scholarly journals Sensorial Network Framework Embedded in Ubiquitous Mobile Devices

2019 ◽  
Vol 11 (10) ◽  
pp. 215
Author(s):  
Behan ◽  
Krejcar ◽  
Sabbah ◽  
Selamat
Keyword(s):  
Real Time ◽  
Mobile Devices ◽  
Transmission Control Protocol ◽  
Smart Devices ◽  
Local Networks ◽  
Server Side ◽  
Current Location ◽  
Key Factor ◽  
Comparable Performance ◽  
Smart Mobile

: Today’s digital society is interconnected and networked, with modern smart devices ubiquitously built into and embedded within smart environments and other environments, where people (their users) typically live. It is very important to mention that sensorial awareness of an environment depends on one’s current location and equipment, as well as the equipment’s real-time capabilities. Personal sensorial information is considered to be the key factor for progress in the improvement of the productivity of everyday life and creation of a smart surrounding environment. This paper describes the design, implementation, and testing process of a new sensorial framework based on the current possibilities created by ubiquitous smart mobile devices with sensors, which involves computing power and battery power issues. The two parts of the proposed framework have been designed, implemented, and tested. The client part is represented by a front-end mobile application, and the back-end part is represented by a server-side application. The analysis of the data, captured during the testing phase, involves the analysis of the processing time, battery consumption, and transmitted data amount. This analysis reveals that Transmission Control Protocol (TCP) and user datagram protocol (UDP) protocols have a comparable performance, although TCP is preferable for use in local networks. In comparison to other solutions such as MobiSense or Feel the World framework, the final solution of the proposed and developed sensorial framework has two main capabilities, which are the security support and social networking possibilities. The advantage of the MobiSense platform is the existence of several real-world applications, whereas the proposed sensorial framework needs to be verified in the massive context of many users in real time.

scholarly journals A Smart Collaborative Policy for Mobile Fog Computing in Rural Vitalization

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Yutong Zhou ◽  
Wei Shi ◽  
Fei Song
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Mobile Devices ◽  
Policy Design ◽  
Fog Computing ◽  
Performance Evaluations ◽  
Round Trip Time ◽  
Round Trip ◽  
Trip Time ◽  
Smart Mobile

Mobile Fog Computing (MFC), as a crucial supplement to cloud computing, has its own special traits in many aspects. As smart mobile devices grow and vary in shapes and formats over the years, the need for real-time interactions and an easy-to-use network is imminent. In this paper, we propose a smart collaborative policy for MFC scenarios by considering the target of rural vitalization. The challenges and drawbacks of extending cloud to fog are reviewed at the beginning. Then, the analysis of policy design is presented from the perspectives of feature comparisons, urgent requirements, and possible solutions. The details of policy establishment are introduced with necessary examples. Finally, performance evaluations are provided based on simulation platforms. Validation results related to round trip time and transmission time illustrate the significant improvements of our proposal in certain ways compared to the original candidate, which enables larger deployment in impoverished areas.

scholarly journals UTAUT2 Based Predictions of Factors Influencing the Technology Acceptance of Phablets by DNP

2015 ◽  
Vol 2015 ◽  
pp. 1-23 ◽  
Author(s):  
Chi-Yo Huang ◽  
Yu-Sheng Kao
Keyword(s):  
Technology Acceptance ◽  
Mobile Devices ◽  
Smart Phones ◽  
Smart Devices ◽  
Analytic Framework ◽  
Predicting Factors ◽  
Use Of Technology ◽  
Network Process ◽  
And Performance ◽  
Smart Mobile

The smart mobile devices have emerged during the past decade and have become one of the most dominant consumer electronic products. Therefore, exploring and understanding the factors which can influence the acceptance of novel mobile technology have become the essential task for the vendors and distributors of mobile devices. The Phablets, integrated smart devices combining the functionality and characteristics of both tablet PCs and smart phones, have gradually become possible alternatives for smart phones. Therefore, predicting factors which can influence the acceptance of Phablets have become indispensable for designing, manufacturing, and marketing of such mobile devices. However, such predictions are not easy. Meanwhile, very few researches tried to study related issues. Consequently, the authors aim to explore and predict the intentions to use and use behaviors of Phablets. The second generation of the Unified Theory of Acceptance and Use of Technology (UTAUT2) is introduced as a theoretic basis. The Decision Making Trial and Evaluation Laboratory (DEMATEL) based Network Process (DNP) will be used to construct the analytic framework. In light of the analytic results, the causal relationships being derived by the DEMATEL demonstrate the direct influence of the habit on other dimensions. Also, based on the influence weights being derived, the use intention, hedonic motivation, and performance expectancy are the most important dimensions. The analytic results can serve as a basis for concept developments, marketing strategy definitions, and new product designs of the future Phablets. The proposed analytic framework can also be used for predicting and analyzing consumers’ preferences toward future mobile devices.

scholarly journals Energy-Efficient Real-Time Human Activity Recognition on Smart Mobile Devices

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Jin Lee ◽  
Jungsun Kim
Keyword(s):  
Real Time ◽  
Mobile Devices ◽  
Activity Recognition ◽  
Human Activity ◽  
Energy Efficient ◽  
Window Size ◽  
Human Activity Recognition ◽  
Smart Mobile ◽  
The Impact ◽  
Smart Mobile Devices

Nowadays, human activity recognition (HAR) plays an important role in wellness-care and context-aware systems. Human activities can be recognized in real-time by using sensory data collected from various sensors built in smart mobile devices. Recent studies have focused on HAR that is solely based on triaxial accelerometers, which is the most energy-efficient approach. However, such HAR approaches are still energy-inefficient because the accelerometer is required to run without stopping so that the physical activity of a user can be recognized in real-time. In this paper, we propose a novel approach for HAR process that controls the activity recognition duration for energy-efficient HAR. We investigated the impact of varying the acceleration-sampling frequency and window size for HAR by using the variable activity recognition duration (VARD) strategy. We implemented our approach by using an Android platform and evaluated its performance in terms of energy efficiency and accuracy. The experimental results showed that our approach reduced energy consumption by a minimum of about 44.23% and maximum of about 78.85% compared to conventional HAR without sacrificing accuracy.

scholarly journals Real-Time Physical Activity Recognition on Smart Mobile Devices Using Convolutional Neural Networks

2020 ◽  
Vol 10 (23) ◽  
pp. 8482
Author(s):  
Konstantinos Peppas ◽  
Apostolos C. Tsolakis ◽  
Stelios Krinidis ◽  
Dimitrios Tzovaras
Keyword(s):  
Neural Network ◽  
Physical Activity ◽  
Real Time ◽  
Mobile Devices ◽  
Mobile Device ◽  
Classification Performance ◽  
Sensor Data ◽  
Accelerometer Data ◽  
Smart Mobile ◽  
Fully Connected

Given the ubiquity of mobile devices, understanding the context of human activity with non-intrusive solutions is of great value. A novel deep neural network model is proposed, which combines feature extraction and convolutional layers, able to recognize human physical activity in real-time from tri-axial accelerometer data when run on a mobile device. It uses a two-layer convolutional neural network to extract local features, which are combined with 40 statistical features and are fed to a fully-connected layer. It improves the classification performance, while it takes up 5–8 times less storage space and outputs more than double the throughput of the current state-of-the-art user-independent implementation on the Wireless Sensor Data Mining (WISDM) dataset. It achieves 94.18% classification accuracy on a 10-fold user-independent cross-validation of the WISDM dataset. The model is further tested on the Actitracker dataset, achieving 79.12% accuracy, while the size and throughput of the model are evaluated on a mobile device.

Research on Mobile Information Access Based on Internet of Things

2014 ◽  
Vol 539 ◽  
pp. 460-463 ◽  
Author(s):  
Jiang Tao Geng ◽  
Xiao Bo Xiong
Keyword(s):  
Internet Of Things ◽  
Sensor Network ◽  
Mobile Devices ◽  
Information Access ◽  
Mobile Terminal ◽  
Smart Devices ◽  
Information Collection ◽  
Data Movement ◽  
Mobile Information ◽  
Smart Mobile

The paper design mobile information collection system based on Internet of Things, implemented access gateway by smart mobile devices through a variety of ways, such as Wi-Fi and access the underlying perceptual information based on ZigBee wireless sensor networks. On the one hand, For information sensitivity of the sensor network, we design the mobile terminal through the gateway access authentication protocol, and effective solute the authentication and information between mobile devices and gateways, gateway and sensor network nodes obtain permission problem; on the other hand, according to the practical application of mobile information collection characteristics, the paper proposed information collection strategy based on historical data movement path to solve the problem for too long the device connection is established when the mobile smart devices collecting information along fixed lines, increasing the actual data transmission time and improve the efficiency of information transmission.

Undergraduate Iraqi Students’ Awareness of Social Mobile Media and Their Attitudes to Mobile Learning

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Tahsin YAGCI
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Mobile Devices ◽  
Mobile Learning ◽  
Undergraduate Students ◽  
Electronic Devices ◽  
Smart Devices ◽  
Young Generation ◽  
Northern Iraq ◽  
Smart Mobile

In recent years advances in social networking and rapid developments in wireless internet technologies stimulated all of us to integrate and use them in our lives. Smart mobile technology industries are racing with each other to launch the newest model for their consumers. The biggest market beyond the dispute is teenagers and young generation. Of course, the adults cannot be ignored, either. The general aim to use the social network is for communication and sharing information. During the daytime students want to keep in touch with their peers. The most common electronic devices are smart mobile phones and the top rate for social networking website is Facebook. This study aims to seek for and clarify the perceptions and the attitudes of undergraduate students in Northern Iraq, using electronic devices, in particular, smart mobile devices. What kinds of social media tools and platforms they are registered to? How often do they benefit from their accounts? What is their frequency to login to internet access and what part of the day do students use their mobile devices? What are students’ general purposes to use social media? – these were the questions asked in the research. This article emphasizes the diversity according to gender, faculty, grade, universities, etc. In addition, it seeks for the distribution of social media accounts. An online survey, conducted among different university students to recognize the ratio between various institutions, came to a conclusion that undergraduate students in Northern Iraq are equipped with sufficient smart devices to get involved in mobile learning via using social platforms such as Facebook, Instagram, Twitter, etc.  

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