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检索条件"任意字段=Conference on Advanced Sensor Systems and Applications X"

共 16568 条记录，以下是1241-1250 订阅

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8-inch wafer level through glass via (TGV) interposer with 110-GHz bandwidth facing 128-GBaud 2.5D co-packaged optics (CPO)

8-inch wafer level through glass via (TGV) interposer with 1...

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2024 Asia Communications and Photonics conference, ACP 2024 and International conference on Information Photonics and Optical Communications, IPOC 2024

作者： Ge, Chang Wang, xinyi Du, Jiangbing Lin, xiaozhong Lei, Ting Du, Luping He, Zuyuan State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai200240 China Research and Development Department Shenzhen Photonics Valley Technology Co. Ltd. Shenzhen518114 China Nanophotonics Research Center Shenzhen Key Laboratory of Microscale Optical Information Technology Institute of Microscale Shenzhen University Shenzhen518060 China

TGV interposer fabricated by 8-inch glass wafer with 110-GHz bandwidth and 128-GBaud OOK signal interconnection is presented. Flip-chip packaging of EML and EIC chips were realized, proving great potential in 2.5D CPO... 详细信息

ISBN: (纸本)9798350379266

关键词： Flip chip devices

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IoT Innovations for Enhanced Agricultural Practices and Sustainable Farming

IoT Innovations for Enhanced Agricultural Practices and Sust...

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International conference on Inventive Computation Technologies (ICICT)

作者： Chhinder Kaur Dhaliwal Bharti Sharma Samrity Sandeep Kaur Richa Chandel Department of Computer Applications Chandigarh Business School Of Administration Landran Mohali Punjab India Department of Computer Applications Chandigarh College Of Technology Landran Mohali Punjab India

ISBN: (数字)9798331512248

ISBN: (纸本)9798331512255

Smart farming represents a forward-thinking transition by incorporating information and communication technology into agriculture. This refers to the use of equipment, machineries and sensors within network based hi-tech farming systems. The introduction of innovative technologies like IoT and cloud computing is expected to usher in robotics and artificial intelligence, challenging traditional approaches while presenting various hurdles. This paper explores tools and equipment in wireless sensor applications for IoT agriculture, addressing potential challenges when merging technology with conventional farming, offering technical insights applicable across the entire crop lifecycle, including sowing, harvest, packing, and transportation.

关键词： Wireless communication Smart agriculture Wireless sensor networks Technological innovation Crops Transportation Robot sensing systems sensor systems Intelligent sensors Farming

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applications of Composite Microfluidic systems and Micro Total Analysis systems (μTAS) for Monitoring the State of Natural Soils, Swamps or Wetlands: Biodegradable Polymers of the μTAS Chip Moldings as sensor Layers for Weathering Estimations 9

Applications of Composite Microfluidic Systems and Micro Tot...

引用

9th International Technical conference on Frontiers of Hydraulic and Civil Engineering Technology, HCET 2024

作者： Gradov, Oleg V. Gradova, Margaret A. Maklakova, Irina A. Popov, Anatoly A. Varian, Ivetta N.N. Semenov Federal Research Center for Chemical Physics The Russian Academy of Sciences Moscow119991 Russia N.M. Emanuel Institute of Biochemical Physics The Russian Academy of Sciences Moscow119334 Russia

ISBN: (纸本)9781643685595

The ability to model / monitor biodegradation processes is vital for predicting the lifespan and environmental impact of biodegradable materials used in civil engineering applications. Digital analogs of Cholodny chambers and burried slides can be equipped with sensors to monitor changes in physical and chemical properties of the soil and materials over time (for example - lens-less optical sensors with multiphysical converters of non-optical signals into optical ones). This data can be used to develop predictive models that account for varying soil conditions, microbial populations, and material compositions. Such models can aid engineers in selecting appropriate materials for specific applications (for example - for long-term hydraulic expositions in contact with oceanic or freshwater plastisphere), ensuring that they meet both performance and environmental criteria. The surface characteristics of biodegradable composites significantly influence their interaction with soil microorganisms. By employing SEM and 2D FFT methods, researchers can gather valuable data on the mechanisms of biodegradation, including microbial colonization, enzymatic activity, and chemical breakdown processes. The usage of biodegradable and soil-modifiable composite buried slides and soil chambers allows for detailed examination of surface degradation, which are critical for understanding how materials will perform in real-world applications. By analyzing surface erosion, microbial biofilm formation, and chemical weathering, researchers can identify optimal formulations for biodegradable polymer composites that enhance their performance while minimizing ecological / toxicological impact. Consequently biodegradable and soil-modifiable polymer composite buried slides and soil chambers facilitate multiphysical predictive analysis of biodegradable polymeric composite materials, enabling engineers to make informed decisions regarding sustainable practices in eco-friendly civil and hydraulic engi

关键词： Weathering

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MEMS DIFFERENTIAL THERMOPILES FOR HIGH-SENSITIVITY HYDROGEN GAS DETECTION 36

MEMS DIFFERENTIAL THERMOPILES FOR HIGH-SENSITIVITY HYDROGEN ...

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36th IEEE International conference on Micro Electro Mechanical systems (MEMS)

作者： Zhang, Haozhi Jia, Hao Li, Ming xu, Pengcheng Li, xinxin Chinese Acad Sci Shanghai Inst Microsyst & Informat Technol State Key Lab Transducer Technol Shanghai 200050 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (纸本)9781665493086

We report a MEMS differential thermopile sensor for high-sensitivity hydrogen (H-2) gas detection. By exploiting the single-sided microhole inter-etch and sealing (MIS) process, pairs of MEMS single-crystalline silicon thermopiles are batch fabricated into 2x1mm(2) dies. Each suspended thermopile is integrated with high-density thermocouples, allowing us to achieve a temperature sensitivity of similar to 27.8mV/degrees C. Such design ensures the detection of tiny temperature changes (down to similar to 1mK) caused by catalytic combustion of H-2-air mixture at 120 degrees C when the sensing thermopile is loaded with platinum nanoparticles-decorated aluminum oxide (Pt NPs@Al2O3) nanosheets. The sensors exhibit a linear response to H-2 concentration from 1.0% down to 5ppm with a response time of similar to 2.5s and a recovery time of similar to 1.7s (in 1% H-2), which are more sensitive than the previously reported MEMS thermopile H-2 sensors. The proposed sensors are also selective against other combustible gases and remain stable after 30 days. Our highly-sensitive, cost-effective MEMS differential thermopile sensors hold promise for H-2 leakage detection in industrial applications.

关键词： Hydrogen sensor MEMS thermopile MIS process High Sensitivity

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Multi sensor Network System for Early Detection and Prediction of Forest Fires in Southeast Asia 33

Multi Sensor Network System for Early Detection and Predicti...

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33rd International Telecommunication Networks and applications conference, ITNAC 2023

作者： Kadir, Evizal Abdul Alomainy, Akram Daud, Hanita Maharani, Warih Muhammad, Noryanti Syafitri, Nesi Universitas Islam Riau Department of Informatics Engineering Pekanbaru28284 Indonesia School of Electronic Engineering Queen Mary University of London LondonE1 4NS United Kingdom Universiti Teknologi Petronas Department of Applied Mathematics Perak32610 Malaysia School of Computing Telkom University Bandung40257 Indonesia Universiti Malaysia Pahang Centre for Mathematics Sciences Kuantan26300 Malaysia

ISBN: (纸本)9798350317138

The increasing frequency and severity of forest and land fires have become a significant environmental concern, necessitating the development of effective early detection and prediction systems. This paper presents a novel approach to address the issue through the implementation of a multi-sensor network system for forest and land fires. The proposed system integrates an array of advanced multi-sensors strategically placed across the targeted regions to capture and analyze a wide range of fire-related data. The key objective of the system is to enable timely identification of potential fire hotspots by continuously monitoring various environmental parameters, including temperature, humidity, and infrared radiation. The collected data is then processed and analyzed using machine learning algorithms to identify fire patterns and predict the likelihood of fire outbreaks. The system utilizes a network of sensors, and the system offers real-time and comprehensive coverage, allowing for rapid response and timely deployment of fire suppression resources. Furthermore, the results of extensive field tests and evaluations, demonstrate the system's accuracy and efficiency in early fire detection and prediction. The proposed system offers a case in Indonesia which is Riau Province with high-risk cases almost every year. Plotting results data achieved and forecasting of the incident for the future in the year 2023 with a successful percentage up to 93.6%. Ultimately, the integration of the multi-sensor network system into existing fire management frameworks promises to enhance emergency response capabilities and foster proactive measures to preserve our valuable forests and lands. © 2023 IEEE.

关键词： Fires

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advanced Security System for four wheeler: Minimizing Collision Accidents through Collision Avoidance Technology

Advanced Security System for four wheeler: Minimizing Collis...

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International conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE)

作者： Abhishek Chaudhary Koshal Nikita Rana Mohd Arman Electrical Engineering Department Delhi Technological University DTU New Delhi India

ISBN: (数字)9798350379297

ISBN: (纸本)9798350379303

This project aims to develop an advanced and cost-effective solution to enhance safety in various environments by preventing collisions between objects. Employing Arduino microcontrollers and a range of sensors, the system operates in real-time to identify obstacles and take immediate corrective actions. Key components include ultrasonic sensors for accurate distance measurement, an Arduino microcontroller for data processing, and actuators such as motors or servos for executing avoidance maneuvers. By analyzing sensor data, the Arduino assesses obstacle proximity and triggers suitable responses to avoid collisions. The project introduces a flexible and scalable framework suitable for integration into different applications, including robotics, autonomous vehicles, and smart environments. Moreover, emphasis is placed on user-friendly customization, allowing end-users to adjust system parameters and behaviors according to specific requirements. Addressing the growing need for safety solutions in autonomous systems, robotics, and IoT applications, the Collision Avoidance System represents a significant advancement in reliable collision avoidance technologies. By providing an accessible and adaptable platform, the project facilitates the development of technologies that can reduce accidents, enhance operational efficiency, and promote the widespread adoption of autonomous systems across various domains.

关键词： Microcontrollers Decision making Robot sensing systems Real-time systems sensor systems Energy efficiency Distance measurement

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Data-Enhanced Prediction with Decomposition and Amplitude-Aware Permutation Entropy in Distributed Computing systems

Data-Enhanced Prediction with Decomposition and Amplitude-Aw...

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2024 IEEE International conference on systems, Man, and Cybernetics, SMC 2024

作者： Yuan, Haitao Hu, Qinglong Bi, Jing Zhang, Wei Zhang, Jia Zhou, MengChu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China City University of Hong Kong Dept. of Computer Science 999077 Hong Kong College of Computer Beijing University of Technology Beijing100124 China University of Connecticut Dept. of Computer Science and Engineering StorrsCT06269 United States Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781665410205

In recent years, distributed computing has wit-nessed widespread applications across numerous organizations. Predicting workload and computing resource data can facilitate proactive service operation management, leading to substantial improvements in quality of service and cost efficiency. However, these data often exhibit non-linearity, high volatility, and inter-dependencies across different categories, presenting challenges for accurate forecasting. Consequently, there is a critical need to develop a method that thoroughly and comprehensively analyzes all available data to forecast future trends effectively. This work proposes a novel integrated data-enhanced prediction model named SVI for achieving high-accuracy workload prediction in distributed computing systems. SVI employs the Savitzky-Golay filter and variational mode decomposition for feature processing, whose features are subsequently utilized by Informer for multivariate joint analysis of the enhanced data, achieving high-precision prediction. Ablation and comparative experiments with advanced prediction models are conducted on the Google cluster trace and other typical datasets. Realistic data-driven results indicate that SVI improves the prediction accuracy by 35.4% compared to the original Informer, with each module contributing to the performance enhancement. Furthermore, compared with Autoformer, SVI enhances the prediction accuracy of workload, CPU, and memory by 62.5%, 65.6%, and 69.1 %, respectively. © 2024 IEEE.

关键词： Quality of service

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Curved CMOS imaging sensor: benefits for space optical system design

Curved CMOS imaging sensor: benefits for space optical syste...

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2022 International conference on Space Optics, ICSO 2022

作者： Mehri, Tahar Jahn, Wilfried Joaquina, Kelly Renard, Marc Lemared, Sabri Struss, Quentin SILINA route de Mimet Gardanne880 France

ISBN: (纸本)9781510668034

Curved imaging sensors bring significant size, weight and cost reduction to imaging systems while mitigating off-axis optical aberrations, as opposed to current flat sensors. Unlocking these key features has captured the interest of major players over the last two decades. SILINA has been developing a CMOS Image sensor (CIS) curving process, which adapts to various sensor characteristics. This enables the design of image focal planes to various shapes to specifically maximize the optical performance of every single imaging system. We demonstrated the manufacturing of spherical and aspherical CIS in 2021, opening a new area of compact, fast, wide-angle and high-resolution optical system solutions. From concave to convex, spherical, aspherical, cylindrical, toroidal, or even freeform shapes can be reached. These new degrees of freedom offered to CIS can significantly simplify optical systems through a reduction of the number of elements and improve optical performance in many different ways. The field of view, the contrast, the F-number can be increased while optical aberrations and distortion can be minimized. At the end, the different costs related to manufacturing, metrology, integration, and alignment are reduced. This is of great importance for applications requiring compact payload, high resolution, high transmission factor and shorter integration time. In this paper we address the challenges caused by the adoption of curved image sensors, notably the different approaches for the adaptation of existing designs with a highlight on the optimization and tolerancing methodology. We describe our approach to enhance existing designs by including a curved focal plane, from the first analysis to the last optimization run, in order to improve key performance criteria while maintaining first order parameters. We discuss the improvement expected for space observation through a focus on a two-mirror telescope design based on the Hubble Space Telescope characteristics. © 202

关键词： Image sensors

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Integrating Photonics and Fiber Bragg Grating sensors with Deep Reinforcement Learning for advanced Robotic systems

Integrating Photonics and Fiber Bragg Grating Sensors with D...

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International conference on Computing for Sustainable Global Development (INDIACom)

作者： T Subaranjani R Jaideep C Manjula V Seema Dept. of Artificial Intelligence and Machine Learning The Oxford College of Engineering Bangalore India Dept. of Mechatronics Engineering The Oxford College of Engineering Bangalore India

This research introduces the Photonics-Enhanced Embedded Robotic Intelligence Model (PEERIM), an innovative approach that integrates fiber Bragg grating (FBG) sensors with photonics and deep reinforcement learning (DRL) for advanced robotics applications. Addressing the limitations of current AI models in dynamic and complex environments, PEERIM leverages the rapid data transmission capabilities of photonics to process high-frequency sensor data, enabling real-time decision-making and enhanced automation. The methodology encompasses the development and integration of a variant of the Proximal Policy Optimization (PPO) algorithm, tailored to manage the continuous data stream and execute precise, adaptive control. The proposed model has been empirically evaluated, demonstrating a significant improvement in handling real-time sensor data with an average reward of 99.02 and a low average loss of 0.099, indicating robust performance and learning stability. These findings suggest that PEERIM provides a substantial advantage over existing AI-driven robotic systems, offering a scalable solution for a variety of challenging applications. The study’s contributions lay the groundwork for future advancements in autonomous systems, promising a new era of precision and reliability in robotics.

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Curving Motion Control of a Traction Rail Mover Using a Dual BLAC Motor Drive

Curving Motion Control of a Traction Rail Mover Using a Dual...

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24th International conference on Electrical Machines and systems (ICEMS)

作者： Ok, Sangjae Bae, Jongnam Lee, Dong-Hee Kyungsung Univ Dept Mechatron Engn Busan 48434 South Korea

This article presents an improved position control method of an overhang-type rail system considering a curved path. The designed system is driven by two BLAC (brushless ac) motors, and the moving position is controlled based on the signal from a simple Hall position sensor mounted on the motor without any absolute position sensors. The rail is composed of both linear and curved paths. For the linear rail, the two motors are controlled to rotate in the same speed. However, in a curved path, the two motors must have different moving distance according to the curvature. Generally, in order to determine the proper motion commands for both traction motors, the actual curvature state and position have to be detected by a potentiometer or an encoder equipped with linear position sensor, but this method significantly increases complexity and cost of the system. This article aims to solve this problem by using a low-cost semiconductor IMU (inertia measurement unit) to estimate the actual rail condition. The IMU will then estimate the heading angle variation to compensate the motion commands for the two BLAC motors without any additional external absolute sensors. As a result, a balanced and improved motion can be achieved for an arbitrary rail path. Practical experiments using an overhang-type rail traction system were performed to verify the effectiveness of the proposed control scheme. The results show the advanced control performance in both linear and curved path, and also a smooth transition between them both.

关键词： Rails Traction motors Brushless motors AC motors Rotors Permanent magnet motors Synchronous motors Curving motion dual BLAC (brushless ac) motor Hall sensor heading angle estimation turning

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