Personalized Context-aware Collaborative Online Activity Prediction

2019 ◽  
Vol 3 (4) ◽  
pp. 1-28 ◽  
Author(s):  
Yali Fan ◽  
Zhen Tu ◽  
Yong Li ◽  
Xiang Chen ◽  
Hui Gao ◽  
...  
Keyword(s):  
Context Aware ◽  
Activity Prediction ◽  
Online Activity

Context-aware activity prediction using human behavior pattern in real smart home environments

2016 ◽  
Author(s):  
Ming-Je Tsai ◽  
Chao-Lin Wu ◽  
Sipun Kumar Pradhan ◽  
Yifei Xie ◽  
Ting-Ying Li ◽  
...  
Keyword(s):  
Human Behavior ◽  
Smart Home ◽  
Behavior Pattern ◽  
Context Aware ◽  
Activity Prediction ◽  
Home Environments ◽  
Smart Home Environments

scholarly journals A context-aware model for human activity prediction and risk inference in actions

2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Alfredo Del Fabro Neto ◽  
Bruno Romero de Azevedo ◽  
Rafael Boufleuer ◽  
João Carlos D. Lima ◽  
Iara Augustin ◽  
...  
Keyword(s):  
Human Activity ◽  
Context Aware ◽  
Activity Prediction

scholarly journals A Context-Aware mHealth System for Online Physiological Monitoring in Remote Healthcare

2015 ◽  
Vol 11 (1) ◽  
pp. 142 ◽  
Author(s):  
Weiping Zhang ◽  
Kerstin Thurow ◽  
Regina Stoll
Keyword(s):  
Physiological Stress ◽  
Human Subjects ◽  
Risk Groups ◽  
Daily Activities ◽  
Upper Body ◽  
Context Aware ◽  
Online Activity ◽  
Real Time Analysis ◽  
Biological Stress ◽  
Acceleration Sensors

<p class="Abstract">Physiological or biological stress is an organism’s response to a stressor such as an environmental condition or a stimulus. The identification of physiological stress while performing the activities of daily living is an important field of health research in preventive medicine. Activities initiate a dynamic physiological response that can be used as an indicator of the overall health status. This is especially relevant to high risk groups; the assessment of the physical state of patients with cardiovascular diseases in daily activities is still very difficult. This paper presents a context-aware telemonitoring platform, IPM-mHealth, that receives vital parameters from multiple sensors for online, real-time analysis. IPM-mHealth provides the technical basis for effectively evaluating patients’ physiological conditions, whether inpatient or at home, through the relevance between physical function and daily activities. The two core modules in the platform include: 1) online activity recognition algorithms based on 3-axis acceleration sensors and 2) a knowledge-based, conditional-reasoning decision module which uses context information to improve the accuracy of determining the occurrence of a potentially dangerous abnormal heart rate. Finally, we present relevant experiments to collect cardiac information and upper-body acceleration data from the human subjects. The test results show that this platform has enormous potential for use in long-term health observation, and can help us define an optimal patient activity profile through the automatic activity analysis.</p>

Context-Aware Mobile System for Public Bus Transportation

2014 ◽  
pp. 102-111
Author(s):  
Mitja Krajnc ◽  
Vili Podgorelec ◽  
Marjan Heričko
Keyword(s):  
Context Awareness ◽  
Mobile Applications ◽  
User Interaction ◽  
Context Aware ◽  
Mobile System ◽  
Activity Prediction ◽  
Context Data ◽  
Current Context ◽  
Windows Phone ◽  
Bus Transportation

The spread of smartphones in recent years announced an era of smarter and advanced mobile applications that not only show information but also adapt themselves to users’ surroundings. In this chapter, the authors present a context-aware mobile system in public bus transportation domain based on Windows Phone platform. The principal objective of this system is using users’ location, identity, and timeframe as context data to tailor shown information according to users’ needs. Together with users’ previous actions, the system predicts intended activity in the form of presenting users with preferred bus lines in the current context. The developed system shows how context-awareness and activity prediction can be combined to create mobile applications that do not require a lot of user interaction but still offer detailed information about specific domains.

Evidence-Based Context-Aware Log Data Management for Integrated Monitoring System

2018 ◽  
Vol E101.B (9) ◽  
pp. 1997-2006 ◽  
Author(s):  
Tatsuya SATO ◽  
Yosuke HIMURA ◽  
Yoshiko YASUDA
Keyword(s):  
Data Management ◽  
Monitoring System ◽  
Evidence Based ◽  
Context Aware ◽  
Integrated Monitoring ◽  
Log Data

SOCIAL MEDIA FOR BEGINNERS

2018 ◽  
Vol 8 (3) ◽  
pp. 24
Author(s):  
Matthew N. O. Sadiku ◽  
Mahamadou Tembely ◽  
Sarhan M. Musa
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Modern Society ◽  
Paper Briefly ◽  
Online Activity

Social media (or social networking) is a universal phenomenon.  It is the most popular online activity worldwide. It empowers people to share their opinions with others online.It has opened new ways of communication in the hyper-connected world. It has become an integral part of modern society as they provide means of interacting and socializing. This paper briefly introduces beginners to social media.

A formal context-aware model for web service composition

2014 ◽  
Author(s):  
Li Bao ◽  
Zhiqiang Liu ◽  
Yonghong Tian
Keyword(s):  
Web Service ◽  
Service Composition ◽  
Web Service Composition ◽  
Formal Context ◽  
Context Aware

Context-Aware Local Binary Feature Learning An Approach For Face Recognition

2019 ◽  
Vol 7 (6) ◽  
pp. 462-465
Author(s):  
Sushmitamai K. Ahire ◽  
Nilesh R. Wankhade
Keyword(s):  
Face Recognition ◽  
Feature Learning ◽  
Context Aware ◽  
Binary Feature

Context Aware Data Gathering Study

2019 ◽  
Author(s):  
Keyword(s):  
Data Gathering ◽  
Context Aware
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