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Conference on mobile devices and multimedia: enabling technologies, algorithms, and applications

作者： Schmidt, Erick Akopian, David Univ Texas San Antonio Dept Elect Engn San Antonio TX 78249 USA

ISBN: (纸本)9781628415018

With the growing integration of location based services (LBS) such as GPS in mobile devices, indoor position systems (IPS) have become an important role for research. There are several IPS methods such as AOA, TOA, TDOA, which use trilateration for indoor location estimation but are generally based on line-of-sight. Other methods rely on classification such as fingerprinting which uses WLAN indoor signals. This paper re-examines the classical WLAN fingerprinting accuracy which uses received signal strength (RSS) measurements by introducing channel estimates for improvements in the classification of indoor locations. The purpose of this paper is to improve existing classification algorithms used in fingerprinting by introducing channel estimates when there are a low number of APs available. The channel impulse response, or in this case the channel estimation from the receiver, should characterize a complex indoor area which usually has multipath, thus providing a unique signature for each location which proves useful for better pattern recognition. In this experiment, channel estimates are extracted from a Software-Defined Radio (SDR) environment, thus exploiting the benefits of SDR from a NI-USRP model and LabVIEW software. Measurements are taken from a known building, and several scenarios with one and two access points (APs) are used in this experiment. Also, three granularities in distance between locations are analyzed. A Support Vector Machine (SVM) is used as the algorithm for pattern recognition of different locations based on the samples taken from RSS and channel estimation coefficients.

关键词： indoor positioning WLAN 802.11 fingerprinting channel estimate SVM

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mobile-based text recognition from water quality devices

Mobile-based text recognition from water quality devices

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Conference on mobile devices and multimedia: enabling technologies, algorithms, and applications

作者： Dhakal, Shanti Rahnemoonfar, Maryam Texas A&M Univ Corpus Christi Sch Engn & Comp Sci Corpus Christi TX 78412 USA

ISBN: (纸本)9781628415018

Measuring water quality of bays, estuaries, and gulfs is a complicated and time-consuming process. YSI Sonde is an instrument used to measure water quality parameters such as pH, temperature, salinity, and dissolved oxygen. This instrument is taken to water bodies in a boat trip and researchers note down different parameters displayed by the instrument's display monitor. In this project, a mobile application is developed for Android platform that allows a user to take a picture of the YSI Sonde monitor, extract text from the image and store it in a file on the phone. The image captured by the application is first processed to remove perspective distortion. Probabilistic Hough line transform is used to identify lines in the image and the corner of the image is then obtained by determining the intersection of the detected horizontal and vertical lines. The image is warped using the perspective transformation matrix, obtained from the corner points of the source image and the destination image, hence, removing the perspective distortion. Mathematical morphology operation, black-hat is used to correct the shading of the image. The image is binarized using Otsu's binarization technique and is then passed to the Optical Character Recognition (OCR) software for character recognition. The extracted information is stored in a file on the phone and can be retrieved later for analysis. The algorithm was tested on 60 different images of YSI Sonde with different perspective features and shading. Experimental results, in comparison to ground-truth results, demonstrate the effectiveness of the proposed method.

关键词： Document image extraction image processing

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mobile micro-colorimeter and micro-spectrometer sensor modules as enablers for the replacement of subjective inspections by objective measurements for optically clear colored liquids in-field

Mobile micro-colorimeter and micro-spectrometer sensor modul...

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Conference on mobile devices and multimedia: enabling technologies, algorithms, and applications

作者： Dittrich, Paul-Gerald Grunert, Fred Ehehalt, Joerg Hofmann, Dietrich Technol & Innovat Pk Jena GmbH SpectroNet D-07745 Jena Germany MAZeT GmbH JENCOLOR D-07745 Jena Germany RGB Lasersyst GmbH D-93309 Kelheim Germany

ISBN: (纸本)9781628415018

Aim of the paper is to show that the colorimetric characterization of optically clear colored liquids can be performed with different measurement methods and their application specific multichannel spectral sensors. The possible measuremet n methods are differentiated by the applied types of multichannel spectral sensors and therefore by their spectral resolutio, n measurement speed, measurement accuracy and measurement costs. The paper describes how different types of multichannel spectral sensors are calibrated with different types of calibration methods and how the measurement values can be used for further colorimetric calculations. The different measurement methods and the different application specicf i calibration methods will be explained methodically and theoretically. The paper proofs that and how different multichannel spectral sensor modules with different calibration methods can be applied with smartpads for the calculation of measurement results both in laboratory and in field. A given practical example is the application of differet n multichannel spectral sensors for the colorimetric characterization of petroleum oils and fuels and their colorimetcr i characterization by the Saybolt color scale.

关键词： Sensors Calibration Liquids Sensor calibration Color difference Inspection Spectroscopy Computing systems Optical testing Platinum

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APP and PHY in Harmony: Demonstrating Scalable Video Streaming Supported by Flexible Physical Layer Control 16

APP and PHY in Harmony: Demonstrating Scalable Video Streami...

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IEEE 16th International Symposium on a World of Wireless, mobile and multimedia Networks (WoWMoM)

作者： Stohr, Denny Schulz, Matthias Hollick, Matthias Effelsberg, Wolfgang Tech Univ Darmstadt Secure Mobile Networking Lab Darmstadt Germany Tech Univ Darmstadt Distributed Multimedia Syst Darmstadt Germany

ISBN: (纸本)9781479984619

Wireless, high-bandwidth data transfer gains increasing significance with a wider adoption of high-quality video streaming on mobile devices. technologies enabling such data transfer (e.g., 802.11 or LTE) can adapt dynamically to changing conditions, which allows data transfers in a reliable way. However, applications have little or no influence on how those underlying systems execute their adaptations. Yet, in applications such as video streaming, this could provide important clues on what requirements are relevant for data delivery. In this demonstration, we present a system that allows application-defined underlay control to use such potentials in a mobile scalable video based streaming scenario by combining Android smartphones with software-defined radios (SDRs) for advanced physical layer control.

关键词： scalable video Video streaming data transmission APP gene Physical layer Streaming Local thermodynamic equilibrium Software radio

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The Application of Machine Learning in Multi Sensor Data Fusion for Activity Recognition in mobile Device Space 2

The Application of Machine Learning in Multi Sensor Data Fus...

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Conference on Image Sensing technologies - Materials, devices, Systems, and applications II

作者： Marhoubi, Asmaa H. Saravi, Sara Edirisinghe, Eran A. Univ Loughborough Dept Comp Sci Loughborough Leics England

ISBN: (纸本)9781628415971

The present generation of mobile handheld devices comes equipped with a large number of sensors. The key sensors include the Ambient Light Sensor, Proximity Sensor, Gyroscope, Compass and the Accelerometer. Many mobile applications are driven based on the readings obtained from either one or two of these sensors. However the presence of multiple-sensors will enable the determination of more detailed activities that are carried out by the user of a mobile device, thus enabling smarter mobile applications to be developed that responds more appropriately to user behavior and device usage. In the proposed research we use recent advances in machine learning to fuse together the data obtained from all key sensors of a mobile device. We investigate the possible use of single and ensemble classifier based approaches to identify a mobile device's behavior in the space it is present. Feature selection algorithms are used to remove non-discriminant features that often lead to poor classifier performance. As the sensor readings are noisy and include a significant proportion of missing values and outliers, we use machine learning based approaches to clean the raw data obtained from the sensors, before use. Based on selected practical case studies, we demonstrate the ability to accurately recognize device behavior based on multi-sensor data fusion.

关键词： Activity Recognition mobile phone mobile Sensors Gyroscope Accelerometer Multi Sensor

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multimedia content delivery between mobile cloud and mobile devices 13

Multimedia content delivery between mobile cloud and mobile ...

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13th International Conference on Ad-hoc Networks and Wireless, ADHOC-NOW 2014 accompanied by 2nd International Workshop on Emerging technologies for Smart devices, ETSD 2014, 2nd International Workshop on Marine Sensors and Systems, MARSS 2014, multimedia Wireless ad hoc Networks, MWaoN 2014, Security in Ad Hoc Networks, SecAN 2014, 2nd Smart Sensor Protocols and algorithms, SSPA 2014 and 8th International Workshop on Wireless Sensor, Actuator and Robot Networks, WiSARN 2014

作者： Jakimovski, Goran Karadimce, Aleksandar Davcev, Danco Skopje Macedonia Skopje Macedonia

ISBN: (纸本)9783662463376

The usage of mobile devices in everyday life poses new challenges for processing, adaptation and rendering of multimedia content, which can’t be accomplished due to mobile device limitations (battery lifetime, storage limitation, processing capacity and etc.). The proposed mobile Cloud Content Delivery (MCCD) framework shows how multimedia delivery applications and services can efficiently exploit the computing power of mobile cloud resources to achieve high efficient delivery of multimedia content. The experimental case study shows how local multimedia content from the mobile device can be offloaded and processed in the mobile cloud and the transformed multimedia content can be delivered back to the user’s mobile device. The case study further shows that using different communication protocols (EDGE, 3G and LTE) to offload media content to MCCD can significantly influence the turnaround computational time. © Springer-Verlag Berlin Heidelberg 2015.

关键词： multimedia services

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Beyond the Monograph: Publishing Research for multimedia and Multiplatform Delivery

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JOURNAL OF SCHOLARLY PUBLISHING 2015年第4期46卷 321-342页

作者： Mrva-Montoya, Agata Sydney University Press Australia

The output of university presses remains centred on a stand-alone, print-driven book paradigm, despite technological developments that can enable interaction, communication, and interconnection.' In order to improve the distribution of books, several university presses have invested in the development of online content platforms, but the great majority of digital publishing output is limited to PDF, ePub, and HTML files. Inspired by increasing popularity of mobile technologies and devices, this article investigates opportunities for greater use of digital media in scholarly book publishing. It focuses on the feasibility of producing ebook applications and using social networking platforms as a way to make complex information accessible to wider audiences enabling improved research dissemination and increased engagement with individual works.

关键词： scholarly publishing mobile technologies ebook applications social networking platforms scholarly digital editions

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13th International Conference on Ad-hoc Networks and Wireless, ADHOC-NOW 2014 accompanied by 2nd International Workshop on Emerging technologies for Smart devices, ETSD 2014, 2nd International Workshop on Marine Sensors and Systems, MARSS 2014, multimedia Wireless ad hoc Networks, MWaoN 2014, Security in Ad Hoc Networks, SecAN 2014, 2nd Smart Sensor Protocols and algorithms, SSPA 2014 and 8th International Workshop on Wireless Sensor, Actuator and Robot Networks, WiSARN 2014

13th International Conference on Ad-hoc Networks and Wireles...

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ISBN: (纸本)9783662463376

The proceedings contain 25 papers. The special focus in this conference is on 2nd international workshop on emerging technologies for smart devices, ETSD 2014, 2nd international workshop on marine sensors and systems, MARSS 2014, multimedia wireless ad hoc networks 2014, MWaoN 2014, 2nd smart sensor protocols and algorithms - SSPA2014 and 8th international workshop on wireless sensor and actuator and robot networks - WiSARN 2014. The topics include: multimedia content delivery between mobile cloud and mobile devices;delayed key exchange for constrained smart devices;the time calibration system of KM3NET: the laser beacon and the nanobeacon;adaptive data collection in sparse underwater sensor networks using mobile elements;cross layer ant based routing protocol for wireless multimedia sensor network;access and resources reservation in 4G-VANETs for multimedia applications;a smart M2M deployment to control the agriculture irrigation;a location prediction based data gathering protocol for wireless sensor networks using a mobile sink;virtual localization for robust geographic routing in wireless sensor networks and micro robots for dynamic sensor networks.

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Power-Aware Computing in Wearable Sensor Networks: An Optimal Feature Selection

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IEEE TRANSACTIONS ON mobile COMPUTING 2015年第4期14卷 800-812页

作者： Ghasemzadeh, Hassan Amini, Navid Saeedi, Ramyar Sarrafzadeh, Majid Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99164 USA Univ Calif Los Angeles Jules Stein Eye Inst Los Angeles CA 90095 USA Univ Calif Los Angeles Wireless Hlth Inst Los Angeles CA 90095 USA Univ Calif Los Angeles Dept Comp Sci Los Angeles CA 90095 USA

Wearable sensory devices are becoming the enabling technology for many applications in healthcare and well-being, where computational elements are tightly coupled with the human body to monitor specific events about their subjects. Classification algorithms are the most commonly used machine learning modules that detect events of interest in these systems. The use of accurate and resource-efficient classification algorithms is of key importance because wearable nodes operate on limited resources on one hand and intend to recognize critical events (e.g., falls) on the other hand. These algorithms are used to map statistical features extracted from physiological signals onto different states such as health status of a patient or type of activity performed by a subject. Conventionally selected features may lead to rapid battery depletion, mainly due to the absence of computing complexity criterion while selecting prominent features. In this paper, we introduce the notion of power-aware feature selection, which aims at minimizing energy consumption of the data processing for classification applications such as action recognition. Our approach takes into consideration the energy cost of individual features that are calculated in real-time. A graph model is introduced to represent correlation and computing complexity of the features. The problem is formulated using integer programming and a greedy approximation is presented to select the features in a power-efficient manner. Experimental results on thirty channels of activity data collected from real subjects demonstrate that our approach can significantly reduce energy consumption of the computing module, resulting in more than 30 percent energy savings while achieving 96.7 percent classification accuracy.

关键词： Real-time systems and embedded systems emerging technologies wearable computers healthcare human-centered computing signal processing ubiquitous computing low-power design optimization

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Prediction Model for Mental and Physical Health Condition using Risk Ratio EM

Prediction Model for Mental and Physical Health Condition us...

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International Conference on Information Networking (ICOIN)

作者： Jung, Yuchae Yoon, Yongik Sookmyung Womens Univ Dept Multimedia Seoul South Korea

ISBN: (纸本)9781479983421

Recently, mobile applications which provide health services at anytime and anywhere are on demand due to the growth of mobile wireless technologies. For the health service, an inspection service middleware is needed for monitoring health condition such as observing and analyzing EEG ( electroencephalography), ECG ( electrocardiography) and EMG ( Electrocardiogram) waveforms from wearable ECG devices under the coverage of a wireless sensor network ( WSN). For the inspection service middleware, we propose a new notion of prediction model based on risk ratio Expectation Maximization ( EM) by monitoring real-time bio-signals. The prediction model can detect abnormal health condition by the monitoring system. In this paper, we explain the detail algorithms and results for these steps based on EM. There are the five modules as follows: ( 1) The measurement of bio-signals such as body temperature, EEG, ECG and EMG, ( 2) Object assessment from measurement wavelength, ( 3) Situation assessment from GPS in smart device, ( 4) Maximized health condition using risk ratio EM, ( 5) Knowledge update and decision making for healthy life.

关键词： inspection service middleware bio-signal monitoring health condition Expectation Maximization (EM)

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