2022 Smart Systems Integration (SSI)最新文献

Effect of Surface Uniformity and Droplet Volume on Actuation Voltage of PCB Based EWOD Microfluidic System 表面均匀性和液滴体积对基于PCB的EWOD微流体系统驱动电压的影响

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/SSI56489.2022.9901428

Wail Al-Mogahed, S. Voigt, J. Mehner

{"title":"Effect of Surface Uniformity and Droplet Volume on Actuation Voltage of PCB Based EWOD Microfluidic System","authors":"Wail Al-Mogahed, S. Voigt, J. Mehner","doi":"10.1109/SSI56489.2022.9901428","DOIUrl":"https://doi.org/10.1109/SSI56489.2022.9901428","url":null,"abstract":"Electrowetting on Dielectrics (EWOD) is an important method of manipulating discrete fluid droplets in digital microfluidic systems. In this paper, a simply implemented low cost EWOD system based on printed circuit board was built and tested. The form of the triple contact line (TCL) connecting the droplet with solid surface and ambient surrounding was simulated using a numerical simulation tool called Surface Evolver (SE). Different electrode patterns and sizes were designed and measurements were conducted using deionized (DI) water mixed with Sodium Chloride (NaCl) as fluidic samples. Polytetrafluoroethylene (PTFE), Parylene C and Parafilm were used as dielectric layers separating microfluidic droplets from the electrodes surface. In addition, these materials provided a hydrophobic surface leading to an increase in the initial contact angle of the droplets. The actuation voltage of the system varied between 40 V and 183 V depending on the electrodes pattern and size and the volume of the droplets. The smoothness and regularity of the PCB and hydrophobic surfaces had a major effect on decreasing the actuation voltage of the system.","PeriodicalId":339250,"journal":{"name":"2022 Smart Systems Integration (SSI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116226016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Touch Sensor Based on Highly Compressive Magnetic Foam Composite 基于高压缩磁性泡沫复合材料的触摸传感器

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/SSI56489.2022.9901425

G. Diguet, J. Froemel, M. Muroyama, Koichi Ohtaka

引用次数: 0

Comparison of Artificial and Spiking Neural Networks for Ambient-Assisted Living 环境辅助生活中人工神经网络与脉冲神经网络的比较

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/ssi56489.2022.9901412

Sven Nitzsche, Brian Pachideh, Moritz Neher, Marius Kreutzer, Norbert Link, Lukas Theurer, J. Becker

{"title":"Comparison of Artificial and Spiking Neural Networks for Ambient-Assisted Living","authors":"Sven Nitzsche, Brian Pachideh, Moritz Neher, Marius Kreutzer, Norbert Link, Lukas Theurer, J. Becker","doi":"10.1109/ssi56489.2022.9901412","DOIUrl":"https://doi.org/10.1109/ssi56489.2022.9901412","url":null,"abstract":"In assisted living environments, various situations may arise where a person falls or is otherwise injured and is unable to call for help on their own. In such situations, it is necessary to quickly identify the problem and take appropriate action, such as calling for help. This can be supported or even automated by using vision-based AI systems. In this context, we investigated and evaluated different AI solutions for rapid human action recognition. More specifically, we trained and compared artificial neural networks (ANN) in combination with frame-based cameras to a processing pipeline using spiking neural networks (SNN) and event-based cameras. For the SNNs, we further distinguished and compared two models, which we simulated in software and implemented on event-based hardware. The SNNs feature various layer types, e.g. fully-connected, spiking convolutions and recurrent. The implementation on event-based hardware was compared to GPU-based embedded hardware for artificial neural networks. The comparison was made primarily with regard to the highest possible energy efficiency in order to enable battery-powered vision systems in the future that can be used flexibly not only in assisted living, but also in industrial and smart city applications. The networks were constructed in such a way that they achieve a similar classification accuracy, which was measured on our own dataset specifically recorded for the project.","PeriodicalId":339250,"journal":{"name":"2022 Smart Systems Integration (SSI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131606176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

AEFishBIT: a smart system to monitor fish activity and welfare AEFishBIT:监测鱼类活动和福利的智能系统

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/SSI56489.2022.9901419

Manuel Lozano, E. Cabruja, J. Pérez‐Sánchez, Josep Calduch Giner, Juan Antonio Montiel-Nelson, J. Sosa, A. Vega, Miguel A. Ferrer

引用次数: 0

Functional CMOS extension with integrated carbon nano devices 集成碳纳米器件的功能CMOS扩展

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/SSI56489.2022.9901422

Böttger Simon, Dietz Franz, Martin Hartmann, Dahra Nipun, K.-R. Eberhard, Hermann Sascha

{"title":"Functional CMOS extension with integrated carbon nano devices","authors":"Böttger Simon, Dietz Franz, Martin Hartmann, Dahra Nipun, K.-R. Eberhard, Hermann Sascha","doi":"10.1109/SSI56489.2022.9901422","DOIUrl":"https://doi.org/10.1109/SSI56489.2022.9901422","url":null,"abstract":"In recent years there has been a steep increase in application and system complexity driven by trends such as Internet of Things (IoT), Industry 4.0 or autonomous driving. Hence, there is a massive demand for cyber-physical systems (CPS) merging sensoric, electronic and communication capabilities. Nanomaterials such as Carbon Nanotubes (CNTs) prospect significant added value for such systems, as they inherently feature low energy consumption, superior sensitivity for bio- , optical-, and mechanical sensing and even high amplification linearity in FETs. However, complemented new functionalities still rely on conventional system architectures requiring complementary metal oxide semiconductor (CMOS) based application-specific integrated circuits (ASICs) with the corresponding front-(FEOL) and back-end-of-line (BEOL). Hence, post-CMOS hetero-integration technologies for upgrading conventional IC’s with nanomaterial based devices is a highly promising path in the context of More than Moore scaling. At the example of condition monitoring, we demonstrate the applicability of CNT strain sensors towards holistic prognostic health monitoring (PHM) approaches of forthcoming electronic systems. Therefore, we develop a CMOS compatible technology platform for integrated CNT field-effect transistors (FETs) serving as the core building block for various system on chip (SOC) applications in analogue high frequency electronics, hardware security, biosensing or condition monitoring.","PeriodicalId":339250,"journal":{"name":"2022 Smart Systems Integration (SSI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123323683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Backscattered Visual Light Positioning using LED Sensing in Combination with Edge Computing based Artificial Neural Network Classification 结合基于边缘计算的人工神经网络分类的LED传感背向散射视觉光定位

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/ssi56489.2022.9901418

Christian Fragner, A. Weiss, F. Wenzl

{"title":"Backscattered Visual Light Positioning using LED Sensing in Combination with Edge Computing based Artificial Neural Network Classification","authors":"Christian Fragner, A. Weiss, F. Wenzl","doi":"10.1109/ssi56489.2022.9901418","DOIUrl":"https://doi.org/10.1109/ssi56489.2022.9901418","url":null,"abstract":"Indoor Positioning Systems gained notable interest in the recent years. Amongst the various applied technologies and methods, positioning systems that utilize the visible light spectrum, have proven to be ideal candidates to establish such systems. Amongst other embodiments, visible light based systems can be realized by applying backscattered scenarios, where only reflections from the object of interest are utilized to infer its position. This backscattering approach has the advantage that the light source and the photosensitive device can be integrated into the same module. In this work we combine such a backscattering approach with the innovative approach in order to utilize LEDs not only as light sources, but also as receiving elements. Our novel approach demonstrates a sophisticated control mechanism, that uses 4 LEDs as light sources and receiving elements, without any disturbance in the provided illumination being perceivable to an observer. By utilizing an Artificial Neural Network, we perform the task of position determination on the edge, demonstrating the great potential of our solution approach. We verify our approach by experimental results, showing that the position (quadrant) in which a retroreflective foil is located, can be determined correctly with more than 92% accuracy, thus showing the advanced implementation of a highly integrated smart system.","PeriodicalId":339250,"journal":{"name":"2022 Smart Systems Integration (SSI)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124856952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of a MEMS-Based Fully Passive Wireless Pressure Sensor for Harsh Environments 基于mems的恶劣环境全无源无线压力传感器的设计

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/SSI56489.2022.9901429

Romain Alcesilas, P. Rey, C. Jouvaud, M. Sansa, J. Bastien, C. Delaveaud

引用次数: 0

Modeling and Characterization of a 3D Environment for the Design of an Inductively Based Locating Method by Coil Couplings 基于线圈耦合器的电感式定位方法的三维环境建模与表征

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/ssi56489.2022.9901416

Sven Lange, C. Hedayat, H. Kuhn, U. Hilleringmann

引用次数: 0

High-resolution projection lithography for MEMS-applications using thick photoresist AZ 10XT 采用厚光刻胶az10xt的mems应用的高分辨率投影光刻

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/ssi56489.2022.9901437

Sebastian Schermer, C. Helke, Danhe Song, D. Reuter, H. Kuhn

引用次数: 0

Characterization of a cMUT as a gas sensor for a fast-response electronic nose cMUT作为快速响应电子鼻气体传感器的特性研究

2022 Smart Systems Integration (SSI) Pub Date : 2022-04-27 DOI: 10.1109/SSI56489.2022.9901410

Boutonnet Charles, Vialletelle Adrien, Legoux Christophe, Bastien Jean-Claude, Blard Francois, Herrier Cyril, Livache Thierry, Fain Bruno

引用次数: 0