2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)最新文献_第8页

Optimized KPCA method for chemical vapor class recognition by SAW sensor array response analysis 利用声呐传感器阵列响应分析优化KPCA方法识别化学蒸汽类别

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827590

S. K. Jha, K. Hayashi

{"title":"Optimized KPCA method for chemical vapor class recognition by SAW sensor array response analysis","authors":"S. K. Jha, K. Hayashi","doi":"10.1109/ISSNIP.2014.6827590","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827590","url":null,"abstract":"This paper confirms the suitability of kernel principal component analysis (KPCA) as a robust feature extraction and denoising method in sensor array based vapor detection system (E-nose). Particularly the study focuses on response analysis of surface acoustic wave (SAW) sensor array in chemical class recognition of volatile organic compounds (VOCs). Usually KPCA results deprived performance compare to linear feature extraction methods. However its performance is affected by the proper selection of kernel function and optimization of allied parameters. We have presented the comparative performance analysis of feature vectors extracted by KPCA method using five types of kernel functions in combination with support vector machine (SVM) classifier. Study outcomes are based on analysis of 12 data sets (enclosing different intensity of additive noise and outliers) generated with SAW sensor model simulator. We find that in research of kernel function selection; polynomial kernel achieves persistently maximum class recognition rate of VOCs (average 82 %) even in presence of high level of additive Gaussian noise and outlier and anova kernel results minimum class recognition rate (average 70 %). The class recognition efficiency of feature vectors extracted by rest of the three kernel functions lies in between these two.","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":"115556698","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: 4

Discriminative time-domain features for activity recognition on a mobile phone 判别时域特征在移动电话上的活动识别

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827651

Ebubekir Buber, M. A. Güvensan

{"title":"Discriminative time-domain features for activity recognition on a mobile phone","authors":"Ebubekir Buber, M. A. Güvensan","doi":"10.1109/ISSNIP.2014.6827651","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827651","url":null,"abstract":"People perform several activities during the daily life. It is important to reveal and analyze the daily life characteristic of a person, since it might help to cure several health problems. Especially to overcome obesity, heart attacks etc., people frequently do exercise. However, it is not easy to calculate the consumed energy during these exercises. Extra devices were/are required accomplishing this task. On the other hand, the powerful mobile phones encourage researchers to implement activity recognition task on these smartphones. Thus, activity recognition via mobile phone applications became so popular that several publications are made within the last five years. In this study, we elaborate on the discriminative time-domain features in order to recognize the daily activities with reduced number of features. 70 features, combined from existing studies have been analyzed and 15 of them are selected for the implementation of activity recognition on mobile phone. 6 different classification algorithms and 2 feature selection algorithms have been tested comparatively. The test results show that 8 daily activities including walking, sitting, standing, ascending/descending stairs, jogging, cycling and jumping could be classified with 94% ratio of success rate. Since k-NN is one of the most successful classifier, we have implemented it on our mobile application.","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":"116502372","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: 18

CIMLoc: A crowdsourcing indoor digital map construction system for localization CIMLoc:面向本地化的众包室内数字地图构建系统

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827640

Xiuming Zhang, Yunye Jin, H. Tan, Wee-Seng Soh

{"title":"CIMLoc: A crowdsourcing indoor digital map construction system for localization","authors":"Xiuming Zhang, Yunye Jin, H. Tan, Wee-Seng Soh","doi":"10.1109/ISSNIP.2014.6827640","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827640","url":null,"abstract":"Indoor maps, as crucial prerequisites for many indoor localization and navigation systems, are sometimes inaccessible. The absence of an indoor map database and the high cost of manually constructing an indoor map produce a need for an inexpensive and efficient way to dynamically construct indoor maps. The ubiquity of sensor-equipped mobile devices enables us to crowdsource user trajectories, out of which indoor digital maps can be automatically constructed at low costs. Similar to other crowdsourced data, the collected user trajectories are often noisy and of low fidelity, which poses a challenge to the accurate map construction. To alleviate this problem, we propose CIMLoc - a crowdsourcing indoor map construction system for localization. The system is evaluated with real-world trajectories collected from different mobile devices. We quantify the construction errors by computing the localization errors achieved with the constructed map and the real map. Experimental results reveal that CIMLoc is able to construct accurate maps that significantly improve localization results. We believe that CIMLoc provides an effective solution to the indoor localization problems where the indoor maps are unavailable.","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":"126099356","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: 39

Profiling spatial and temporal behaviour in sensor networks: A case study in energy monitoring 剖析传感器网络的空间和时间行为:能源监测的案例研究

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827606

Lida Rashidi, S. Rajasegarar, C. Leckie, M. Nati, A. Gluhak, M. Imran, M. Palaniswami

{"title":"Profiling spatial and temporal behaviour in sensor networks: A case study in energy monitoring","authors":"Lida Rashidi, S. Rajasegarar, C. Leckie, M. Nati, A. Gluhak, M. Imran, M. Palaniswami","doi":"10.1109/ISSNIP.2014.6827606","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827606","url":null,"abstract":"Wireless sensor networks (WSNs) provide a cost-effective platform for monitoring phenomena of interest at fine spatial and temporal resolutions. In this paper, we consider the application of monitoring power usage in an office environment at the resolution of individual users. A key challenge in this context is how to extract meaningful profiles of user behaviour in the large volume of monitoring data collected by the WSN. To manage the complexity of learning such profiles in this context, we propose a query based model for profiling. This query based model provides the ability to characterize the spatial and temporal occurrences of the power usage patterns of interest. We demonstrate the effectiveness of our query-based profiling model for finding relevant electricity usage patterns in a real life data set of power measurements collected by a WSN deployment in an office environment. To the best of our knowledge, this is the first time such a case study has been made on analysing the power usage of users at such a fine scale in an office environment.","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":"126281714","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: 9

Consensus-based decentralized resource sharing between co-located Wireless Sensor Networks 无线传感器网络间基于共识的分散资源共享

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827662

Vana Micie, D. Tolic, V. Bilas

{"title":"Consensus-based decentralized resource sharing between co-located Wireless Sensor Networks","authors":"Vana Micie, D. Tolic, V. Bilas","doi":"10.1109/ISSNIP.2014.6827662","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827662","url":null,"abstract":"With the emergence of various co-located Wireless Sensor Networks (WSNs) in applications such as smart buildings and smart cities, it becomes increasingly important to facilitate their interaction. The aim of inter-network collaboration is to leverage the performance of each WSN, as well as the quality of service of the overall system. In this paper, we propose a decentralized method for inter-network collaboration, where each node is able to initiate a consensus-reaching procedure among the nodes from its network and terminate it after the consensus is reached. After that, it exchanges the information with a node from a neighboring network. In order not to interfere with the main task of the WSNs (detecting and reporting interesting events), our consensus algorithm needs to be energy-efficient and fast. We emphasize the importance of our approach on a case study of a smart surveillance application, where a gas WSN and video WSN share the same physical environment. The performance of the consensus algorithm during intranetwork communication (prior to inter-network communication) is experimentally investigated, using off-the-shelf wireless sensor platforms. We introduce an energy-time factor that indicates the optimal communication rate in terms of energy- and time-efficiency of the consensus algorithm. In our experiments, the best performance is achieved for period of communication 0.1 s (i.e., 2% duty cycle).","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":"127977163","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: 5

Phase-correction-network design using the SOCP optimization scheme 采用SOCP优化方案的相位校正网络设计

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827588

N. Ito

引用次数: 1

An adaptable and extensible mobile sensing framework for patient monitoring 用于患者监测的适应性和可扩展的移动传感框架

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827648

G. Novak, D. Carlson, S. Jarzabek

{"title":"An adaptable and extensible mobile sensing framework for patient monitoring","authors":"G. Novak, D. Carlson, S. Jarzabek","doi":"10.1109/ISSNIP.2014.6827648","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827648","url":null,"abstract":"Smartphone apps with self-monitoring and sensing capabilities can help in disease prevention; however, such context-aware applications are difficult to develop, due to the complexities of sensor data acquisition, context modeling, and data management. To ease the development of mHealth and Telemedicine apps, we developed the Mobile Sensing Framework (MSF), which dynamically installs device appropriate context sensing plug-ins that provide a wealth of information about users' mental and physical states. The MSF automatically collects information about incoming/outgoing/missed calls; apps usage; sound pressure levels; light sensor values; movement data (e.g., step count); location; heart rate; etc. The MSF also includes a searchable object-based persistence layer, which is capable of rapidly serializing and de-serializing detected context data. Collected data are stored securely in the phone's database, where they can be retrieved by applications for local analysis, remote monitoring, and alert generation. We developed a fully operational prototype of the MSF platform that was validated using several Android-based devices. This paper presents an overview of our approach along with a description of the experiments conducted using the MSF prototype.","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":"130904140","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: 2

Gaussian-sum cubature Kalman smoothers for bearings-only tracking 高斯和培养卡尔曼平滑器用于方位跟踪

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827589

Pei H. Leong, S. Arulampalam, T. Lamahewa, T. Abhayapala

引用次数: 1

Observability degree criteria evaluation for temperature observability in a battery string towards optimal thermal sensors placement 基于最佳热传感器位置的电池组温度可观测性评价准则

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827641

V. Lystianingrum, B. Hredzak, V. Agelidis, Vivien S. Djanali

引用次数: 8

Critical performance of a new breath alcohol analyzer for screening applications 一种新的呼气酒精分析仪的关键性能筛选应用

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI: 10.1109/ISSNIP.2014.6827626

Jonas Ljungblad, B. Hök, M. Ekström

引用次数: 11