Pub Date : 2016-06-27DOI: 10.1109/ISSNIP.2014.6827681
N. Khalil, M. Abid, D. Benhaddou, M. Gerndt
The Internet is smoothly migrating from an Internet of people towards an Internet of Things (IoT). By 2020, it is expected to have 50 billion things connected to the Internet. However, such a migration induces a strong level of complexity when handling interoperability between the heterogeneous Internet things, e.g., RFIDs (Radio Frequency Identification), mobile handheld devices, and wireless sensors. In this context, a couple of standards have been already set, e.g., IPv6, 6LoWPAN (IPv6 over Low power Wireless Personal Area Networks), and M2M (Machine to Machine communications). In this paper, we focus on the integration of wireless sensor networks into IoT, and shed further light on the subtleties of such integration. We present a real-world test bed deployment where wireless sensors are used to control electrical appliances in a smart building. Encountered problems are highlighted and suitable solutions are presented.
{"title":"Wireless sensors networks for Internet of Things","authors":"N. Khalil, M. Abid, D. Benhaddou, M. Gerndt","doi":"10.1109/ISSNIP.2014.6827681","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827681","url":null,"abstract":"The Internet is smoothly migrating from an Internet of people towards an Internet of Things (IoT). By 2020, it is expected to have 50 billion things connected to the Internet. However, such a migration induces a strong level of complexity when handling interoperability between the heterogeneous Internet things, e.g., RFIDs (Radio Frequency Identification), mobile handheld devices, and wireless sensors. In this context, a couple of standards have been already set, e.g., IPv6, 6LoWPAN (IPv6 over Low power Wireless Personal Area Networks), and M2M (Machine to Machine communications). In this paper, we focus on the integration of wireless sensor networks into IoT, and shed further light on the subtleties of such integration. We present a real-world test bed deployment where wireless sensors are used to control electrical appliances in a smart building. Encountered problems are highlighted and suitable solutions are presented.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129720747","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}
Pub Date : 2014-06-09DOI: 10.1109/ISSNIP.2014.6827612
T. D. Groot, O. Krasnov, A. Yarovoy
An efficient strategy solution is developed for a specific deployment problem in which different types of sensors are required to simultaneously cover the same area of interest. The deployment goal is to select the sensor positions and orientations in such a way that the sensor network coverage is optimized. A general challenge within resource allocation problems is that, even with small-scale sensor networks, the number of possible final deployment solutions expands very fast and the problem becomes intractable. We assume that it is acceptable to trade solution optimality against algorithm speed. In this case, algorithms can be based on greedy and/or divide-and-conquer principles, which both results in good computational efficiency. We developed an efficient algorithm in three steps. Firstly, we developed a global search algorithm, but with improvements that reduce the search space significantly without losing optimality. Secondly, we transformed the global algorithm into a sequential and a hierarchical algorithm for more efficiency at the cost of optimality. Thirdly, we combine the sequential and hierarchical principles into one algorithm which results in even higher efficiency. In the end, the algorithms are evaluated with the use of an extensive testing scheme which generates many random cases for solving.
{"title":"Efficient sequential-hierarchical deployment strategy for heterogeneous sensor networks","authors":"T. D. Groot, O. Krasnov, A. Yarovoy","doi":"10.1109/ISSNIP.2014.6827612","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827612","url":null,"abstract":"An efficient strategy solution is developed for a specific deployment problem in which different types of sensors are required to simultaneously cover the same area of interest. The deployment goal is to select the sensor positions and orientations in such a way that the sensor network coverage is optimized. A general challenge within resource allocation problems is that, even with small-scale sensor networks, the number of possible final deployment solutions expands very fast and the problem becomes intractable. We assume that it is acceptable to trade solution optimality against algorithm speed. In this case, algorithms can be based on greedy and/or divide-and-conquer principles, which both results in good computational efficiency. We developed an efficient algorithm in three steps. Firstly, we developed a global search algorithm, but with improvements that reduce the search space significantly without losing optimality. Secondly, we transformed the global algorithm into a sequential and a hierarchical algorithm for more efficiency at the cost of optimality. Thirdly, we combine the sequential and hierarchical principles into one algorithm which results in even higher efficiency. In the end, the algorithms are evaluated with the use of an extensive testing scheme which generates many random cases for solving.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115660692","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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827665
Timo Hongell, I. Kivelä, I. Hakala
Wireless sensor networks can be used to perform structural monitoring. Strain gauges, which can be glued on or integrated to the observed material, are the most common nondestructive sensing elements for measuring surface strain. Wireless strain gauge measurement system makes strain measurements more flexible while opening new targets of application in addition to those that traditional wired strain measuring systems can offer. We have implemented a long term strain measurement in a PVC-covered hall using wireless sensor network. In this paper we evaluate the functionality and suitability of the developed wireless system for this kind of monitoring. The paper discusses the experiences gained in the development and utilization of a wireless strain gauge measurement system. The calibration of measurement system as well as energy consumption issues are also brought under observation along with the reliability of communication aspects in the described measurement case.
{"title":"Wireless strain gauge network — Best-hall measurement case","authors":"Timo Hongell, I. Kivelä, I. Hakala","doi":"10.1109/ISSNIP.2014.6827665","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827665","url":null,"abstract":"Wireless sensor networks can be used to perform structural monitoring. Strain gauges, which can be glued on or integrated to the observed material, are the most common nondestructive sensing elements for measuring surface strain. Wireless strain gauge measurement system makes strain measurements more flexible while opening new targets of application in addition to those that traditional wired strain measuring systems can offer. We have implemented a long term strain measurement in a PVC-covered hall using wireless sensor network. In this paper we evaluate the functionality and suitability of the developed wireless system for this kind of monitoring. The paper discusses the experiences gained in the development and utilization of a wireless strain gauge measurement system. The calibration of measurement system as well as energy consumption issues are also brought under observation along with the reliability of communication aspects in the described measurement case.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116898003","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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827593
U. Ghoshdastider, R. Viga, Michael Kraft
Wireless body sensor networks consisting of EEG, ECG, EMG and acceleration sensors provide assistance to the researchers in cognitive physiology and clinical research as well as in neurophysiology. The data fusion of the electrical activities of muscle structures, e.g. facial muscles, heart and brain combined with the movement data of patients helps to detect nocturnal epileptic seizure in home care application. A mobile, flexible, densely configurable distributed body area network featuring wireless data transmission and a wired time synchronization technique was designed and realized in this work Signal conditioning of each of sensor systems was realized depending on their signal strength and frequency bandwidth. Moreover, synchronization between each of the nodes was achieved with the help of wired USART (universal synchronous/asynchronous receiver/transmitter). All measurement units follow the same synchronization protocol, which is controlled by a master unit. The ExG-system can sample bio-potentials from 125 Hz up to 1000 Hz and it exhibits 1.445 μν peak-to-peak system noise between 0.1 Hz and 500 Hz and can send data with incorporated Wi-Fi module in it to a basis station at a maximum data speed of 1.45 Mbps. A 3-4 cm spatial resolution can be achieved for high-dense EEG during a complete 256 channel deployment.
{"title":"Non-invasive synchronized spatially high-resolution wireless body area network","authors":"U. Ghoshdastider, R. Viga, Michael Kraft","doi":"10.1109/ISSNIP.2014.6827593","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827593","url":null,"abstract":"Wireless body sensor networks consisting of EEG, ECG, EMG and acceleration sensors provide assistance to the researchers in cognitive physiology and clinical research as well as in neurophysiology. The data fusion of the electrical activities of muscle structures, e.g. facial muscles, heart and brain combined with the movement data of patients helps to detect nocturnal epileptic seizure in home care application. A mobile, flexible, densely configurable distributed body area network featuring wireless data transmission and a wired time synchronization technique was designed and realized in this work Signal conditioning of each of sensor systems was realized depending on their signal strength and frequency bandwidth. Moreover, synchronization between each of the nodes was achieved with the help of wired USART (universal synchronous/asynchronous receiver/transmitter). All measurement units follow the same synchronization protocol, which is controlled by a master unit. The ExG-system can sample bio-potentials from 125 Hz up to 1000 Hz and it exhibits 1.445 μν peak-to-peak system noise between 0.1 Hz and 500 Hz and can send data with incorporated Wi-Fi module in it to a basis station at a maximum data speed of 1.45 Mbps. A 3-4 cm spatial resolution can be achieved for high-dense EEG during a complete 256 channel deployment.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126060723","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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827669
Daesung Hwang, Hyoungsuk Jeon, J. Ha, Jinho Choi
In this paper, we propose two energy efficient ordered transmission schemes with fusion rules for distributed detection in wireless sensor networks (WSNs). The fusion rule at the fusion center (FC) has been derived to take into account not only the reliability of local decision at sensors, but also channel gains from sensors to the FC. In the first scheme, the sensors' transmission order is based on only local log-likelihood ratio (LLR), while it is based on both the reliability of local decision and quality of transmission channels in the second scheme. Due to the ordered transmission, the target detection performance can be achieved with a small number of sensors, which leads to energy efficient distributed detection in WSNs. At the high signal-to-noise ratio (SNR) regime, the performances of both strategies converge to the best achievable one in the case that the sensors perfectly know the received signals at the FC.
{"title":"Energy efficient transmission strategies for distributed detection in wireless sensor networks","authors":"Daesung Hwang, Hyoungsuk Jeon, J. Ha, Jinho Choi","doi":"10.1109/ISSNIP.2014.6827669","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827669","url":null,"abstract":"In this paper, we propose two energy efficient ordered transmission schemes with fusion rules for distributed detection in wireless sensor networks (WSNs). The fusion rule at the fusion center (FC) has been derived to take into account not only the reliability of local decision at sensors, but also channel gains from sensors to the FC. In the first scheme, the sensors' transmission order is based on only local log-likelihood ratio (LLR), while it is based on both the reliability of local decision and quality of transmission channels in the second scheme. Due to the ordered transmission, the target detection performance can be achieved with a small number of sensors, which leads to energy efficient distributed detection in WSNs. At the high signal-to-noise ratio (SNR) regime, the performances of both strategies converge to the best achievable one in the case that the sensors perfectly know the received signals at the FC.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115182866","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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827682
P. Urien
This paper presents a new secure model for NFC (Near Field Communication) services based on the P2P (Peer to Peer) mode. NFC is a proximity communication technology more and more supported by smartphones or consumer devices that seems a promising technology for the Internet of Things (IoT). It is used in applications such as payment, access control, transport and more generally for the exchange of small pieces of information. NFC P2P sessions are managed by the Logical Link Control Protocol (LLCP). We introduce LLCPS, a TLS security layer working over LLCP. This framework enforces data privacy and integrity; it also provides identity to smart objects, bound to certificates providing strong mutual authentications. Two experimental platforms are described built with NFC devices and smartphones.
本文提出了一种基于P2P (Peer to Peer)模式的NFC (Near Field Communication)服务安全模型。NFC是一种近距离通信技术，越来越受到智能手机或消费设备的支持，似乎是物联网(IoT)的一项有前途的技术。它用于支付、访问控制、运输等应用，更普遍的是用于小块信息的交换。NFC P2P会话由逻辑链路控制协议LLCP (Logical Link Control Protocol)管理。我们介绍了LLCPS，一个工作在LLCP之上的TLS安全层。该框架加强了数据隐私和完整性;它还为智能对象提供身份，绑定到提供强相互身份验证的证书。本文描述了用NFC设备和智能手机构建的两个实验平台。
{"title":"LLCPS: A new secure model for Internet of Things services based on the NFC P2P model","authors":"P. Urien","doi":"10.1109/ISSNIP.2014.6827682","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827682","url":null,"abstract":"This paper presents a new secure model for NFC (Near Field Communication) services based on the P2P (Peer to Peer) mode. NFC is a proximity communication technology more and more supported by smartphones or consumer devices that seems a promising technology for the Internet of Things (IoT). It is used in applications such as payment, access control, transport and more generally for the exchange of small pieces of information. NFC P2P sessions are managed by the Logical Link Control Protocol (LLCP). We introduce LLCPS, a TLS security layer working over LLCP. This framework enforces data privacy and integrity; it also provides identity to smart objects, bound to certificates providing strong mutual authentications. Two experimental platforms are described built with NFC devices and smartphones.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122354537","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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827622
B. Rangarajan, Venkatesh Babu Radhakrishnan
Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBFN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PBL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.
人类行为的巨大变化给计算机视觉研究带来了重大挑战。设计了几种算法来解决这些挑战。独立的算法，有助于解决挑战，除了执行更快，更有效的方式。在本文中，我们提出了一种基于人类认知启发的基于投影的学习方法，用于H.264/AVC压缩域中的独立于人的人类动作识别，并演示了一种基于PBL-McRBFN的方法，以帮助将机器学习算法提升到一个新的水平。在此，我们采用基于梯度图像的特征提取过程，提取运动矢量和量化参数，并对其进行临时研究，形成若干组图像(Group of Pictures, GoP)。然后分别考虑两个不同基准数据集的GoP，并使用独立于人的人类行为识别对结果进行分类。采用基于投影的元认知径向基函数网络(PBL-McRBFN)学习算法研究了函数关系，该算法具有认知和元认知两部分。认知成分是径向基函数网络，而元认知成分是自我调节的。McC模仿人类的认知，比如学习，以达到更好的表现。该方法可以处理压缩视频域的稀疏信息，并提供比其他像素域更高的精度。使用PBL-McRBFN的特征提取过程的性能达到了90%以上的准确率，这促进了所提出的高速动作识别算法的速度。我们进行了20次随机试验，以了解GoP的性能。结果还与机器学习文献中其他知名分类器进行了比较。
{"title":"Human action recognition in compressed domain using PBL-McRBFN approach","authors":"B. Rangarajan, Venkatesh Babu Radhakrishnan","doi":"10.1109/ISSNIP.2014.6827622","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827622","url":null,"abstract":"Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBFN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PBL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124671800","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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827607
S. Rajasegarar, P. Zhang, Yang Zhou, S. Karunasekera, C. Leckie, M. Palaniswami
Atmospheric pollutants, such as gases and particulate matters (PM) pose a threat to human health. In particular, there has been a strong focus on particulate matter as it is a common pollutant to cause population health hazards, especially respiratory illness. Monitoring of this pollutant is currently attained at low spatial resolutions due to the cost of accurate sensing devices. Even though these devices are highly accurate, given the distance they are placed apart from each other, the relevance of their measurements to an unmeasured spatial location in between sensors will be very low, which causes large estimation errors. In this paper, we present a solution by creating easy-to-implement wireless sensor network hardware equipped with inexpensive PM sensors to supplement the existing high accurate PM devices to improve estimation accuracy at higher spatial and temporal resolutions. The measurements collected from the real deployments of these sensors are analyzed using spatio-temporal estimation technique to demonstrate the ability to provide accurate estimation at unmeasured locations.
{"title":"High resolution spatio-temporal monitoring of air pollutants using wireless sensor networks","authors":"S. Rajasegarar, P. Zhang, Yang Zhou, S. Karunasekera, C. Leckie, M. Palaniswami","doi":"10.1109/ISSNIP.2014.6827607","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827607","url":null,"abstract":"Atmospheric pollutants, such as gases and particulate matters (PM) pose a threat to human health. In particular, there has been a strong focus on particulate matter as it is a common pollutant to cause population health hazards, especially respiratory illness. Monitoring of this pollutant is currently attained at low spatial resolutions due to the cost of accurate sensing devices. Even though these devices are highly accurate, given the distance they are placed apart from each other, the relevance of their measurements to an unmeasured spatial location in between sensors will be very low, which causes large estimation errors. In this paper, we present a solution by creating easy-to-implement wireless sensor network hardware equipped with inexpensive PM sensors to supplement the existing high accurate PM devices to improve estimation accuracy at higher spatial and temporal resolutions. The measurements collected from the real deployments of these sensors are analyzed using spatio-temporal estimation technique to demonstrate the ability to provide accurate estimation at unmeasured locations.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129476360","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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827676
D. Carlson, Lukas Ruge
Emerging context frameworks enable Websites to interact with the Internet of Things directly from the browser; however, Websites must be specifically designed to utilize such context framework support. As such, the majority of “legacy” Websites remains context-unaware. This paper presents Ambient Amp, an open framework for dynamically augmenting legacy Websites with context-awareness, without requiring browser extensions, proxies or Website reengineering. Amp provides an extensible Bookmarklet framework that serves as a conduit between the user's browser and a server-side repository of Amp plug-ins, which can be used to dynamically augment any 3rd party Website with new content, adapted behavior and context framework support - enabling augmented Websites to sense the user's physical environment and interact with discovered smart devices. This paper introduces the Amp architecture, its fully operational prototype and an example Amp plug-in that augments a well-known photo sharing Website with the ability to stream selected images to networked media devices discovered in the user's physical environment. We also present a preliminary performance evaluation, which indicates that Amp is suitable for deployment on many commodity mobile devices.
{"title":"Ambient Amp: An open framework for dynamically augmenting legacy Websites with context-awareness","authors":"D. Carlson, Lukas Ruge","doi":"10.1109/ISSNIP.2014.6827676","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827676","url":null,"abstract":"Emerging context frameworks enable Websites to interact with the Internet of Things directly from the browser; however, Websites must be specifically designed to utilize such context framework support. As such, the majority of “legacy” Websites remains context-unaware. This paper presents Ambient Amp, an open framework for dynamically augmenting legacy Websites with context-awareness, without requiring browser extensions, proxies or Website reengineering. Amp provides an extensible Bookmarklet framework that serves as a conduit between the user's browser and a server-side repository of Amp plug-ins, which can be used to dynamically augment any 3rd party Website with new content, adapted behavior and context framework support - enabling augmented Websites to sense the user's physical environment and interact with discovered smart devices. This paper introduces the Amp architecture, its fully operational prototype and an example Amp plug-in that augments a well-known photo sharing Website with the ability to stream selected images to networked media devices discovered in the user's physical environment. We also present a preliminary performance evaluation, which indicates that Amp is suitable for deployment on many commodity mobile devices.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129885083","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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827603
Wenzheng Hu, E. Charry, M. Umer, A. Ronchi, Simon Taylor
Accurate measurement of knee motion during dynamic movements is the key to detect and highlight deficiencies in peripheral muscles and ligaments of the knee and hence to predict the risk of injury. Miniature inertial sensors are increasingly becoming a viable option for human movement measurement, given their small size, low cost and relatively good accuracy compared with traditional optical measurements. A system capable of measuring tibia angle using a shank mounted wireless inertial sensor is proposed. The system employs a simple setup with only one skin-mounted triaxial accelerometer and gyroscope module attached to the tibia segment, and an algorithm to estimate the tibia angle. The accuracy of the system was assessed by an optical tracking system (Optotrak Certus) during dynamic movements performed by three subjects by evaluating Root-Mean-Square Error (RMSE) of tibia-flexion and tibia-adduction angles over the period of motion. We achieve an RMSE of 1.6±1.1 and2.5±1.6 degrees in tibia-flexion and tibia-adduction angles, respectively. It is argued that tibia angle can be reliably used to detect valgus or varus movement of the knee and hence the proposed system provides a simple and useful assessment tool for performance enhancement and rehabilitation.
{"title":"An inertial sensor system for measurements of tibia angle with applications to knee valgus/varus detection","authors":"Wenzheng Hu, E. Charry, M. Umer, A. Ronchi, Simon Taylor","doi":"10.1109/ISSNIP.2014.6827603","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827603","url":null,"abstract":"Accurate measurement of knee motion during dynamic movements is the key to detect and highlight deficiencies in peripheral muscles and ligaments of the knee and hence to predict the risk of injury. Miniature inertial sensors are increasingly becoming a viable option for human movement measurement, given their small size, low cost and relatively good accuracy compared with traditional optical measurements. A system capable of measuring tibia angle using a shank mounted wireless inertial sensor is proposed. The system employs a simple setup with only one skin-mounted triaxial accelerometer and gyroscope module attached to the tibia segment, and an algorithm to estimate the tibia angle. The accuracy of the system was assessed by an optical tracking system (Optotrak Certus) during dynamic movements performed by three subjects by evaluating Root-Mean-Square Error (RMSE) of tibia-flexion and tibia-adduction angles over the period of motion. We achieve an RMSE of 1.6±1.1 and2.5±1.6 degrees in tibia-flexion and tibia-adduction angles, respectively. It is argued that tibia angle can be reliably used to detect valgus or varus movement of the knee and hence the proposed system provides a simple and useful assessment tool for performance enhancement and rehabilitation.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124454532","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}
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