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2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)最新文献

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Towards Model Development for Sensor-Based Activity Recognition at the Construction Site 基于传感器的建筑工地活动识别模型开发
Pub Date : 2023-06-08 DOI: 10.1109/IWASI58316.2023.10164490
Carla Tettamanti, Marco Giordano, Julia Altheimer, Lukas Linhart, Michele Magno
Digital solutions for the construction industry are promising to improve energy consumption, tool life cycle, tool design, productivity, safety, health, and risk management. In this study we assess the feasibility of using accelerometer data obtained from a low-power Micro-Electro-Mechanical Systems (MEMS) sensor directly placed on the tool, to identify screwdriver tool usage types. We focus on the performance evaluation of several distinct features and machine learning (ML) techniques regarding their accuracy and model size. To establish a comprehensive data set, we first collect data, identify fit-for-purpose usage classes and, subsequently, apply a variety of feature engineering and ML techniques to the established problem. As two distinct usage class groups, we identify, runtime classes (Drilling”, “Screwing” and “Unscrewing”) and the non-runtime classes (“Preparing the Tool “Carrying the Tool “Transportation of the Tool and “No Movement”).The paper proposes two tree-based models Decision Tree Classifier (DTC) and Gradient Boosting Machine (GBM), for which we assess various techniques of automated and handcrafted feature extraction. We design an iterative feature selection method to identify the most important ones from more than 4000 features. Further, we evaluated the neural networks Long Short-Term Memory (LSTM) and Temporal Convolutional Network (TCN), which process time-series data, and the Minimally Random Convolutional Kernel Transform (MINIROCKET). The experimental evaluation focuses on accuracy and model size.The MINIROCKET is the best-suited model with a balanced accuracy of 94.1% and a model size of 377.5 kB, enabling real-time processing in small micro-controller or even in Bluetooth low energy modules.
建筑行业的数字化解决方案有望改善能源消耗、工具生命周期、工具设计、生产力、安全、健康和风险管理。在本研究中,我们评估了使用直接放置在工具上的低功耗微机电系统(MEMS)传感器获得的加速度计数据来识别螺丝刀工具使用类型的可行性。我们专注于几个不同的特征和机器学习(ML)技术的性能评估,包括它们的准确性和模型大小。为了建立一个全面的数据集,我们首先收集数据,确定适合目的的使用类别,然后将各种特征工程和ML技术应用于已确定的问题。作为两个不同的使用类组,我们确定了运行时类(钻孔、旋紧和旋紧)和非运行时类(“准备工具”、“携带工具”、“运输工具”和“不移动”)。本文提出了决策树分类器(Decision Tree Classifier, DTC)和梯度提升机(Gradient Boosting Machine, GBM)两种基于树的模型,并对各种自动化和手工特征提取技术进行了评估。我们设计了一种迭代特征选择方法,从4000多个特征中识别出最重要的特征。此外,我们评估了处理时间序列数据的神经网络长短期记忆(LSTM)和时间卷积网络(TCN),以及最小随机卷积核变换(MINIROCKET)。实验评价的重点是准确性和模型尺寸。MINIROCKET是最适合的模型,其平衡精度为94.1%,模型尺寸为377.5 kB,可在小型微控制器甚至蓝牙低功耗模块中进行实时处理。
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引用次数: 0
Near-Brain Computation: Embedding P300-based BCIs at EEG headset level 近脑计算:在脑电图耳机水平嵌入基于p300的脑机接口
Pub Date : 2023-06-08 DOI: 10.1109/IWASI58316.2023.10164428
G. Mezzina, Martin Walchshofer, C. Guger, D. Venuto
This paper presents a first-of-a-kind BCI framework overcoming technological and environmental factors that limit the adaptability of EEG-based BCIs to everyday life contexts. Some examples of these limitations include discomfort associated with the use of EEG headsets that require conductive gel, the lack of “plug and play” solutions, and noisy environments. In this context, the proposed BCI framework aims to realize an integrated system, currently running on the STM32L4 embedded platform (oriented towards headset-level implementation), capable of: (i) analyzing data from 8 dry EEG electrodes, (ii) detecting and correcting spatially uncorrelated deflections in EEG channels caused by external disturbances, and (iii) identifying and fine-tuning hyperparameters of a Fully Connected Neural Network with a user data-driven approach. The implemented embedded system, applied for a feasibility study to a 12-choice P300 speller matrix, demonstrated matrix element recognition accuracy exceeding 80% after only 4 runs, while maintaining an information transfer rate (ITR) of approximately 16 commands per minute under non-optimal usage conditions.
本文提出了一种首创的脑机接口框架,克服了限制基于脑电图的脑机接口适应日常生活环境的技术和环境因素。这些限制的一些例子包括与使用需要导电凝胶的EEG耳机相关的不适,缺乏“即插即用”解决方案,以及嘈杂的环境。在此背景下,所提出的BCI框架旨在实现一个集成系统,目前运行在STM32L4嵌入式平台上(面向头戴式实现),能够:(i)分析来自8个干脑电图电极的数据,(ii)检测和纠正由外部干扰引起的脑电图通道中空间不相关的偏转,以及(iii)通过用户数据驱动的方法识别和微调全连接神经网络的超参数。所实现的嵌入式系统,应用于12个选择的P300拼写矩阵的可行性研究,显示仅在4次运行后,矩阵元素识别准确率超过80%,同时在非最佳使用条件下保持每分钟约16个命令的信息传输速率(ITR)。
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引用次数: 0
X-ray qualification of hydrogenated amorphous silicon sensors on flexible substrate 柔性衬底氢化非晶硅传感器的x射线鉴定
Pub Date : 2023-06-08 DOI: 10.1109/IWASI58316.2023.10164611
M. Menichelli, L. Antognini, A. Bashiri, M. Bizzarri, L. Calcagnile, M. Caprai, A. Caricato, R. Catalano, G. Cirrone, T. Croci, G. Cuttone, S. Dunand, M. Fabi, L. Frontini, C. Grimani, M. Ionica, K. Kanxheri, M. Large, V. Liberali, M. Martino, G. Maruccio, G. Mazza, A. Monteduro, A. Morozzi, F. Moscatelli, S. Pallotta, A. Papi, D. Passeri, M. Pedio, M. Petasecca, G. Petringa, F. Peverini, L. Piccolo, P. Placidi, G. Quarta, S. Rizzato, G. Rossi, Federico Sabbatini, A. Stabile, L. Servoli, C. Talamonti, L. Tosti, M. Villani, R. Wheadon, N. Wyrsch, N. Zema
Hydrogenated amorphous silicon (a-Si:H) is a well known material for its radiation resistance and for the possibility of deposition on flexible substrates like Polyimide (PI), polyethylene terephthalate (PET) or polyethylene naphthalate (PEN). Due to the properties of a-Si:H its usage for dosimetry, beam monitoring for particle physics and nuclear medicine, as well as, radiation flux measurement for space applications and neutron flux measurement can be foreseen. In this paper the dosimetric X-ray response of p-i-n diodes deposited on Polyimide will be studied. In particular we will study the linearity of the photocurrent response to X-rays versus dose-rate from which we will extract the dosimetric sensitivity at various bias voltages. We will repeat this study for devices having two different areas (2 mm x 2 mm and 5 mm x 5 mm) also a measurement of stability of X-ray response versus time will be shown.
氢化非晶硅(a- si:H)是一种众所周知的材料,因为它具有抗辐射性能,并且可以沉积在聚酰亚胺(PI)、聚对苯二甲酸乙二醇酯(PET)或聚萘二甲酸乙二醇酯(PEN)等柔性衬底上。由于a-Si:H的特性,可以预见它将用于剂量学、粒子物理和核医学的束流监测,以及空间应用的辐射通量测量和中子通量测量。本文研究了沉积在聚酰亚胺上的p-i-n二极管的剂量学x射线响应。特别地,我们将研究光电流对x射线的响应与剂量率的线性关系,从中我们将提取不同偏置电压下的剂量学灵敏度。我们将对具有两个不同区域(2mm x 2mm和5mm x 5mm)的设备重复此研究,并将显示x射线响应随时间的稳定性测量。
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引用次数: 1
Detector design and R&D directions for a future Multi-TeV Muon Collider 未来多tev介子对撞机探测器设计及研发方向
Pub Date : 2023-06-08 DOI: 10.1109/IWASI58316.2023.10164594
R. Venditti
A Multi-TeV muon collider is one of the best candidates for the future development of High Energy Particle physics in the post High Luminosity LHC era. Such a machine will allow to reach high center-of mass energy in leptonic collisions, thus opening the path to a vast and mostly unexplored physics program. However, the design of a suitable detection apparatus represents a technological challenge, mainly because of the unstable nature of the muons. The interaction of the muon decay products with the machine elements, can produce an intense flux of background particles that eventually reach the detector and may degrade its performance. In this contribution, the latest simulation studies performed to optimize the detector design will be presented, together with an overview of the detector technologies that have a potential to match the challenging specifications of a muon collider, with a focus on the ongoing R&D efforts.
多tev介子对撞机是后高光度LHC时代高能粒子物理学未来发展的最佳候选者之一。这样的机器将允许在轻子碰撞中达到较高的质心能量,从而为一个巨大的、大部分尚未开发的物理项目开辟了道路。然而,设计合适的探测设备是一项技术挑战,主要是因为μ子的不稳定性。μ子衰变产物与机器元件的相互作用可以产生强烈的背景粒子通量,最终到达探测器并可能降低其性能。在这篇文章中,将介绍为优化探测器设计而进行的最新模拟研究,以及有可能匹配μ子对撞机具有挑战性规格的探测器技术的概述,重点是正在进行的研发工作。
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引用次数: 0
ZnO based Back- and Front-Illuminated Photoresistor for UV Sensing Applications 紫外光感应用ZnO前后照光敏电阻器
Pub Date : 2023-06-08 DOI: 10.1109/IWASI58316.2023.10164377
A. Buzzin, Francesca Grossi, D. Cannatà, M. Benetti, G. Cesare, C. Caliendo
This work presents a versatile and low-cost photoresistor based on zinc oxide (ZnO). ZnO thin films were grown by RF reactive magnetron sputtering technique onto fused silica substrates. Metal planar electrodes were fabricated on top of the films to obtain a photoresistor. A device was tested for UV power amounts up to 65 mW/cm2 at 365 nm. The UV sensing performances were investigated for UV light illumination from the top surface of the ZnO film or from the bottom side through the substrate. Preliminary results highlight a dark current of 75 pA/cm2 at 1 V bias and electro-optical responsivities of around 1.1 μA/W and 540 nA/W for front-illumination and back-illumination mode, respectively. These data, together with the capability of the sensor to adapt to different scenarios, encourage possible implementations in the field of UV sensing in harsh environments.
本文提出了一种基于氧化锌(ZnO)的多功能低成本光敏电阻器。采用射频反应磁控溅射技术在熔融二氧化硅衬底上生长ZnO薄膜。金属平面电极被制作在薄膜的顶部以获得光敏电阻。在365 nm处测试了UV功率高达65 mW/cm2的装置。研究了紫外光从ZnO薄膜的上表面照射或从底侧穿过衬底照射时的紫外感应性能。初步结果显示,在1 V偏置下,暗电流为75 pA/cm2,前照明和后照明模式下的电光响应分别约为1.1 μA/W和540 nA/W。这些数据,加上传感器适应不同场景的能力,鼓励在恶劣环境下紫外线传感领域的可能实施。
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引用次数: 0
Session 2: Sensor systems and algorithms 第二部分:传感器系统和算法
Pub Date : 2023-06-08 DOI: 10.1109/iwasi58316.2023.10164515
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引用次数: 0
A combined SiPM-based TOF+RICH detector for future high-energy physics experiments 用于未来高能物理实验的基于sipm的TOF+RICH探测器
Pub Date : 2023-06-08 DOI: 10.1109/IWASI58316.2023.10164558
N. Nicassio, A. R. Altamura, C. Altomare, G. Robertis, D. Bari, A. D. Mauro, J. O. Guerra-Pulido, M. N. Mazziotta, E. Nappi, G. Paic, R. Pillera, G. Volpe
A novel compact particle identification (PID) detector concept based on Silicon Photomultipliers (SiPMs) optimized to perform combined Time-of-Flight (TOF) and Ring-Imaging Cherenkov (RICH) measurements using a common photosensitive sensor is under development. The system consists of a Cherenkov radiator layer separated from a photosensitive surface equipped with SiPMs by an expansion gap. A thin glass slab, acting as a second Cherenkov radiator, is coupled to the SiPMs to perform Cherenkov-based TOF measurements. We have built and tested a detector prototype including a 2 cm thick aerogel radiator and a 3 mm thick NaF slab. With a RICH resolution better than 1 mrad and a TOF resolution better than 50 ps, the present technology makes the proposed SiPM-based PID system particularly attractive for future high-energy physics experiments where space and cost constraints are critical. In this work, we discuss the principle of operation of the proposed TOF+RICH integration, with a particular focus on the optimization of the TOF radiator material, thickness and coupling with SiPMs, as well as the achievable angular and timing performance. Finally, preliminary beam test results for the considered detector prototype are presented.
一种基于硅光电倍增管(SiPMs)的新型紧凑型粒子识别(PID)探测器概念正在开发中,该探测器优化了使用普通光敏传感器进行飞行时间(TOF)和环成像切伦科夫(RICH)测量的组合。该系统由切伦科夫辐射层组成,通过膨胀间隙与配备sipm的光敏表面分离。一个薄玻璃板,作为第二个切伦科夫散热器,耦合到sipm执行基于切伦科夫的TOF测量。我们已经建立并测试了一个探测器原型,包括一个2厘米厚的气凝胶散热器和一个3毫米厚的NaF板。RICH分辨率优于1 mrad, TOF分辨率优于50 ps,目前的技术使所提出的基于sipm的PID系统对空间和成本限制至关重要的未来高能物理实验特别有吸引力。在这项工作中,我们讨论了所提出的TOF+RICH集成的工作原理,特别关注TOF散热器材料的优化,厚度和与sipm的耦合,以及可实现的角度和时序性能。最后给出了所考虑的探测器原型的初步光束测试结果。
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引用次数: 2
IWASI 2023 Blank Page IWASI 2023空白页
Pub Date : 2023-06-08 DOI: 10.1109/iwasi58316.2023.10164485
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引用次数: 0
A High-Gain Low-Noise Transimpedance Amplifier based on Active-Feedback Network 一种基于有源反馈网络的高增益低噪声跨阻放大器
Pub Date : 2023-06-08 DOI: 10.1109/IWASI58316.2023.10164441
E. Genco, Kyle van Oosterhout, Martijn Timmermans, M. Fattori
In this work, we present a novel TIA with ultra-high transimpedance gain, achieved without the use of pseudo-resistors or off-chip resistors. The proposed approach overcomes the conventional trade-offs between noise and gain in the design of a TIA with resistive feedback. The proposed architecture makes use of a transconductor in the TIA negative feedback path to achieve impedance multiplication and enable large transimpedance amplification. Moreover, thanks to the dominant pole positioned at the input of the TIA, circuit stability can be disentangled from the gain when different capacitive loads are connected to the input of the circuit. Simulation results reveal that it is possible to design a TIA with programmable transimpedance gain ranging from 5 M$Omega$ (134.1 dB$Omega$) to 5 G$Omega$(194.4 dB$Omega$) and exhibiting a 3dB bandwidth of 1.54 MHz and 23 kHz, respectively when coupled to a current-source with an output capacitance of 20 pF. At the frequency of 20 Hz, the TIA achieves an input referred noise current of 2fA/$sqrt{}$Hz and 20 fA/$sqrt{}$Hz, for the maximum and minimum gain, respectively. Moreover, the programmable TIA is unconditionally stable by design for any input capacitance equal to or larger than 20 pF. The proposed TIA is implemented in a TSMC 65nm CMOS technology node, it requires an area of 0.045 $mu m^{2}$ and consumes 850 $mu$W at a power supply of 1.2 V. Thanks to its high-gain, large bandwidth, low-noise performance and its flexibility with the respect to the input source capacitance value, the proposed solution is best suited for the interfacing highly capacitive sensors or as a versatile first stage for the noise performance characterization of solid-state devices.
在这项工作中,我们提出了一种具有超高跨阻增益的新型TIA,无需使用伪电阻或片外电阻即可实现。提出的方法克服了传统的电阻反馈TIA设计中噪声和增益之间的权衡。所提出的架构利用TIA负反馈路径中的transconductor来实现阻抗倍增并实现大的跨阻放大。此外,由于主导极位于TIA的输入端,当不同的容性负载连接到电路的输入端时,电路的稳定性可以与增益分离。仿真结果表明,当与输出电容为20pf的电流源耦合时,可以设计出具有5 M $Omega$ (134.1 dB $Omega$)至5 G $Omega$ (194.4 dB $Omega$)可编程跨阻增益的TIA,其3dB带宽分别为1.54 MHz和23 kHz。在20hz频率下,TIA的输入参考噪声电流分别为2fA/ $sqrt{}$ Hz和20fa / $sqrt{}$ Hz。分别为最大和最小增益。此外,可编程TIA在任何输入电容等于或大于20pf的情况下都具有无条件稳定性。该TIA在台积电65nm CMOS技术节点上实现,其面积为0.045 $mu m^{2}$,功耗为850 $mu$ W,电源为1.2 V。由于其高增益、大带宽、低噪声性能以及对输入源电容值的灵活性,所提出的解决方案最适合于连接高电容传感器或作为固态器件噪声性能表征的通用第一阶段。
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引用次数: 0
Towards Robust Velocity and Position Estimation of Opponents for Autonomous Racing Using Low-Power Radar 基于低功率雷达的自主赛车对手鲁棒速度和位置估计
Pub Date : 2023-06-08 DOI: 10.1109/IWASI58316.2023.10164312
Andrea Ronco, Nicolas Baumann, Marco Giordano, Michele Magno
This paper presents the design and development of an intelligent subsystem that includes a novel low-power radar sensor integrated into an autonomous racing perception pipeline to robustly estimate the position and velocity of dynamic obstacles. The proposed system, based on the Infineon BGT60TR13D radar, is evaluated in a real-world scenario with scaled race cars. The paper explores the benefits and limitations of using such a sensor subsystem and draws conclusions based on field-collected data. The results demonstrate a tracking error up to 0.21 ± 0.29m in distance estimation and 0.39 ± 0.19m/s in velocity estimation, despite the power consumption in the range of 10s of milliwatts. The presented system provides complementary information to other sensors such as LiDAR and camera, and can be used in a wide range of applications beyond autonomous racing.
本文介绍了一种智能子系统的设计和开发,该子系统包括一个集成在自主赛车感知管道中的新型低功耗雷达传感器,用于鲁棒估计动态障碍物的位置和速度。该系统基于英飞凌BGT60TR13D雷达,并在实际赛车场景中进行了评估。本文探讨了使用这种传感器子系统的优点和局限性,并根据现场收集的数据得出结论。结果表明,尽管功耗在10s毫瓦范围内,但距离估计误差为0.21±0.29m,速度估计误差为0.39±0.19m/s。该系统为激光雷达和摄像头等其他传感器提供补充信息,可用于自动驾驶赛车以外的广泛应用。
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引用次数: 1
期刊
2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)
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