Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827590
S. K. Jha, K. Hayashi
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.
{"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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827651
Ebubekir Buber, M. A. Güvensan
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.
{"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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827640
Xiuming Zhang, Yunye Jin, H. Tan, Wee-Seng Soh
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.
{"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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827606
Lida Rashidi, S. Rajasegarar, C. Leckie, M. Nati, A. Gluhak, M. Imran, M. Palaniswami
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.
{"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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827662
Vana Micie, D. Tolic, V. Bilas
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).
{"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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827588
N. Ito
In this paper, we investigate a new design technique that adopts a modern optimization scheme called the second-order-cone-programming (SOCP) for designing an all-pass (AP) phase-correction-network (PCN). The PCN is required in the digital communications through non-linear phase channel such that the non-linear phase characteristic can be corrected to nearly linear phase. As a consequence, applying such a PCN can avoid the waveform distortion after transmitting a signal through the non-linear phase channel. This paper formulates the PCN design as an iterative SOCP (iSOCP) problem and solves the iSOCP problem iteratively. Consequently, we can yield the optimal PCN design for approximating a given phase design specification in the minimax error sense. We will utilize an example to validate the iSOCP design scheme.
{"title":"Phase-correction-network design using the SOCP optimization scheme","authors":"N. Ito","doi":"10.1109/ISSNIP.2014.6827588","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827588","url":null,"abstract":"In this paper, we investigate a new design technique that adopts a modern optimization scheme called the second-order-cone-programming (SOCP) for designing an all-pass (AP) phase-correction-network (PCN). The PCN is required in the digital communications through non-linear phase channel such that the non-linear phase characteristic can be corrected to nearly linear phase. As a consequence, applying such a PCN can avoid the waveform distortion after transmitting a signal through the non-linear phase channel. This paper formulates the PCN design as an iterative SOCP (iSOCP) problem and solves the iSOCP problem iteratively. Consequently, we can yield the optimal PCN design for approximating a given phase design specification in the minimax error sense. We will utilize an example to validate the iSOCP design scheme.","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":"129412918","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.2014.6827648
G. Novak, D. Carlson, S. Jarzabek
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.
{"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}
Pub Date : 2014-04-21DOI: 10.1109/ISSNIP.2014.6827589
Pei H. Leong, S. Arulampalam, T. Lamahewa, T. Abhayapala
In this paper, a fixed-lag and a fixed-interval Gaussian-sum cubature Kalman smoother are proposed for the bearings-only tracking problem. The smoothers are of the forward-backward type and they utilise the Gaussian-sum cubature Kalman filter with improved robustness presented by the authors in [1]. Simulation results show that both the fixed-lag and fixed-interval smoothers exhibit improved accuracy over their filtering counterpart and outperform other existing smoothers of the same type for this problem, with the root-mean-square error overlapping the Cramér-Rao lower bound.
{"title":"Gaussian-sum cubature Kalman smoothers for bearings-only tracking","authors":"Pei H. Leong, S. Arulampalam, T. Lamahewa, T. Abhayapala","doi":"10.1109/ISSNIP.2014.6827589","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827589","url":null,"abstract":"In this paper, a fixed-lag and a fixed-interval Gaussian-sum cubature Kalman smoother are proposed for the bearings-only tracking problem. The smoothers are of the forward-backward type and they utilise the Gaussian-sum cubature Kalman filter with improved robustness presented by the authors in [1]. Simulation results show that both the fixed-lag and fixed-interval smoothers exhibit improved accuracy over their filtering counterpart and outperform other existing smoothers of the same type for this problem, with the root-mean-square error overlapping the Cramér-Rao lower bound.","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":"129997245","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.2014.6827641
V. Lystianingrum, B. Hredzak, V. Agelidis, Vivien S. Djanali
Temperature measurement in battery strings is most critical not just for safety reasons but also to restrain operating conditions that would reduce the battery lifetime. However, placing a thermal sensor in each individual battery cell within a battery string implies cost and space. In this paper, the optimal number and location of thermal sensors in a forced-cooled battery string is discussed. Different observability Gramian-based observability criteria are used to evaluate and compare observability degree of placement of different number and different combinations of sensors locations in the battery string. The observability degree is further verified by evaluating the observer performance for the different sensor locations. The most suitable observability criteria to ascertain the optimal location of such thermal sensors are recommended.
{"title":"Observability degree criteria evaluation for temperature observability in a battery string towards optimal thermal sensors placement","authors":"V. Lystianingrum, B. Hredzak, V. Agelidis, Vivien S. Djanali","doi":"10.1109/ISSNIP.2014.6827641","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827641","url":null,"abstract":"Temperature measurement in battery strings is most critical not just for safety reasons but also to restrain operating conditions that would reduce the battery lifetime. However, placing a thermal sensor in each individual battery cell within a battery string implies cost and space. In this paper, the optimal number and location of thermal sensors in a forced-cooled battery string is discussed. Different observability Gramian-based observability criteria are used to evaluate and compare observability degree of placement of different number and different combinations of sensors locations in the battery string. The observability degree is further verified by evaluating the observer performance for the different sensor locations. The most suitable observability criteria to ascertain the optimal location of such thermal sensors are recommended.","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":"132582214","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.2014.6827626
Jonas Ljungblad, B. Hök, M. Ekström
In screening applications there is a need for improved breath alcohol analyzers. Accuracy, specificity, usability, and through-put are critical to the device performance. Objective: To characterize the critical performance of a new contactless breath alcohol analyzer. Methods: The device is characterized by measurements using artificial breath gas and human subjects. Breath sampling is performed in ambient air using carbon dioxide as a biomarker. Results: Resolution and inter-individual variation, response time, and specificity were shown to meet the requirements of industrial standards. The feasibility of contactless measurement was demonstrated. Conclusions: The new device exhibits sufficient performance in moderately diluted breath samples. Further work is underway to reach the objective of unobtrusive breath alcohol analysis.
{"title":"Critical performance of a new breath alcohol analyzer for screening applications","authors":"Jonas Ljungblad, B. Hök, M. Ekström","doi":"10.1109/ISSNIP.2014.6827626","DOIUrl":"https://doi.org/10.1109/ISSNIP.2014.6827626","url":null,"abstract":"In screening applications there is a need for improved breath alcohol analyzers. Accuracy, specificity, usability, and through-put are critical to the device performance. Objective: To characterize the critical performance of a new contactless breath alcohol analyzer. Methods: The device is characterized by measurements using artificial breath gas and human subjects. Breath sampling is performed in ambient air using carbon dioxide as a biomarker. Results: Resolution and inter-individual variation, response time, and specificity were shown to meet the requirements of industrial standards. The feasibility of contactless measurement was demonstrated. Conclusions: The new device exhibits sufficient performance in moderately diluted breath samples. Further work is underway to reach the objective of unobtrusive breath alcohol analysis.","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":"123292309","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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