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Optimal Sensor Placement for Human Activity Recognition with a Minimal Smartphone-IMU Setup 用最小的智能手机- imu设置进行人类活动识别的最佳传感器放置
Vincent Xeno Rahn, Lin Zhou, Eric Klieme, B. Arnrich
Human Activity Recognition (HAR) of everyday activities using smartphones has been intensively researched over the past years. Despite the high detection performance, smartphones can not continuously provide reliable information about the currently conducted activity as their placement at the subject’s body is uncertain. In this study, a system is developed that enables real-time collection of data from various Bluetooth inertial measurement units (IMUs) in addition to the smartphone. The contribution of this work is an extensive overview of related work in this field and the identification of unobtrusive, minimal combinations of IMUs with the smartphone that achieve high recognition performance. Eighteen young subjects with unrestricted mobility were recorded conducting seven daily-life activities with a smartphone in the pocket and five IMUs at different body positions. With a Convolutional Neural Network (CNN) for activity recognition, activity classification accuracy increased by up to 23% with one IMU additional to the smartphone. An overall prediction rate of 97% was reached with a smartphone in the pocket and an IMU at the ankle. This study demonstrated the potential that an additional IMU can improve the accuracy of smartphone-based HAR on daily-life activities.
过去几年,人们对智能手机日常活动的人类活动识别(HAR)进行了深入研究。尽管智能手机具有很高的检测性能,但由于它们在受试者身体上的位置是不确定的,因此无法持续提供有关当前进行的活动的可靠信息。在本研究中,开发了一个系统,可以实时收集来自各种蓝牙惯性测量单元(imu)和智能手机的数据。这项工作的贡献是对该领域相关工作的广泛概述,以及识别不显眼的imu与智能手机的最小组合,以实现高识别性能。18名活动能力不受限制的年轻受试者在口袋里装着智能手机,在不同的身体姿势下使用5个imu进行7项日常生活活动。使用卷积神经网络(CNN)进行活动识别,在智能手机上增加一个IMU,活动分类准确率提高了23%。在口袋里放一个智能手机,脚踝上放一个IMU时,总体预测率达到了97%。这项研究表明,额外的IMU可以提高基于智能手机的HAR对日常生活活动的准确性。
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引用次数: 3
Advances in Sensing Technologies for Smart Monitoring in Precise Agriculture 面向精准农业智能监测的传感技术研究进展
L. Maiolo, D. Polese
The demand for a continuous increment of crop production reducing at the same time the impact on the used resources is a challenge that can be solved only exploiting the full potential of sensors technology applied in precise agriculture. In this review, we present the most recent advances in remote sensing technologies to be deployed in field and in greenhouses to monitor multiple key parameters such as air temperature, solar radiation, vegetative index, plant microclimate, soil feature, etc.
对作物产量持续增长的需求,同时减少对已使用资源的影响,这是一个挑战,只有充分利用应用于精准农业的传感器技术的潜力,才能解决这个问题。本文综述了应用于田间和温室的遥感技术的最新进展,以监测空气温度、太阳辐射、植被指数、植物小气候、土壤特征等多个关键参数。
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引用次数: 5
System for Supporting Implementation and Monitoring of Smart Campus Applications based on IoT Protocols 基于物联网协议的智慧校园应用支持实施与监控系统
Franklin A. M. Venceslau, R. Gomes, I. Fonseca
This paper descbribes a system for monitoring Smart Campus applications based on IoT protocols. The system have as main goals to support the deployment of new sensors, actuators, and gateways in the campus, based on a pre-deployed network infrasctructure, and to monitor the performance of applications along the time. The network architecture considered in this paper provides reliability through the use of diversity techniques at physical and data link layers, based on the IEEE 802.15.4g SUN standard, and it performs the persistence of information based on time series database. In order to support the network infrastructure evolution and the incorporation of new devices and applications, information about the currently running applications and about the quality of the data links and the wireless network’s overload level can be collected by the proposed system. In this position paper, the architecture of the system is described in details, and initial results are discussed.
介绍了一种基于物联网协议的智能校园应用监控系统。该系统的主要目标是支持基于预部署的网络基础设施在校园中部署新的传感器、执行器和网关,并随时监控应用程序的性能。本文所考虑的网络架构基于IEEE 802.15.4g SUN标准,通过在物理层和数据链路层使用分集技术来提供可靠性,并基于时间序列数据库实现信息的持久化。为了支持网络基础设施的发展和新设备和应用程序的合并,有关当前运行的应用程序、数据链路的质量和无线网络的过载水平的信息可以被提议的系统收集。在本文中,详细描述了该系统的体系结构,并讨论了初步结果。
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引用次数: 0
Smart Farming in sub-Saharan Africa: Challenges and Opportunities 撒哈拉以南非洲的智慧农业:挑战与机遇
P. Abbott, Alessandro Checco, D. Polese
Smallholder farmers provide the majority of food production in sub-Saharan Africa. They will be severely impacted by climate change, especially because they are dependent on rain-fed irrigation. We provide a summary of challenges and opportunities in designing smart farming infrastructure in this context. We observe that innovation in technology and knowledge production is necessary to increase the efficacy of water usage and land management. Such solutions must take into account the technological constraints and their regional variability to be able to provide sustainable and scalable solutions. Such solutions also need to embrace the notion of openness, encouraging collaborative endeavour and avoiding proprietary
在撒哈拉以南非洲,小农提供了大部分粮食生产。它们将受到气候变化的严重影响,特别是因为它们依赖雨水灌溉。我们总结了在这种背景下设计智能农业基础设施的挑战和机遇。我们注意到,技术创新和知识生产是提高水资源利用和土地管理效率的必要条件。此类解决方案必须考虑到技术限制及其区域差异,以便能够提供可持续和可扩展的解决方案。这样的解决方案还需要包含开放的概念,鼓励合作努力,避免专有
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引用次数: 3
Linoc: A Prototyping Platform for Capacitive and Passive Electrical Field Sensing Linoc:电容和无源电场传感的原型平台
Julian von Wilmsdorff, Malte Lenhart, Florian Kirchbuchner, Arjan Kuijper
In this paper the Linoc prototyping toolkit is presented. It is a sensor toolkit that focuses on fast prototyping of sensor systems, especially on capacitive ones. The toolkit is built around two capacitive and two Electric Potential Sensing (EPS) groups providing unobtrusive proximity detection in the field of Human Computer Interface (HCI). The toolkits focus lies on its usability and connectivity in order to be adapted in future research and novel use cases. A common obstacle in the beginning of a project is the time required to familiarize with present tools and systems, before the actual project can be attended to. Another obstacle while tackling new tasks is the actual physical connection of sensors to the processing unit. This situation can be even worse due to dependencies on previous work, most of the times not fully documented and missing knowledge even if the the original designer is involved. Good toolkits can help to overcome this problem by providing a layer of abstraction and allowing to work on a higher level. If the toolkit however requires too much time to familiarize or behaves too restrictive, its goal has been missed and no benefits are generated. To assess the quality of the Linoc prototyping toolkit, it was evaluated in terms of three different aspects: demonstration, usage and technical performance. The usage study found good reception, a fast learning curve and an interest to use the toolkit in the future. Technical benchmarks for the capacitive sensors show a detectable range equal to its predecessors and several operational prototypes prove that the toolkit can actually be used in projects.
本文介绍了Linoc原型工具包。它是一个传感器工具包,专注于传感器系统的快速原型,特别是在电容式的。该工具包围绕两个电容和两个电位传感(EPS)组构建,在人机界面(HCI)领域提供不显眼的接近检测。该工具包的重点在于其可用性和连接性,以便适应未来的研究和新的用例。在项目开始时,一个常见的障碍是在实际的项目开始之前,熟悉现有的工具和系统所需要的时间。处理新任务时的另一个障碍是传感器与处理单元的实际物理连接。由于依赖于之前的工作,这种情况可能会变得更糟,即使原始设计师参与其中,大多数情况下也没有完整的文档记录和知识缺失。好的工具包可以通过提供一个抽象层并允许在更高的层次上工作来帮助克服这个问题。但是,如果工具包需要太多的时间来熟悉,或者行为过于严格,那么它的目标就没有实现,也不会产生任何好处。为了评估Linoc原型工具包的质量,它从三个不同的方面进行了评估:演示、使用和技术性能。使用研究发现了良好的接收,快速的学习曲线和在未来使用该工具包的兴趣。电容式传感器的技术基准显示,其可探测范围与前代产品相当,几个可操作的原型证明,该工具包实际上可以在项目中使用。
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引用次数: 1
Efficient Flash Indexing for Time Series Data on Memory-constrained Embedded Sensor Devices 内存受限嵌入式传感器设备上时间序列数据的高效Flash索引
Scott Fazackerley, Nadir Ould-Khessal, R. Lawrence
Embedded sensor devices with limited hardware resources must efficiently collect environmental and industrial time series data for analysis. Performing data analysis on the device requires data storage and indexing that minimizes memory, I/O, and energy usage. This paper presents an index structure that is optimized for the constrained use cases associated with sensor time series collection and analysis. By supporting only planned queries and analysis patterns, the storage and indexing implementation is simplified, and outperforms general techniques based on hashing and trees. The indexing technique is analyzed and compared with other indexing approaches and is adapted to all flash memory types including memory that supports overwriting.
硬件资源有限的嵌入式传感器设备必须有效地收集环境和工业时间序列数据进行分析。在设备上执行数据分析需要数据存储和索引,从而最大限度地减少内存,I/O和能源消耗。本文提出了一种索引结构,该结构针对与传感器时间序列收集和分析相关的受限用例进行了优化。通过只支持计划好的查询和分析模式,简化了存储和索引实现,并且优于基于散列和树的一般技术。该索引技术与其他索引方法进行了分析和比较,适用于所有闪存类型,包括支持覆盖的存储器。
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引用次数: 3
Digital Villages: A Data-Driven Approach to Precision Agriculture in Small Farms 数字村庄:小农场精准农业的数据驱动方法
R. Fishman, M. Ghosh, Amit Mishra, Shmuel Shomrat, Meshi Laks, Roy Mayer, Aakash Jog, E. Ben-Dor, Y. Shacham-Diamand
An approach for system monitoring of smallholder farms. The system will be based on low-cost mobile units (i.e. IoTs, phones) collecting and transmitting data directly from the farms. The IoT information will be merged with available and free access satellite data to form near real-time thematic images to the end-users. It will serve people with low technical literacy who are working with smallholders in developing countries. The novelty of using an integrated interdisciplinary behavioral-technological approach that builds on our respective disciplinary expertise, and the ability to pilot and implement at scale through partnerships, on the ground, allowing gaining new insights into smallholder cultivation and revolutionizing agricultural extension in the developing world. To achieve that goal of Holistic Integrated Precision Agriculture Network (HIPAN) three networks have been established in experimental farms in India: wireless network for “on-the-ground” sensing, virtual network with satellite multispectral imaging-based data and social network collecting the farmers’ inputs. The three networks are fused together and the data is processed using a cloud supported data analysis; the results are visually transferred to the farmers as well as to organizations and companies for their
一种对小农农场进行系统监测的方法。该系统将基于低成本的移动设备(即物联网,电话)直接从农场收集和传输数据。物联网信息将与可用和免费获取的卫星数据合并,形成接近实时的主题图像,提供给最终用户。它将为发展中国家与小农一起工作的低技术素养的人提供服务。利用基于我们各自学科专长的综合跨学科行为技术方法的新颖性,以及通过合作伙伴关系在实地进行大规模试点和实施的能力,使我们能够对发展中国家的小农种植和革命性的农业推广获得新的见解。为了实现整体综合精准农业网络(HIPAN)的目标,印度的实验农场已经建立了三个网络:用于“地面”传感的无线网络、基于卫星多光谱成像数据的虚拟网络和收集农民投入的社交网络。三个网络融合在一起,使用云支持的数据分析处理数据;结果直观地传递给农民以及组织和公司,以供他们使用
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引用次数: 3
Anomaly Detection in Beehives using Deep Recurrent Autoencoders 基于深度循环自编码器的蜂箱异常检测
Padraig Davidson, M. Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, A. Hotho
Precision beekeeping allows to monitor bees' living conditions by equipping beehives with sensors. The data recorded by these hives can be analyzed by machine learning models to learn behavioral patterns of or search for unusual events in bee colonies. One typical target is the early detection of bee swarming as apiarists want to avoid this due to economical reasons. Advanced methods should be able to detect any other unusual or abnormal behavior arising from illness of bees or from technical reasons, e.g. sensor failure. In this position paper we present an autoencoder, a deep learning model, which detects any type of anomaly in data independent of its origin. Our model is able to reveal the same swarms as a simple rule-based swarm detection algorithm but is also triggered by any other anomaly. We evaluated our model on real world data sets that were collected on different hives and with different sensor setups.
通过在蜂箱上安装传感器,精确养蜂可以监测蜜蜂的生活状况。这些蜂箱记录的数据可以通过机器学习模型进行分析,以学习蜂群的行为模式或搜索蜂群中的异常事件。一个典型的目标是早期发现蜂群,因为养蜂人由于经济原因想要避免这种情况。先进的方法应该能够检测到由蜜蜂疾病或技术原因(如传感器故障)引起的任何其他异常或异常行为。在这篇论文中,我们提出了一种自动编码器,一种深度学习模型,可以检测数据中独立于其来源的任何类型的异常。我们的模型能够像简单的基于规则的群体检测算法一样揭示相同的群体,但也可以由任何其他异常触发。我们在真实世界的数据集上评估了我们的模型,这些数据集是在不同的蜂巢和不同的传感器设置上收集的。
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引用次数: 15
papagenoX: Generation of Electronics and Logic for Embedded Systems from Application Software 从应用软件到嵌入式系统的电子和逻辑的生成
Tobias Scheipel, M. Baunach
Embedded systems development usually starts with hardware engineering based on specific requirements of the systems. These requirements are mainly derived from the needs of the not yet developed software to be executed on the system. This process is predictive and many iterations are thus needed, as new requirements often arise during the software development period. In the future, the market will demand more and more sophisticated embedded systems with a much reduced time to market. It will thus be inevitable that system prototypes and series products will need to be created as fast as possible. To enable this, we propose a top-down approach termed papagenoX, dealing with the question of “How to generate all layers X of the embedded systems stack including hardware and reconfigurable logic units from application software?”. The present work is a work in progress and deals with the definition of the research questions and several ideas and concepts of how to fundamentally solve them. Hence, it aims at introducing ideas to create a generator for embedded systems electronics, reconfigurable logic and software.
嵌入式系统开发通常从基于系统特定需求的硬件工程开始。这些需求主要来源于尚未开发的软件在系统上执行的需求。这个过程是可预测的,因此需要多次迭代,因为在软件开发期间经常出现新的需求。在未来,市场将需要越来越复杂的嵌入式系统,而上市时间将大大缩短。因此,系统原型和系列产品将不可避免地需要尽快创建。为了实现这一点,我们提出了一种自上而下的方法,称为papagenoX,处理“如何从应用软件生成嵌入式系统堆栈的所有层X,包括硬件和可重构逻辑单元?”的问题。目前的工作是一项正在进行的工作,涉及研究问题的定义以及如何从根本上解决这些问题的几个想法和概念。因此,它旨在介绍为嵌入式系统电子,可重构逻辑和软件创建生成器的想法。
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引用次数: 0
A Sensor Network for Existing Residential Buildings Indoor Environment Quality and Energy Consumption Assessment and Monitoring: Lessons Learnt from a Field Experiment 基于传感器网络的既有住宅室内环境质量与能耗评价与监测:基于现场试验的经验
Mathieu Bourdeau, David Werner, P. Basset, E. Nefzaoui
Enhancing residential buildings energy efficiency has become a critical goal to take up current challenges of human comfort, urbanization growth and the consequent energy consumption increase. In a context of integrated smart infrastructures, sensor networks offer a relevant solution to support building energy consumption monitoring, operation and prediction. The amount of accessible data with such networks also opens new prospects to better consider key parameters such as human behaviour and to lead to more efficient energy retrofit of existing buildings. However, sensor networks planning and implementation in general, and in existing buildings in particular, is a particularly complex task facing many challenges and affecting the performances of such a promising solution. In the present paper, we report on a field experiment of a sensor network deployment involving more than 250 sensors in three collective residential buildings in Paris region for the evaluation of a deep energy retrofit. More specifically, we describe the whole process of the sensor network design and roll-out and highlight the main critical aspects in such complex process. We also provide a feedback after several months of the sensor network operation and preliminary analysis of collected data. Reported results path the way for an efficient and optimized design and deployment of sensor networks for energy and indoor environment quality monitoring in existing buildings.
提高住宅建筑的能源效率已成为应对当前人类舒适、城市化发展和随之而来的能源消耗增加的挑战的关键目标。在集成智能基础设施的背景下,传感器网络为支持建筑能耗监测、运行和预测提供了相关的解决方案。这种网络的可访问数据量也为更好地考虑人类行为等关键参数以及对现有建筑进行更有效的能源改造开辟了新的前景。然而,一般来说,传感器网络的规划和实施,特别是在现有建筑中,是一项特别复杂的任务,面临着许多挑战,并影响着这种有前途的解决方案的性能。在本文中,我们报告了在巴黎地区的三个集体住宅建筑中部署250多个传感器的传感器网络的现场实验,以评估深度能源改造。更具体地说,我们描述了传感器网络设计和推出的整个过程,并强调了这一复杂过程中的主要关键方面。我们还在几个月的传感器网络运行和收集数据的初步分析后提供反馈。报告的结果为现有建筑中用于能源和室内环境质量监测的传感器网络的有效和优化设计和部署指明了道路。
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引用次数: 4
期刊
... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks
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