Pub Date : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617394
Liviu-Cristian Duţu, G. Mauris, P. Bolon, Stéphanie Dabic, J. Tissot
Nowadays tactile surfaces are slowly replacing the mechanical interfaces of our electronic devices, and the actual trend is toward a quasi-total touch interaction. This transition has however one important side effect, i.e the lack of feedback from the device, which in certain situations can be crucial. In order to overcome this, it has been suggested that feedback has to be delivered to the finger through vibrations that should be both detectable and comfortable. This paper aims to define a perception model for the sensory evaluations of the vibrotactile signals using fuzzy set theory. First of all, the hypothesis that haptic perception is strongly related to physical characteristics of the signals was evaluated and confirmed with a 93% correlation rate, based on psychophysical studies of the tactile sense. Secondly, using the previous analysis as a knowledge base we have implemented a fuzzy inference system which forecasts the preference values for vibrotactile signals. The preliminary results show that for 15 out of 18 signals, the preference is correctly predicted within a reasonable uncertainty interval.
{"title":"A fuzzy model relating vibrotactile signal characteristics to haptic sensory evaluations","authors":"Liviu-Cristian Duţu, G. Mauris, P. Bolon, Stéphanie Dabic, J. Tissot","doi":"10.1109/CIVEMSA.2013.6617394","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617394","url":null,"abstract":"Nowadays tactile surfaces are slowly replacing the mechanical interfaces of our electronic devices, and the actual trend is toward a quasi-total touch interaction. This transition has however one important side effect, i.e the lack of feedback from the device, which in certain situations can be crucial. In order to overcome this, it has been suggested that feedback has to be delivered to the finger through vibrations that should be both detectable and comfortable. This paper aims to define a perception model for the sensory evaluations of the vibrotactile signals using fuzzy set theory. First of all, the hypothesis that haptic perception is strongly related to physical characteristics of the signals was evaluated and confirmed with a 93% correlation rate, based on psychophysical studies of the tactile sense. Secondly, using the previous analysis as a knowledge base we have implemented a fuzzy inference system which forecasts the preference values for vibrotactile signals. The preliminary results show that for 15 out of 18 signals, the preference is correctly predicted within a reasonable uncertainty interval.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125740729","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 : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617398
Yong Hu, Jerry Kwok, J. Tse
The contaminated electrocardiography (ECG) is a big problem in the surface electromyography (SEMG) signal detection and analysis. The objective of the current study is to propose and validate an algorithm for the automated feature cognition and identification for eliminating ECG artifact from the raw SEMG signals. The utilization of Independent Component Analysis (ICA) method is to decompose the raw SEMG signals into individual independent source components. After that, some of the independent source components with the characteristics of ECG artifact were detected by the automated identification algorithm and thereafter eliminated. The sensitivity and specificity of the algorithm for distinguishing ECG source components from independent source components are 100% and 99% respectively. The automated identification algorithm exhibits the prominent performance of recognition for ECG artifact and can be considered reliable and effective.
{"title":"Automatic ECG artifact removal in the real-time SEMG recording system","authors":"Yong Hu, Jerry Kwok, J. Tse","doi":"10.1109/CIVEMSA.2013.6617398","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617398","url":null,"abstract":"The contaminated electrocardiography (ECG) is a big problem in the surface electromyography (SEMG) signal detection and analysis. The objective of the current study is to propose and validate an algorithm for the automated feature cognition and identification for eliminating ECG artifact from the raw SEMG signals. The utilization of Independent Component Analysis (ICA) method is to decompose the raw SEMG signals into individual independent source components. After that, some of the independent source components with the characteristics of ECG artifact were detected by the automated identification algorithm and thereafter eliminated. The sensitivity and specificity of the algorithm for distinguishing ECG source components from independent source components are 100% and 99% respectively. The automated identification algorithm exhibits the prominent performance of recognition for ECG artifact and can be considered reliable and effective.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117046089","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 : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617388
D. Ionescu, V. Suse, C. Gadea, B. Solomon, B. Ionescu, S. Islam
Gesture Control dominates presently the research on new human computer interfaces. The domain covers both the sensors to capture gestures and also the driver software which interprets the gesture mapping it onto a robust command. More recently, there is a trend to use depth-mapping camera as the 2D cameras fall short in assuring the conditions of real-time robustness of the whole system. As image processing is at the core of the detection, recognition, and tracking the gesture, depth mapping sensors have to provide a depth image insensitive to illumination conditions. Thus depth-mapping cameras work in a certain wavelength of the infrared (IR) spectrum. In this paper, a novel real-time depth-mapping principle for an IR camera is introduced. The new IR camera architecture comprises an illuminator module which is pulse-modulated via a monotonic function using a cycle driven feedback loop for the control of laser intensity, while the reflected infrared light is captured in “slices” of the space in which the object of interest is situated. A reconfigurable hardware architecture unit calculates the depth slices and combines them in a depth-map of the object to be further used in the detection, tracking, and recognition of the gesture made by the user. Images of real objects are reconstructed in 3D based on the data obtained by the space-slicing technique, and a corresponding image processing algorithm builds the 3D map of the object in real-time. As this paper will show through a series of experiments, the camera can be used in a variety of domains, including for gesture control of 3D objects in virtual environments.
{"title":"An infrared-based depth camera for gesture-based control of virtual environments","authors":"D. Ionescu, V. Suse, C. Gadea, B. Solomon, B. Ionescu, S. Islam","doi":"10.1109/CIVEMSA.2013.6617388","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617388","url":null,"abstract":"Gesture Control dominates presently the research on new human computer interfaces. The domain covers both the sensors to capture gestures and also the driver software which interprets the gesture mapping it onto a robust command. More recently, there is a trend to use depth-mapping camera as the 2D cameras fall short in assuring the conditions of real-time robustness of the whole system. As image processing is at the core of the detection, recognition, and tracking the gesture, depth mapping sensors have to provide a depth image insensitive to illumination conditions. Thus depth-mapping cameras work in a certain wavelength of the infrared (IR) spectrum. In this paper, a novel real-time depth-mapping principle for an IR camera is introduced. The new IR camera architecture comprises an illuminator module which is pulse-modulated via a monotonic function using a cycle driven feedback loop for the control of laser intensity, while the reflected infrared light is captured in “slices” of the space in which the object of interest is situated. A reconfigurable hardware architecture unit calculates the depth slices and combines them in a depth-map of the object to be further used in the detection, tracking, and recognition of the gesture made by the user. Images of real objects are reconstructed in 3D based on the data obtained by the space-slicing technique, and a corresponding image processing algorithm builds the 3D map of the object in real-time. As this paper will show through a series of experiments, the camera can be used in a variety of domains, including for gesture control of 3D objects in virtual environments.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194357","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 : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617400
C. Roadknight, U. Aickelin, J. Scholefield, L. Durrant
In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insight into immunological status at the point of tumour removal, tumour classification and post-operative survival. We build on existing research on clustering and machine learning facets of this data to demonstrate a role for an ensemble approach to highlighting patients with clearer prognosis parameters. Results for survival prediction using 3 different approaches are shown for a subset of the data which is most difficult to model. The performance of each model individually is compared with subsets of the data where some agreement is reached for multiple models. Significant improvements in model accuracy on an unseen test set can be achieved for patients where agreement between models is achieved.
{"title":"Ensemble learning of colorectal cancer survival rates","authors":"C. Roadknight, U. Aickelin, J. Scholefield, L. Durrant","doi":"10.1109/CIVEMSA.2013.6617400","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617400","url":null,"abstract":"In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insight into immunological status at the point of tumour removal, tumour classification and post-operative survival. We build on existing research on clustering and machine learning facets of this data to demonstrate a role for an ensemble approach to highlighting patients with clearer prognosis parameters. Results for survival prediction using 3 different approaches are shown for a subset of the data which is most difficult to model. The performance of each model individually is compared with subsets of the data where some agreement is reached for multiple models. Significant improvements in model accuracy on an unseen test set can be achieved for patients where agreement between models is achieved.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129987940","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 : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617414
R. D. Labati, A. Genovese, V. Piuri, F. Scotti
In this paper, we present a complete virtual environment for the computation of synthetic three-dimensional samples representing free falling wood strands.The proposed method permits to simulate acquisitions performed by real multiple view setups in which the stream of strands falling out of a conveyor belt is analyzed with image processing techniques in order to compute the particle size distribution. Unfortunately, experiments in real time applications are complex and expensive, and the ground true is almost impossible to measure in such conditions. The creation of a metric and fully virtual environment of falling wood strands represent a key feature in order to properly design the illuminotecnic and optical setups, optimize the image processing methods as well as the three- dimensional reconstruction techniques, using controlled and fully repeatable virtual image datasets.
{"title":"A virtual environment for the simulation of 3D wood strands in multiple view systems for the particle size measurements","authors":"R. D. Labati, A. Genovese, V. Piuri, F. Scotti","doi":"10.1109/CIVEMSA.2013.6617414","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617414","url":null,"abstract":"In this paper, we present a complete virtual environment for the computation of synthetic three-dimensional samples representing free falling wood strands.The proposed method permits to simulate acquisitions performed by real multiple view setups in which the stream of strands falling out of a conveyor belt is analyzed with image processing techniques in order to compute the particle size distribution. Unfortunately, experiments in real time applications are complex and expensive, and the ground true is almost impossible to measure in such conditions. The creation of a metric and fully virtual environment of falling wood strands represent a key feature in order to properly design the illuminotecnic and optical setups, optimize the image processing methods as well as the three- dimensional reconstruction techniques, using controlled and fully repeatable virtual image datasets.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123127915","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 : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617417
M. Alreshoodi, J. Woods
A model that can predict an end user satisfaction or QoE (Quality of Experience) directly from the network QoS (Quality of Service) is still illusive in the field of image processing and is completely absent in multi-layered video. This motivates the derivation of a meaningful QoS to QoE mapping function to allow one to be predicted in the absence of the other. This paper presents an affine fuzzy logic based system that can map the QoS to QoE and can be extended to layered video streaming. The proposed methodology employs a learning system which optimizes the coded layered video for best QoE. Four QoS parameters are chosen as the inputs of the designed model, while the output is the Peak Signal-to-Noise Ratio (PSNR). The designed membership functions and the fuzzy rules extracted from the input and the output enable the proposed model to identify and learn the video QoE.
{"title":"An empirical study based on a fuzzy logic system to assess the QoS/QoE correlation for layered video streaming","authors":"M. Alreshoodi, J. Woods","doi":"10.1109/CIVEMSA.2013.6617417","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617417","url":null,"abstract":"A model that can predict an end user satisfaction or QoE (Quality of Experience) directly from the network QoS (Quality of Service) is still illusive in the field of image processing and is completely absent in multi-layered video. This motivates the derivation of a meaningful QoS to QoE mapping function to allow one to be predicted in the absence of the other. This paper presents an affine fuzzy logic based system that can map the QoS to QoE and can be extended to layered video streaming. The proposed methodology employs a learning system which optimizes the coded layered video for best QoE. Four QoS parameters are chosen as the inputs of the designed model, while the output is the Peak Signal-to-Noise Ratio (PSNR). The designed membership functions and the fuzzy rules extracted from the input and the output enable the proposed model to identify and learn the video QoE.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121191821","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 : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617395
Lucas Silva, R. Dantas, Andre L. H. Pantoja, Antonio Pereira
This article describes the first steps on the development of a low cost dataglove based on the Arduino Uno microprocessor. The glove is designed for use in virtual reality systems and is integrated into a suite of applications. This article also presents a set of preliminary results obtained with the glove and discuss about the use of the glove to control a video game application for rehabilitation of stroke patients.
{"title":"Development of a low cost dataglove based on arduino for virtual reality applications","authors":"Lucas Silva, R. Dantas, Andre L. H. Pantoja, Antonio Pereira","doi":"10.1109/CIVEMSA.2013.6617395","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617395","url":null,"abstract":"This article describes the first steps on the development of a low cost dataglove based on the Arduino Uno microprocessor. The glove is designed for use in virtual reality systems and is integrated into a suite of applications. This article also presents a set of preliminary results obtained with the glove and discuss about the use of the glove to control a video game application for rehabilitation of stroke patients.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132203327","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 : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617390
Channarth Jerome Vantin, D. Megherbi
In today's computing environment, it is well known that the computing bottleneck is rather at the I/O peripheral levels instead of at the level of CPU and memory. The access times to fetch data from an external device such as a CD-ROM, a network drive, or even the delay of dragging a mouse pointer to a desktop icon consumes seconds of time while CPU operations take nanoseconds. In this thesis, we show how our proposed Bayesian technique can anticipate certain memory intensive programs and how it can be used to preload its contents before the user selects the actual program. We evaluate the I/O peripheral of the mouse cursor and how to leverage historic mouse data to make these predictions. We show that using such Artificial Intelligence (AI) techniques results in a more productive computing environment relieving the user from waiting for a program to load.
{"title":"A Bayesian-learning technique for automatic pre-emptive loads through I/O devices via the mouse pointer","authors":"Channarth Jerome Vantin, D. Megherbi","doi":"10.1109/CIVEMSA.2013.6617390","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617390","url":null,"abstract":"In today's computing environment, it is well known that the computing bottleneck is rather at the I/O peripheral levels instead of at the level of CPU and memory. The access times to fetch data from an external device such as a CD-ROM, a network drive, or even the delay of dragging a mouse pointer to a desktop icon consumes seconds of time while CPU operations take nanoseconds. In this thesis, we show how our proposed Bayesian technique can anticipate certain memory intensive programs and how it can be used to preload its contents before the user selects the actual program. We evaluate the I/O peripheral of the mouse cursor and how to leverage historic mouse data to make these predictions. We show that using such Artificial Intelligence (AI) techniques results in a more productive computing environment relieving the user from waiting for a program to load.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129646834","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 : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617405
Yu Zhang, C. Bingham, M. Gallimore, Zhijing Yang, Jun Chen
The paper reports and demonstrates a computationally efficient method for machine fault detection in industrial turbine systems. Empirical mode decomposition (EMD) and Savitzky-Golay smoothing filters are used for signal denoising, with a resulting noise index being developed. By comparing the noise index with a power index (also derived in the paper), obtained from the detection of transients using a spectral analysis of the rate-of-change of unit power, three operational conditions are identifiable viz. normal operation, transient operation and operation when subject to emerging machine faults. The accommodation of transient operational conditions of the unit, so as not to create excessive `false alerts', provides a valuable alternative to more traditional techniques, based on PCA for instance, that can only provide reliable information during steady-state operation. The efficacy of the proposed approaches is demonstrated through the use of experimental trials on sub-15MW gas turbines.
{"title":"Machine fault detection during transient operation using measurement denoising","authors":"Yu Zhang, C. Bingham, M. Gallimore, Zhijing Yang, Jun Chen","doi":"10.1109/CIVEMSA.2013.6617405","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617405","url":null,"abstract":"The paper reports and demonstrates a computationally efficient method for machine fault detection in industrial turbine systems. Empirical mode decomposition (EMD) and Savitzky-Golay smoothing filters are used for signal denoising, with a resulting noise index being developed. By comparing the noise index with a power index (also derived in the paper), obtained from the detection of transients using a spectral analysis of the rate-of-change of unit power, three operational conditions are identifiable viz. normal operation, transient operation and operation when subject to emerging machine faults. The accommodation of transient operational conditions of the unit, so as not to create excessive `false alerts', provides a valuable alternative to more traditional techniques, based on PCA for instance, that can only provide reliable information during steady-state operation. The efficacy of the proposed approaches is demonstrated through the use of experimental trials on sub-15MW gas turbines.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130888532","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 : 2013-07-15DOI: 10.1109/CIVEMSA.2013.6617410
J. L. Muros-Cobos, J. A. Holgado-Terriza, M. Cabrerizo-Vílchez
Nowadays most of people have smartphones which can run complex application. Some kinds of experiments need several hours to finish. Using recent mobiles capabilities, anyone can monitor instruments and equipment efficiently from anywhere. Hence, alert services can prevent users from any incidence on supervised instruments and experiments. In this paper a new monitoring mechanism is proposed for the supervision of an experiment by improving the reception of messages in any case using mobile devices. Finally, a practice case of the implemented mechanism is presented for Android mobiles.
{"title":"Monitoring experiments using mobile devices","authors":"J. L. Muros-Cobos, J. A. Holgado-Terriza, M. Cabrerizo-Vílchez","doi":"10.1109/CIVEMSA.2013.6617410","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2013.6617410","url":null,"abstract":"Nowadays most of people have smartphones which can run complex application. Some kinds of experiments need several hours to finish. Using recent mobiles capabilities, anyone can monitor instruments and equipment efficiently from anywhere. Hence, alert services can prevent users from any incidence on supervised instruments and experiments. In this paper a new monitoring mechanism is proposed for the supervision of an experiment by improving the reception of messages in any case using mobile devices. Finally, a practice case of the implemented mechanism is presented for Android mobiles.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121228869","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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