meter sapphire fiber, this work surmounts the challenges of cascading FBGs in highly multimode waveguides, enabling FBG signal capture in demanding applications. This research enhances our comprehension of FBG performance in high-temperature environments and paves the way for robust optical fiber systems in steelmaking applications, including tundish probes and submerge entry nozzles (SEN) for molten metal casting. Additionally, the exceptional efficiency and precision of sapphire FBG sensors, in contrast to conventional thermocouples, offer the potential to boost productivity, lower energy consumption, and reduce the carbon footprint in the steel industry.

关键词： Sapphire FBGs sensor distributed thermal mapping harsh environment femtosecond laser fiber Bragg gratings steelmaking industry applications tundish probe submerge entry nozzle

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Enhancing Road Safety: Leveraging CNN-LSTM and Bi-LSTM Models for advanced Driver Behavior Detection 2

Enhancing Road Safety: Leveraging CNN-LSTM and Bi-LSTM Model...

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2nd International conference of Intelligent Methods, systems and applications, IMSA 2024

作者： Diaaeldin, Ahmed Zaher, Moamen Faculty of Computer Science Giza Egypt

ISBN: (纸本)9798350362633

Recognizing the importance of driver behavior is essential for enhancing road safety and optimizing traffic management systems. This study employs advanced deep learning techniques, specifically CNN-LSTM and Bi-LSTM models, to refine the prediction of driver behaviors using sensor data from the Honda Research Institute Driving Dataset (HDD). Our approach integrates a robust dataset encompassing a broad spectrum of sensor inputs, from vehicle dynamics to driver operational parameters, propelling advancements in driver behavior detection. The methodologies utilized enable the discernment of subtle and complex driving patterns, contributing to the reduction of road safety hazards. Our findings indicate that these models significantly improve the detection of hazardous driving behaviors, surpassing previous state-of-the-art methodologies with notable gains in mean average precision (mAP). These advancements affirm the potential of deep learning technologies in crafting sophisticated predictive safety systems, paving the way for future innovations. © 2024 IEEE.

关键词： advanced traffic management systems

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