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advanced three-dimensional graphene-based piezoresistive sensors in wearable devices 9

Advanced three-dimensional graphene-based piezoresistive sen...

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9th International conference on advanced Manufacturing Technology and Materials Science, AMTMS 2021

作者： Chen, Weiyuan Huang, Yanjie Queen Mary University of London Engineering School Northwestern Polytechnical University Shanxi Xi'an710000 China School of Materials Science and Physics China University of Mining &Technology Jiangsu Province Xuzhou221116 China

The piezoresistive pressure sensor made with a three-dimensional (3D) structure as the core material is considered a potential precision sensor for wearable devices because of its unique advantages of simple preparation principle, low power consumption, stable performance and high signal acquisition efficiency. It has attracted the attention of many scientific researchers who are committed to realizing the high intelligence and informatization of personal devices. After the rapid development in the 21st century, this technology has made many breakthroughs and showed strong application potential in high-tech fields such as human motion detection, health monitoring and electronic skin. However, this technology is still a long way from full commercial mass production. This paper introduces the unique advantages of the 3D graphene-based piezoresistive sensor in intelligent wearable devices, summarizes several production methods and applications of this 3D graphene-based piezoresistive sensor, explores the future development trend and application prospect of this technology, and discusses the challenges and prospects of piezoresistive pressure sensor based on three-dimensional graphene. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Graphene

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Fine-grained Spatiotemporal Features-Based for Anomaly Detection in Microservice systems 24

Fine-grained Spatiotemporal Features-Based for Anomaly Detec...

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24th IEEE International conference on High Performance Computing and Communications, 8th IEEE International conference on Data Science and systems, 20th IEEE International conference on Smart City and 8th IEEE International conference on Dependability in sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Yang, xikang Wang, Juan Zhou, Biyu Wang, Wang Liu, Wantao Dong, Yangchen Institute of Information Engineering Chinese Academy of Sciences China School of Cyber Security University of Chinese Academy of Sciences China China Academy of Information and Communications Technology Beijing China

ISBN: (纸本)9798350319934

More and more applications use microservice architecture. Protecting the reliability of the microservice system is very important for the stable operation of applications. However, the complexity of microservice systems poses a great challenge to operation and maintenance. Researchers have proposed a series of anomaly detection algorithms, which can automatically detect the anomalies of cloud systems in time. However, for the microservice system with a complex spatial structure, there is no effective method to represent the fine-grained features of the internal metric level of the microservice. To solve this problem, we propose a fine-grained metric-level spatial feature graph TopoMetrics and use a spatiotemporal neural network STAD to obtain the spatiotemporal features of microservices, which can accurately detect the anomalies of complex microservices. We compare STAD with the most advanced algorithms in three open microservice workloads. The experimental results show that the average precision of STAD is significantly higher than that of the most advanced baseline method. © 2022 IEEE.

关键词： Anomaly detection

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

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

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advanced Computing & Communication Technologies (ICACCTech), International conference on

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

ISBN: (数字)9798331519056

ISBN: (纸本)9798331519063

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.

关键词： Wireless sensor networks Accuracy Protocols System performance Medical services Network architecture Real-time systems Biosensors Monitoring Optimization

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Edge Computing in Wireless Sensing applications 11

Edge Computing in Wireless Sensing Applications

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11th Mediterranean conference on Embedded Computing (MECO) / 3rd Summer School on Cyber-Physical + systems and Internet of Things (CPS and IoT)

作者： Santejudean, Tudor Voicu Mois, George Dan Sanislav, Teodora Folea, Silviu Corneliu Tech Univ Cluj Napoca Dept Automat Cluj Napoca Romania

ISBN: (纸本)9781665468282

Edge computing has emerged as the solution to the continuously increasing numbers of Internet-connected devices and to the ever increasing amounts of data transmitted by them. Through the use of advanced algorithms and hardware components it allows sensor data processing at the source and reduces the volumes of data transmitted within the network. This paper focuses on the idea of edge computing, looks at some of the most important achievements in the field, and presents a use case system that shows how edge intelligence is becoming more common. The developed use case system is an environmental wireless sensor that is able to run for long periods of time on a single coin-cell battery while measuring parameters like equivalent CO2 (carbon dioxide) and VOC (Volatile Organic Compounds). This was made possible through the device's design, components, and advanced firmware, that uses high-level signal processing and fusion algorithms.

关键词： Edge computing Internet-of-Things wireless sensor

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Magnetic Field Sensing with Multi-Material Printed Fiber-Tip Microcantilever 15

Magnetic Field Sensing with Multi-Material Printed Fiber-Tip...

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15th International conference on Information Optics and Photonics, CIOP 2024

作者： Huang, Haoqiang Liao, Changrui Zou, Mengqiang Wang, Yiping Shenzhen Key Laboratory of Photonic Devices and Sensing Systems for Internet of Things Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen University Shenzhen518060 China Shenzhen Key Laboratory of Ultrafast Laser Micro/Nano Manufacturing Key Laboratory of Optoelectronic Devices and Systems Ministry of Education/Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Shenzhen518107 China

ISBN: (数字)9781510686175

ISBN: (纸本)9781510686168

Based the advanced "Lab on Fiber" technology and femtosecond (Fs) laser induced two-photon polymerization (TPP) technology, polymer microstructures printed on fiber tip have great potential as high sensitivity micro-sensors. However, additional functionalization is usually required, the traditional treatments such as electron beam sputtering and chemical coating cannot achieve precise functionalization of local microstructure and require additional post-processing. In this work, we report a successive multi-material on-fiber TPP strategy for 4D-microstructure fabrication, and prepare a fiber-tip polymer magnetic microsensor in one step. First, a cantilever is printed on the fiber tip to form a Fabry-Perot (F-P) interferometer. Then, using a self-made magnetic fluid photoresist, a magnetic cube is printed on the cantilever tip as a magnetically responsive element. This method achieves precise functionalization of local microstructure in one step, avoiding further post-processing. The prepared microcantilever magnetic sensor achieves a high sensitivity of 119 pm mT-1, providing an ultra-compact optical solution for high-resolution measurements of weak magnetic fields. With the rapid development of advanced intelligent materials, the multi-material on-fiber TPP strategy can be extended to other stimulus-response materials, offering new guidance for manufacturing various stimulus-response micro-sensors and micro-actuators on fiber tip. © 2024 SPIE.

关键词： Nanocantilevers

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Automated Assembly and Alignment of NIR and MIR External Cavity Diode Laser systems 11

Automated Assembly and Alignment of NIR and MIR External Cav...

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2025 conference on Components and Packaging for Laser systems

作者： Erfle, Denis Assmann, Christian Schmidtmann, Sebastian Honsberg, Martin Sacher, Joachim Sacher Lasertech GmbH Hedwig Jahnow Str 12 D-35037 Marburg Germany Sensor Photon GmbH Hedwig Jahnow Str 12 D-35037 Marburg Germany

ISBN: (纸本)9781510684362;9781510684379

Laser systems operating in the near-infrared (NIR) and mid-infrared (MIR) spectral regimes have become indispensable tools for a wide range of applications, including spectroscopy, metrology, and emerging quantum technologies. However, high manufacturing costs and variability due to manual assembly remain significant barriers to widespread adoption. This work introduces an automated assembly and alignment approach for NIR and MIR external cavity diode laser systems, leveraging robotic systems and artificial intelligence in the vision system for edge detection to enhance precision, reproducibility, and efficiency while significantly reducing production costs and time. The automation process achieves positioning accuracy better than 100 nm across all three translational degrees of freedom and angular accuracy exceeding 0.6 arcminutes. Continuous in-situ monitoring of optical and spectral performance during each alignment step ensures high reproducibility and optimal laser performance. A key focus of this approach is achieving symmetrical laser beams with well-defined divergence angles, which are crucial for effective cavity alignment. The method is demonstrated through the alignment of external cavity lasers with Volume-Bragg-Grating components, showcasing examples of NIR VBG lasers with varying cavity lengths. This automated production concept represents a significant advancement in industrial laser manufacturing by addressing challenges associated with manual processes, such as variability and inefficiency. It provides a scalable solution for producing high-performance laser systems at reduced costs while maintaining stringent quality standards.

关键词： Spectroscopy applications Optical Alignment External Cavity Diode Lasers Automated Assembly Edge Detection Precision Alignment Volume-Bragg-Grating Industrial Laser Manufacturing

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Global Configuration Strategy of SAPFs Combined with Comprehensive Evaluation of Power Quality in Distribution Network

Global Configuration Strategy of SAPFs Combined with Compreh...

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2022 International conference on Power Energy systems and applications, ICoPESA 2022

作者： Yin, xiaoqing Yi, Hao Yang, Zebin Zhuo, Fang Xi'an Jiaotong University State Key Laboratory of Electrical Insulation and Power Equipmen Xi'an China

ISBN: (纸本)9781665410977

Recently, with the development of the smart distribution network with the advanced metering infrastructure, the requirement of comprehensive evaluation with mass data and global improvement of power quality has emerged. However, most comprehensive evaluation methods only focus on the score of power quality without considering the role of comprehensive evaluation in the global improvement strategy of power quality control devices. This paper proposes a complete global configuration strategy of shunt active power filters (SAPFs), which utilizes the evaluation scores as a part of the objective function. Then, an IEEE 18-bus test system with non-linear loads and unbalance loads is employed in simulation to verify the feasibility of the proposed comprehensive evaluation algorithm and global configuration strategy. After configuring SAPFs according to the result, total power quality indicators in the system can meet the recommended standards. © 2022 IEEE.

关键词： Convex optimization

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IoT-Based Security Detection for Cloud Web applications: Leveraging Internet of Things Approaches 1

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3rd International conference on Mechanical and Energy Technologies, ICMET 2023

作者： Sudhakar, A.V.V. Shweta, Shashwati Kumar, K. Suresh Dube, Anand Prakash Lakshmikanth, R. Sravan, Padala Department of EEE School of Engineering SR University Telangana Warangal India Tilak Maharashtra Vidyapeeth Vidyapeeth Bhavan Gultekdi Pune India MBA Department Panimalar Engineering College Varadarajapuram Poonamallee Chennai India Department of Computer Science School of Management Sciences Uttar Pradesh Varanasi India Department of Management Studies Adithya Institute of Technology Coimbatore Kovilpalayam India School of Computer Science and Artificial Intelligence SR University Telangana Warangal India

ISBN: (数字)9789819727162

ISBN: (纸本)9789819727155

The surge of Internet of Things (IoT) gadgets and cloud-based applications has been increasing the pressure to manage data reliability and security in digital space. This abstract presents examining new techniques for the detection of security among cloud web applications with the capabilities of IoT. Through the equipment of IoT devices, there will be the enhancement of real-time monitoring and detection of safety threats in cloud-based applications that are Internet-based. This synergy enables banks to have access to a variety of data sources, that is, both internal and external data. It makes the collection of large volumes of data possible, and so the banks have a good picture of the environment in which the application runs. With the use of machine learning and AI algorithms in the background, the existing anomalies and known potential vulnerabilities can be found fast, hence paving the way for proactive remediation of the present and future threats. Besides, the sensor through IoT can be utilised to measure physical security areas, which include environmental conditions and access control device integrity, and they make sure provision of security to cloud web applications. A single security architecture that utilises IoT and cloud technologies will allow the organisations to have robust defences, enhanced data protection, and a diminishing risk level, thus keeping the digital services in a trusted and dependable state in an always advanced threat environment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Internet of things

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3-Axis Force Estimation of a Soft Skin sensor using Permanent Magnetic Elastomer (PME) Sheet with Strong Remanence

3-Axis Force Estimation of a Soft Skin Sensor using Permanen...

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IEEE/ASME International conference on advanced Intelligent Mechatronics (AIM)

作者： Wang, Yushi Kamezaki, Mitsuhiro Wang, Qichen Sakamoto, Hiroyuki Sugano, Shigeki Waseda Univ 1 Chome 104 Totsukamachi Shinjuku City Tokyo 1698050 Japan Nippon Paint Holdings Corp Ltd Tokyo Japan

ISBN: (数字)9781665413084

ISBN: (纸本)9781665413084

This paper describes a prototype of a novel Permanent Magnetic Elastomer (PME) sheet based skin sensor for robotic applications. Its working principle is to use a Hall effect transducer to measure the change of magnetic field. PME is a polymer that has Neodymium particles distributed inside it, after strong magnetization for anisotropy, the PME acquires strong remanent magnetization that can be comparable to that of a permanent magnet, in this work, we made improvement of the strength of the magnetic field of PME, so it achieved magnetic strength as high as 25 mT when there is no deformation. When external forces apply on the sensor, the deformation of PME causes a change in the magnetic field due to the change in the alignment of the magnetic particles. Compared with other soft magnetic sensors that employ similar technology, we implemented linear regression method to simplify the calibration, so we focus on the point right above the magnetometer. An MLX90393 chip is installed at the bottom of the PME as the magnetometer. Experimental results show that it can measure forces from 0.01-10 N. Calibration is confirmed effective even for shear directions when the surface of PME is less than 15 x 15 mm.

关键词： Magnetic field measurement Magnetometers Magnetization Robot sensing systems Particle measurements Skin Soft magnetic materials

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AI-Powered Business Intelligence for Smarter Decision-Making and Growth

AI-Powered Business Intelligence for Smarter Decision-Making...

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2024 International conference on Artificial Intelligence and Quantum Computation-Based sensor applications, ICAIQSA 2024

作者： Alijoyo, Franciskus Antonius Pradhan, Rahul Vats, Satvik Rani, V.Kanpur Kholmukhamedov, Timur Karthik, M. School of Business and Information Technology STMIK LIKMI Center for Risk Management and Sustainability Indonesia Bandung Indonesia GLA University Department of Computer Engineering and Applications Mathura India Graphic Era Hill University Department of CSE Dehradun India Graphic Era Deemed to Be University Uttarakhand Dehradun India Hindustan Institute of Technology and Science Department of EEE Chennai India Turin Polytechnic University in Tashkent Management Economics and Humanitarian Disciplines Department Tashkent Uzbekistan K.Ramakrishnan College of Engineering Department of AI & DS Trichy India

ISBN: (纸本)9798331517953

Business intelligence (BI) has become a cornerstone for data-driven decision-making in modern enterprises. With the increasing complexity of data, traditional methods often fall short in providing actionable insights. Machine learning techniques, such as Gradient Boosting Machines (GBMs), offer advanced predictive capabilities that can significantly enhance BI outcomes. This paper explores the application of Gradient Boosting Machines (GBMs) in enhancing BI for better decision-making and operational efficiency. GBMs, a powerful ensemble learning technique, are utilized to predict customer churn based on a comprehensive retail dataset encompassing customer demographics, purchase history, engagement scores, and monetary values. The Proposed Method is implemented using Python Software and demonstrates that GBMs achieve exceptional predictive accuracy of 99.2%, significantly outperforming traditional methods like Decision Tree, SVM, BDMS. Feature importance analysis reveals that 'Recency' (days since last purchase) is the most influential predictor of churn, followed by 'Engagement Score' and 'Monetary Value'. The findings emphasize the model's capability to enhance customer retention strategies, optimize resource allocation, and improve overall business outcomes. Utilizing GBMs, high-risk customers (top 10% predicted probabilities of churn) were targeted with a specialized retention campaign, which led to a 15% reduction in churn rates among this group. The effectiveness of the campaign validates the model's predictions and highlights the practical benefits of integrating GBMs into BI systems. This research underscores the transformative potential of AI-driven techniques in business intelligence, offering actionable insights for businesses seeking to leverage predictive analytics for competitive advantage. © 2024 IEEE.

关键词： Predictive analytics

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