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IEEE/ASME International conference on Mechtronic and Embedded systems and applications, MESA

作者： Jordon Lowe Kaya Kuru School of Engineering and Computing University of Central Lancashire Preston UK

ISBN: (数字)9798331516239

ISBN: (纸本)9798331516246

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： Industries Automation Mechatronics Embedded systems Wheels Reinforcement learning Handover Artificial intelligence Machine intelligence Vehicles

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Stone Soup open source framework for tracking and state estimation: enhancements and applications 31

Stone Soup open source framework for tracking and state esti...

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conference on Signal Processing, sensor/Information Fusion, and Target Recognition xxxI

作者： Barr, Jordi Harrald, Oliver Hiscocks, Steven Perree, Nicola Pritchett, Henry Vidal, Sebastien Wright, James Carniglia, Peter Hunter, Emily Kirkland, David Raval, Divy Zheng, Siyuan Young, Anne Balaji, Bhashyam Maskell, Simon Hernandez, Marcel Vladimirov, Lyudmil Def Sci & Technol Lab London England Def Res & Dev Canada Toronto ON Canada Univ Liverpool Liverpool Merseyside England

ISBN: (数字)9781510651210

ISBN: (纸本)9781510651210;9781510651203

The tracking and state estimation community is broad, with diverse interests. These range from algorithmic research and development, applications to solve specific problems, to systems integration. Yet until recently, in contrast to similar communities, few tools for common development and testing were widespread. This was the motivation for the development of Stone Soup - the open source tracking and state estimation framework. The goal of Stone Soup is to conceive the solution of any tracking problem as a machine. This machine is built from components of varying degrees of sophistication for a particular purpose. The encapsulated nature and modularity of these components allow efficiency and reuse. Metrics give confidence in evaluation. The open nature of the code promotes collaboration. In April 2019, the Stone Soup initial beta version (v0.1b) was released, and though development continues apace, the framework is stable, versioned and subject to review. In this paper, we summarise the key features of and enhancements to Stone Soup - much advanced since the original beta release - and highlight several uses to which Stone Soup has been applied. These include a drone data fusion challenge, sensor management, target classification, and multi-object tracking in video using TensorFlow object detection. We also detail introductory and tutorial information of interest to a new user.

关键词： open source tracking state estimation drone tracking data fusion sensor management classification video tracking

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TiO2-Coated Optical Fibers for Distributed pH Monitoring at High Pressures and Temperatures 2

TiO2-Coated Optical Fibers for Distributed pH Monitoring at ...

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conference on Optical Waveguide and Laser sensors II

作者： Shumski, Alexander Diemler, Nathan Wuenschell, Jeffrey Ohodnicki, Paul Wright, Ruishu Natl Energy Technol Lab 626 Cochran Mill Rd Pittsburgh PA 15236 USA NETL Support Contractor 626 Cochran Mill Rd Pittsburgh PA 15236 USA Univ Pittsburgh Dept Mech Engn & Mat Sci Pittsburgh PA 15261 USA Univ Pittsburgh Dept Elect & Comp Engn Pittsburgh PA 15261 USA Univ Pittsburgh Dept Phys & Astron Pittsburgh PA 15261 USA

ISBN: (纸本)9781510661783;9781510661790

In the oil and gas, CO2 sequestration, H-2 subsurface storage, and geothermal energy sectors, subsurface pH measurements are critical for monitoring the geochemical conditions and structural integrity of wellbore systems. Real-time pH measurements in these conditions are vital for detecting and predicting corrosion deterioration of wellbore components that may jeopardize the safety and continued operation of wellbore systems. The viability of TiO2-coated optical fibers has previously been demonstrated as an effective sensor design for continuous distributed pH monitoring at elevated temperatures and ambient pressures. However, real wellbore conditions contain high pressures and the effects of high pressures on sensor results and the sensing layer have not been well studied. As TiO2 has been established in the literature as being stable at temperatures and pressures substantially higher than those expected in typical wellbore conditions, it makes for a promising sensing material for applications requiring high-pressure, high-temperature (HPHT) conditions. In this study, a sol-gel deposition method is used to coat the optical fiber sensors with TiO2 sensing layer. The sensor performance was measured using optical transmission measurements at various pH and using optical backscatter reflectometry for distributed pH sensing demonstration in wellbore-relevant pressures (up to 1000 psi) and temperatures (similar to 80 degrees C). The TiO2 sensing layer was characterized using scanning electron microscopy (SEM) and full spectrum UVVis-NIR transmission data for a planar substrate. The TiO2-coated optical fiber sensor is tested for any pressure-derived effects and the viability of this sensor design for real-time in-situ wellbore pH monitoring is discussed.

关键词： High pressure high temperature TiO2 thin film pH sensor optical fiber sensor sol-gel coating wellbore monitoring distributed sensing

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Internet of Things-Based Drone Case Study for Atmospheric Data Collection

Internet of Things-Based Drone Case Study for Atmospheric Da...

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International conference on advanced Engineering, Technology and applications, ICAETA 2024

作者： Özer, Muhammed Mirac Unmanned/Intelligent Systems Lab Faculty of Aeronautics and Astronautics Tarsus University Mersin33400 Turkey

ISBN: (纸本)9783031709234

Although ground-based monitoring, manned aircrafts and satellites are used for atmospheric measurements, rapid and comprehensive data collection is not always possible near pollution sources due to the complexity of the areas to be measured, moving sources or physical obstacles. Therefore, drone solutions equipped with different sensors offer new approaches and research opportunities in air pollution and emissions monitoring, as well as on-site air quality monitoring to study atmospheric trends such as climate change. While the potential of unmanned aerial vehicles for air quality research has been identified, several challenges still need to be addressed, including flight durability, payload capacity, sensor consistency/accuracy and sensitivity. In this study, a rotary-wing drone architecture that utilizes artificial intelligence (AI), computer vision algorithms, as well as 4G-LTE IoT-based monitoring to collect atmospheric data, is presented. Designed as a new scalable platform to accommodate sensors suitable for flight control and communication requirements, the system has the ability to take off, fly and land with full autonomy. In case of possible communication interruption, it can switch to the fail- safe mode set in the ground control station. In addition to being able to make atmospheric measurements, a design has been developed in such a way that wide variety of parameters such as urban planning and development of smart cities, monitoring of industrial emissions, determination of pollution points in the city, redirection and management of traffic can be monitored in real time. The designed drone has a small, lightweight and low- cost multi-sensor system capable of measuring temperature, humidity, pressure, air velocity, noise, amount of UV, light intensity, PM2.5, PM10. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Drones

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Research advanced in the visual SLAM methods under indoor environment 2

Research advanced in the visual SLAM methods under indoor en...

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2nd International conference on Computing Innovation and Applied Physics, CONF-CIAP 2023

作者： Lu, Zhengsheng Wang, Jinchang Zhang, Zelin Zhu, Conghua Virginia Polytechnic Institute and State University 24060 United States Shangqiu Normal University 476000 China Tongji University 201804 China University of Nottingham NG7 2QL United Kingdom

Simultaneous localization and mapping (SLAM) have been a hotspot study topic in the computer vision community these days, which aims to locate the agent's position and perceive the surrounding environment to build a map. In Visual SLAM, the camera is the external sensor used, creating an environment map while locating itself. Compared with radar and other rangefinders, the visual sensor is usually tiny and has low power consumption, which has been the mainstream framework in SLAM research task. This paper starts from the system overview of visual SLAM, introduces the landmark achievements and research hotspots of visual SLAM, and discusses the key issues and three research methods based on visual SLAM in indoor environment. Meanwhile, the applications of visual SLAM in dynamic scenes and large indoor environments are listed. Finally, the trend of its future development is prospected. © Published under licence by IOP Publishing Ltd.

关键词： Indoor positioning systems

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MoDD: A Model-Driven Framework for Data Collection in Drone-Based systems

MoDD: A Model-Driven Framework for Data Collection in Drone-...

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Euromicro conference on Software Engineering and advanced applications (SEAA)

作者： Manele Ait Habouche Mickaël Kerboeuf Goulven Guillou Jean-Philippe Babau Université de Bretagne Occidentale Brest France

ISBN: (数字)9798350380262

ISBN: (纸本)9798350380279

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： Computer architecture Data collection Throughput Routing Data models Complexity theory Usability Monitoring Drones Software engineering

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LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models 24

LazyDP: Co-Designing Algorithm-Software for Scalable Trainin...

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29th ACM International conference on Architectural Support for Programming Languages and Operating systems (ASPLOS)

作者： Lim, Juntaek Kwon, Youngeun Hwang, Ranggi Maeng, Kiwan Suh, G. Edward Rhu, Minsoo Korea Adv Inst Sci & Technol Daejeon South Korea Penn State Univ University Pk PA 16802 USA Cornell Univ Ithaca NY USA Meta FAIR Menlo Pk CA USA

ISBN: (纸本)9798400703850

Differential privacy (DP) is widely being employed in the industry as a practical standard for privacy protection. While private training of computer vision or natural language processing applications has been studied extensively, the computational challenges of training of recommender systems (RecSys) with DP have not been explored. In this work, we first present our detailed characterization of private RecSys training using DP-SGD, root-causing its several performance bottlenecks. Specifically, we identify DP-SGD's noise sampling and noisy gradient update stage to suffer from a severe compute and memory bandwidth limitation, respectively, causing significant performance overhead in training private RecSys. Based on these findings, we propose LazyDP, an algorithm-software co-design that addresses the compute and memory challenges of training RecSys with DP-SGD. Compared to a state-of-the-art DP-SGD training system, we demonstrate that LazyDP provides an average 119x training throughput improvement while also ensuring mathematically equivalent, differentially private RecSys models to be trained.

关键词： Recommender systems

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Context-aware assistive driving: an overview of techniques for mitigating the risks of driver in real-time driving environment

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INTERNATIONAL JOURNAL OF PERVASIVE COMPUTING AND COMMUNICATIONS 2023年第3期19卷 325-342页

作者： Gite, Shilpa Kotecha, Ketan Ghinea, Gheorghita Symbiosis Int Deemed Univ Symbiosis Ctr Appl AI SCAAI Symbiosis Inst Technol Comp Sci Dept Pune Maharashtra India Brunel Univ Dept Comp Sci London England

Purpose This study aims to analyze driver risks in the driving environment. A complete analysis of context aware assistive driving techniques. Context awareness in assistive driving by probabilistic modeling techniques. advanced techniques using Spatio-temporal techniques, computer vision and deep learning techniques. Design/methodology/approach Autonomous vehicles have been aimed to increase driver safety by introducing vehicle control from the driver to advanced Driver Assistance systems (ADAS). The core objective of these systems is to cut down on road accidents by helping the user in various ways. Early anticipation of a particular action would give a prior benefit to the driver to successfully handle the dangers on the road. In this paper, the advancements that have taken place in the use of multi-modal machine learning for assistive driving systems are surveyed. The aim is to help elucidate the recent progress and techniques in the field while also identifying the scope for further research and improvement. The authors take an overview of context-aware driver assistance systems that alert drivers in case of maneuvers by taking advantage of multi-modal human processing to better safety and drivability. Findings There has been a huge improvement and investment in ADAS being a key concept for road safety. In such applications, data is processed and information is extracted from multiple data sources, thus requiring training of machine learning algorithms in a multi-modal style. The domain is fast gaining traction owing to its applications across multiple disciplines with crucial gains. Research limitations/implications The research is focused on deep learning and computer vision-based techniques to generate a context for assistive driving and it would definitely adopt by the ADAS manufacturers. Social implications As context-aware assistive driving would work in real-time and it would save the lives of many drivers, pedestrians. Originality/value This paper provi

关键词： Deep learning Assistive driving Context-aware systems Driver activity anticipation Driver activity recognition Multi-sensor data fusion

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advanced RFSoC readout for space-based superconducting sensor arrays 11

Advanced RFSoC readout for space-based superconducting senso...

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conference on : Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy xI

作者： Henderson, Shawn W. Ahmed, Zeeshan D'Ewart, John M. Frisch, Josef C. Herbst, Ryan Liu, Chao Ma, Lili Ruckman, Larry Van Winkle, Daniel D. Yu, Cyndia Kavli Inst Particle Astrophys & Cosmol Menlo Pk CA 94025 USA SLAC Natl Accelerator Lab Menlo Pk CA 94025 USA Stanford Univ Dept Phys Stanford CA 94305 USA

ISBN: (纸本)9781510653627;9781510653610

Low-energy threshold, high-resolution superconducting detector arrays with 10(3) -10(5) pixels are increasingly necessary in ground- and space-based telescopes across the electromagnetic spectrum including mm-wave, far-infrared (Far-IR), near-infrared, x-ray, and gamma rays. Reading out such large numbers of sensors poses significant technical challenges, but recent cryogenic readout technology developments are enabling the simultaneous read out of significantly more channels with minimal performance impact. An especially promising set of cold readout technologies couple cryogenic sensors to superconducting resonators. These technologies rely on high-frequency RF electronics to interrogate and demodulate the sensors' signals using digitally generated tones. Recently released Radio Frequency systems-on-Chip (RFSoC) devices from xilinx combine a FPGA with high-speed ADCs and DACs onto a single chip. These systems provide significant advantages for these applications, including lower cost, reduced size and weight, lower power consumption, and improved RF performance. While an RFSoC-based warm readout system would be attractive for a broad range of spacecraft applications, xilinx has not announced plans for a space qualified version of its RFSoC devices and insufficient data is publicly available to evaluate the feasibility of using RFSoC devices in space. To evaluate the suitability of RFSoC devices for spacecraft applications, we have designed and built custom boards using all space-qualified components except for the RFSoC. In this contribution we present the design of our custom RFSoC board, measurements of critical aspects of board performance which relate to operation in the harsh space environment, and measurements of integrated RF performance targeting the readout of large superconducting sensor arrays and space-based radio spectrometry. In addition to a wide range of spacecraft applications including communications and radar, our RFSoC platform is a potentially

关键词： Radio Frequency Readout Electronics Spacecraft Electronics Space Qualification Radio Frequency-systems-on-Chip Radio Astronomy Far-Infrared Astronomy x-ray Astronomy Cosmic Microwave Background

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The Comparison of the Reliability Performance of Different Top Metal Materials in MEMS applications

The Comparison of the Reliability Performance of Different T...

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2024 Pan Pacific Strategic Electronics Symposium, Pan Pacific 2024

作者： Hein, Verena Weide-Zaage, Kirsten Clausner, Andre X-FAB Global Services GmbH Erfurt Germany Leibniz Universität Hannover Hannover Germany Fraunhofer-Institut für Keramische Technologien und Systeme IKTS Microelectronic Materials and Nanoanalysis Dresden Germany

ISBN: (纸本)9781944543204

The combination of analog/mixed-signal, high-voltage and embedded non-volatile memory options with sensor and actuator integration is still common in automotive, industrial, communication and medical applications. MEMS with or without integrated CMOS, 3D integration micro transfer printing and integrated microfluid systems are in use to realize such applications. The established top metal interconnect materials for analog/mixed-signal CMOS applications are thick Aluminum (AlCu with Titan and Titanium Nitride) and thick Copper. Integrated noble metal electrodes are necessary for MEMS applications like microfluidics. The reliability requirements of a CMOS/ MEMS process differs from a long storage shelf life at room temperature, long life time for medical (in-body) or space applications up to high operating conditions for automotive and industrial applications like oil drilling. applications, like functional surfaces, combine integrated circuits for example for next generation DNA sequencing. The noble metals for electrodes on top are thinner for such applications. An additional reliability challenge for such a lab on a chip is corrosion. Automotive applications have often mission profiles which need high currents, high temperature and a growing mechanical stability. The reliability of noble top metals is more and more under investigation because MEMS are more common in automotive products. The knowledge about reliability especially about mechanical properties is an interesting topic in addition to the results from standard tests like electro migration and stress migration tests because of the advanced mechanical stress in the applications and the danger of corrosion. The comparison of the electromigration performance and mechanical stability of AlCu, Copper, Gold and Platinum as thick and/ or top metal tracks is necessary to evaluate and assess the suitability of the materials for the different applications. The possibilities to generate test results for thick and or

关键词： Reliability

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