... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks最新文献

英文中文

Infrared Photoelectric Sensor Network Applied to Remote Arthropod Insects' Surveillance 红外光电传感器网络在节肢动物昆虫远程监测中的应用

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010793400003118

Federico Gaona, Ever Quiñonez, Adolfo Jara, Ariel Manabe, Norma Silva, M. Monteiro, C. Schaerer, M. C. Vega, A. R. Arias

This work presents a monitoring system trap to detect the presence of arthropod insects in a remote surveillance zone. Detections are made using sensor traps that are installed in twenty houses of an indigenous village of the Paraguayan Chaco in South America, where the insects that transmit Chagas disease are pressing to infest the area. Pheromone baits are used to ensure the attraction of Triatoma infestans. For detecting variations of the light due to insect intrusion, trap entrances have photoelectric infrared sensors. Once the insect is detected, the information is collected and transmitted to an Internet database storage server. More than 750 intrusions were detected during nine months, the highest number of detections occurred when the temperature ranged between 20 °C and 34 °C, relative humidity average less than 30% and the precipitation was less than 1.5 mm. This new result provides evidence of the T. infestans activity at different times of the day and month, and its relationship with certain environmental variables. These findings contribute to reorientate surveillance procedures, validate the monitoring system proposal and give important information on the vector's life activity.

这项工作提出了一个监测系统陷阱，以检测节肢动物昆虫的存在在一个遥远的监视区。利用传感器陷阱进行检测，这些陷阱安装在南美洲巴拉圭查科一个土著村庄的20所房屋中，传播恰加斯病的昆虫正在该地区肆虐。使用费洛蒙诱饵以确保吸引感染三角瘤。为了检测由于昆虫入侵引起的光线变化，陷阱入口装有光电红外传感器。一旦检测到昆虫，信息就会被收集并传输到互联网数据库存储服务器。9个月共检测到入侵750余次，其中温度在20 ~ 34℃，平均相对湿度小于30%，降水量小于1.5 mm时检测到入侵次数最多。这一新结果提供了该菌在一天和一个月的不同时间活动的证据，以及它与某些环境变量的关系。这些发现有助于重新定位监测程序，验证监测系统建议，并提供有关病媒生命活动的重要信息。

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引用次数: 0

On Configuring Directional Transmission for Path Exposure Reliability in Energy Harvesting Wireless Sensor Networks 能量采集无线传感器网络中路径暴露可靠性的定向传输配置

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010981600003118

Abdulsalam Basabaa, E. Elmallah

In this paper, we consider a path exposure problem in energy harvesting wireless sensor networks (EH-WSNs) where nodes are equipped with directional communication devices. Nodes harvest energy from ambient environment (e.g., solar power), and manage fluctuations in their stored energy by adjusting some of their directional transmission parameters. Using a probabilistic graph model we formalize a problem, denoted DirEXPO-RU, that quantifies the ability of a network to detect and report traversal along a given path as probability representing the reliability of the network in performing the path monitoring task. A problem that arises in managing the network resources to maximize this reliability measure is to adjust the transmission beam width of each node, given that nodes beam centers are given as input. We develop a heuristic algorithm to deal with the problem, and use the algorithm in a framework for computing lower bounds on the reliability of the overall network. The obtained numerical results show improvement in the achieved network reliability.

在本文中，我们考虑了能量收集无线传感器网络(EH-WSNs)中节点配备定向通信设备的路径暴露问题。节点从周围环境中获取能量(例如太阳能)，并通过调整一些定向传输参数来管理其存储能量的波动。使用概率图模型，我们形式化了一个问题，称为DirEXPO-RU，该问题量化了网络检测和报告沿给定路径遍历的能力，作为表示网络执行路径监控任务的可靠性的概率。在给定节点波束中心作为输入的情况下，如何调整每个节点的传输波束宽度，是管理网络资源以使该可靠性度量最大化的一个问题。我们开发了一种启发式算法来处理这个问题，并在一个框架中使用该算法来计算整个网络的可靠性下界。数值结果表明，实现的网络可靠性得到了提高。

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引用次数: 0

Appropriate Integration of Wake-up Receivers in Simulations Tools based on Real Experiments 基于真实实验的唤醒接收机在仿真工具中的适当集成

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0011012500003118

Amina Whichi, R. Fromm, A. Fakhfakh, F. Derbel

Wireless Sensor Networks (WSNs) are an emerging and promising approach to Internet of Things (IoT). However, energy consumption is regarded as one of the most critical problems in WSNs due to the devices’ limits.To address this problem, an ultra-low-power radio receiver known as a wake-up receiver (WuRx) is used to handle idle listening while the main radio is turned off. Since simulators for performance prediction have become almost indispensable in the design and management of new hardware equipment and components, we will present in this paper the design of a wake-up receiver module, that could be a solution to the energy consumption’s challenge, in OMNeT++ and compare it to experimental results, focusing on energy performance and reliability factors.

无线传感器网络(wsn)是一种新兴的、有前途的物联网(IoT)方法。然而，由于设备的限制，能量消耗被认为是无线传感器网络中最关键的问题之一。为了解决这个问题，一个超低功耗的无线电接收器被称为唤醒接收器(WuRx)，用于在主无线电关闭时处理空闲收听。由于用于性能预测的模拟器在新硬件设备和组件的设计和管理中几乎不可或缺，我们将在本文中提出一个唤醒接收器模块的设计，这可能是解决能耗挑战的一个方案，在omnet++中，并将其与实验结果进行比较，重点关注能源性能和可靠性因素。

引用次数: 0

Surface Light Barriers 表面光屏障

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010777500003118

Theo Gabloffsky, B. Kruse, R. Salomon

It should be known to almost all readers that light barriers are commonly used for measuring the speed of various objects. These devices are easy to use, quite robust, and of low cost. Despite their advantages, light barriers exhibit certain limitations that occur when the objects of interest move in more than one spatial dimension. This paper discusses a physical setup in which light barriers can also be used in case of two-dimensional trajectories. However, this setup requires rather complicated calculations. Therefore, this paper performs these calculations by means of different neural network models. The results show that backpropagation networks as well as radial basis functions are able to achieve a residual error less than 0.21 %, which is more than sufficient for most sports and everyday applications.

几乎所有读者都应该知道，光屏障通常用于测量各种物体的速度。这些装置使用方便，坚固耐用，成本低。尽管具有优势，但当感兴趣的物体在多个空间维度上移动时，光屏障表现出一定的局限性。本文讨论了一种物理设置，其中光屏障也可以用于二维轨迹的情况下。然而，这种设置需要相当复杂的计算。因此，本文通过不同的神经网络模型来进行这些计算。结果表明，反向传播网络和径向基函数能够实现小于0.21%的残差，这对于大多数运动和日常应用来说已经足够了。

引用次数: 0

A New Architecture Proposal of Half-wave Precision Rectifier using a Single VCII 一种单VCII半波精密整流器的新结构方案

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010901900003118

L. Safari, G. Barile, Mattia Ragnoli, G. Ferri, V. Stornelli

In this paper a new second generation voltage conveyor (VCII) based half wave rectifier circuit architecture proposal is presented. Both inverting and non-inverting outputs in the form of voltage signal are produced. The proposed circuit is the first half wave rectifier architecture using VCIIs introduced in the literature. It consists of one VCII, two diodes and a single grounded resistor. The input signal is in current form and the rectified output voltage signal is provided at the low impedance Z port of the same VCII. Therefore, the produced output signal can be directly used with no need to add extra voltage buffers. In addition, the circuit gain is set by the grounded resistor value and can be tuned. The proposed circuit enjoys a simple transistorlevel structure employing only 21 transistors. In this paper, the architecture of the rectifier is presented and explained, as well as a possible VCII topology. Preliminary simulation results are also given highlighting its capabilities. Its simplicity and versatility make it suitable for sensor interfaces and processing circuits for sensor networks where a low power consumption for the analog processing section is of the utmost

本文提出了一种新的基于第二代电压输送机(VCII)的半波整流电路结构方案。产生电压信号形式的反相输出和非反相输出。所提出的电路是采用文献中介绍的vcii的前半波整流器结构。它由一个VCII，两个二极管和一个接地电阻组成。输入信号为电流形式，整流输出电压信号在同一VCII的低阻抗Z端口提供。因此，产生的输出信号可以直接使用，而无需添加额外的电压缓冲器。此外，电路增益由接地电阻值设定，并可调谐。所提出的电路具有简单的晶体管级结构，仅使用21个晶体管。本文介绍并解释了整流器的结构，以及一种可能的VCII拓扑结构。最后给出了初步的仿真结果。它的简单性和多功能性使其适用于传感器网络的传感器接口和处理电路，其中模拟处理部分的低功耗是最大的

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引用次数: 5

A Distributed Intelligent Intrusion Detection System based on Parallel Machine Learning and Big Data Analysis 基于并行机器学习和大数据分析的分布式智能入侵检测系统

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010886300003118

Faten Louati, F. Ktata, Ikram Amous

Networking security continue to be a serious challenge for all domains because of the increasing number of attacks launched every day due to the advent of connected devices and the emergence of the Internet. Hence, Intrusion detection system comes into focus, especially with the inception of big data challenges. In this paper, we propose a distributed and parallel intrusion detection system suitable for big data environments using machine learning-based multi agent system and big data analysis.

由于连接设备的出现和互联网的出现，每天发起的攻击数量不断增加，网络安全仍然是所有领域面临的严峻挑战。因此，随着大数据挑战的开始，入侵检测系统成为人们关注的焦点。本文利用基于机器学习的多智能体系统和大数据分析，提出了一种适合大数据环境的分布式并行入侵检测系统。

引用次数: 1

Storage Allocation for Camera Sensor Networks using Feedback-based Price Discrimination 基于反馈价格歧视的相机传感器网络存储分配

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2022-01-01 DOI: 10.5220/0010858500003118

Alexandre Martins, Hung-Yu Wei, Karl-Erik Årzén

Camera sensor networks, mainly with surveillance cameras, are growing in size and complexity. Storage space is the prime resource in such systems but current surveillance setups are still very much centralized and limited in resources due to cost and security constraints. Allocating the correct amount of storage to each camera sensor considering their large difference in characteristics and video content is challenging. In this paper we propose a framework using feedback-based price discrimination of storage resources in order to guarantee a uniform quality level of the videos in camera sensor networks, regardless of the specific camera sensor parameters. We designed a lightweight solution using simple video quality metrics, cascade control and PI (Proportional and Integral) controllers to define the optimal price of resources per camera.

摄像头传感器网络，主要是监控摄像头，在规模和复杂性上都在增长。存储空间是此类系统的主要资源，但由于成本和安全限制，目前的监控设置仍然非常集中，资源有限。考虑到每个相机传感器在特性和视频内容上的巨大差异，分配正确的存储空间是一项挑战。在本文中，我们提出了一个基于反馈的存储资源价格歧视框架，以保证摄像机传感器网络中视频的统一质量水平，而不管特定的摄像机传感器参数。我们设计了一个轻量级的解决方案，使用简单的视频质量指标，级联控制和PI(比例和积分)控制器来定义每个摄像机的最佳资源价格。

引用次数: 0

Towards Noninvasive Accurate Detection of Intrapartum Fetal Hypoxic Distress. 无创准确检测分娩期胎儿缺氧窘迫。

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2021-07-01 Epub Date: 2021-08-16 DOI: 10.1109/bsn51625.2021.9507036

Begum Kasap, Kourosh Vali, Weitai Qian, Herman L Hedriana, Aijun Wang, Diana L Farmer, Soheil Ghiasi

Current intrapartum fetal well-being assessment is performed using electronic fetal monitoring (EFM), technically referred to as cardiotocography (CTG), which transabdominally monitors fetal heart rate (FHR) in relationship to maternal uterine contractions. Sometimes the deceleration in FHR following a uterine contraction can be sign of fetal hypoxic distress, but it may also be a normal physiological response. Multiple studies have shown that EFM has a high false positive rate for detecting fetal hypoxia. This has caused a rise in emergency Cesarean section (C-section) deliveries performed in the US over the years, while the rates of various conditions associated with anoxic brain injury at birth remain unchanged. The underlying problem is that many factors other than hypoxia can cause non-reassuring CTG traces and a more objective measure of oxygen supply to the fetal brain is not conveniently available. We are working to develop a transabdominal fetal pulse oximetry (TFO) system to non-invasively measure fetal arterial blood oxygen saturation (FSpO2) in order to enhance intrapartum fetal monitoring. This paper gives an overview of the past and ongoing work performed to develop TFO, highlights the main engineering and clinical challenges faced and presents preliminary results that demonstrate feasibility of TFO in both pregnant sheep models and human subjects.

目前的产时胎儿健康评估是使用电子胎儿监测（EFM）进行的，技术上称为心脏分娩描记术（CTG），它通过腹部监测胎儿心率（FHR）与母体宫缩的关系。有时，子宫收缩后FHR的减速可能是胎儿缺氧窘迫的迹象，但也可能是一种正常的生理反应。多项研究表明，EFM在检测胎儿缺氧方面具有较高的假阳性率。这导致了美国多年来紧急剖腹产（剖腹产）的增加，而与出生时缺氧性脑损伤相关的各种情况的发生率保持不变。潜在的问题是，除了缺氧之外，许多因素都会导致不令人放心的CTG痕迹，而且无法方便地获得更客观的胎儿大脑氧气供应测量。我们正在开发一种经腹部胎儿脉搏血氧计（TFO）系统，以非侵入性测量胎儿动脉血氧饱和度（FSpO2），从而加强产时胎儿监测。本文概述了过去和正在进行的开发TFO的工作，强调了面临的主要工程和临床挑战，并提出了初步结果，证明了TFO在怀孕绵羊模型和人类受试者中的可行性。

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引用次数: 2

PAIoT Network: A Unique Regional IoT Network for Very Different Applications PAIoT网络:一个独特的区域物联网网络，用于非常不同的应用

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2021-01-01 DOI: 10.5220/0010321401070112

S. Nanni, G. Mazzini

LepidaSpa, the ICT in-house company of the Public Administrations of the Emilia Romagna region, has realized a regional IoT public network‡, based on the LoRaWan§ technology, free of charge for all public administrations, as well as to private citizens, potentially enabling the collection of relevant data from thousands of new sensors and making them accessible to both the owners of the sensors and, limitedly to institutional or public interest scopes, to every PA entity. The innovative aspects of the proposed solution mainly concern the extreme simplicity of the sensors installation, the low entry costs for stakeholders, both public and private, who want to deploy their own sensors, a centralized service that collects and makes data available in the cloud, the replicability of IoT projects on a regional scale.

LepidaSpa是艾米利亚罗马尼亚地区公共管理部门的ICT内部公司，已经实现了一个基于LoRaWan技术的区域物联网公共网络‡，该网络免费向所有公共管理部门和普通公民开放，有可能从数千个新传感器收集相关数据，并使传感器所有者和每个PA实体(仅限于机构或公共利益范围)都可以访问这些数据。提出的解决方案的创新方面主要涉及传感器安装的极端简单性，想要部署自己的传感器的公共和私人利益相关者的低入门成本，在云中收集和提供数据的集中服务，以及物联网项目在区域范围内的可复制性。

引用次数: 1

Mirror Mosaicking: A Novel Approach to Achieve High-performance Classification of Gases Leveraging Convolutional Neural Network 镜像镶嵌:利用卷积神经网络实现高性能气体分类的新方法

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks

Pub Date : 2021-01-01 DOI: 10.5220/0010251500860091

S. N. Chaudhri, N. S. Rajput

Limited dimensionality of the dataset obtained from an electronic nose (EN) is due to the number of elements in the sensor array used generally in the range of 4-8 elements only. Further, large number of sensor data can be generated by sampling the sensor responses both during the transient and steady states. The lowerdimensionality of sensor data prohibits the use of a convolutional neural network (CNN)-based pattern recognition techniques because the kernels of a CNN cannot be used on the obtained sample vectors to extract the features. In this paper, we have proposed a novel approach to enhance the data dimensionality keeping the sensor response characteristics absolutely unaltered. By leveraging the concept of mirror mosaicking technique, we have upscaled the input sample vectors into a 6×6 2-D input arrays to train the shallow CNN. Using the proposed approach, all the 16-unknown steady-state test samples classified accurately which are not used during the training. Moreover, the parameters of the classification report viz., Precision, Recall, and F1 score also obtained with a fraction value of 1.00. The proposed technique is a generic approach that can be used to classify various low-dimensional datasets obtained from various sensor arrays in various fields.

从电子鼻(EN)获得的数据集的有限维度是由于传感器阵列中使用的元素数量通常仅在4-8个元素范围内。此外，通过在瞬态和稳态期间对传感器响应进行采样，可以生成大量传感器数据。传感器数据的低维性阻碍了基于卷积神经网络(CNN)的模式识别技术的使用，因为卷积神经网络的核不能用于获得的样本向量来提取特征。在本文中，我们提出了一种新的方法来提高数据维数，保持传感器的响应特性绝对不变。通过利用镜像拼接技术的概念，我们将输入样本向量升级为6×6二维输入阵列来训练浅层CNN。采用该方法对训练中未使用的16个未知稳态测试样本进行了准确分类。此外，还得到了分类报告的参数Precision、Recall和F1分数，分数值为1.00。所提出的技术是一种通用的方法，可用于分类从不同领域的各种传感器阵列获得的各种低维数据集。

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引用次数: 5

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