scholarly journals Context-Aware User Profiling and Multimedia Content Classification for Smart Devices

2014 ◽  
Author(s):  
Abayomi Moradeyo Otebolaku ◽  
Maria Teresa Andrade
Keyword(s):  
User Profiling ◽  
Smart Devices ◽  
Multimedia Content ◽  
Context Aware ◽  
Content Classification

Efficient Ontology Integration Model for Better Inference in Context Aware Computing

2011 ◽  
Vol 268-270 ◽  
pp. 841-846
Author(s):  
Soo Mi Yang
Keyword(s):  
Video Data ◽  
Smart Devices ◽  
Collaborative Network ◽  
Context Aware ◽  
Integration Model ◽  
Smart Cameras ◽  
Ontology Integration ◽  
Context Aware Computing ◽  
Heterogeneous Devices ◽  
Distributed Ontology

In this paper, we describe efficient ontology integration model for better context inference based on distributed ontology framework. Context aware computing with inference based on ontology is widely used in distributed surveillance environment. In such a distributed surveillance environment, surveillance devices such as smart cameras may carry heterogeneous video data with different transmission ranges, latency, and formats. However even smart devices, they generally have small memory and power which can manage only part of ontology data. In our efficient ontology integration model, each of agents built in such devices get services not only from a region server, but also peer servers. For such a collaborative network, an effective cache framework that can handle heterogeneous devices is required for the efficient ontology integration. In this paper, we propose a efficient ontology integration model which is adaptive to the actual device demands and that of its neighbors. Our scheme shows the efficiency of model resulted in better context inference.

scholarly journals Image Compression Approach using Segmentation and Total Variation Regularization

2021 ◽  
Vol 15 ◽  
pp. 43-47
Author(s):  
Ahmad Shahin ◽  
Walid Moudani ◽  
Fadi Chakik
Keyword(s):  
Image Compression ◽  
Total Variation ◽  
Image Data ◽  
Smart Devices ◽  
Multimedia Content ◽  
Total Variation Regularization ◽  
Second Stage ◽  
Tv Regularization ◽  
Rof Model

In this paper we present a hybrid model for image compression based on segmentation and total variation regularization. The main motivation behind our approach is to offer decode image with immediate access to objects/features of interest. We are targeting high quality decoded image in order to be useful on smart devices, for analysis purpose, as well as for multimedia content-based description standards. The image is approximated as a set of uniform regions: The technique will assign well-defined members to homogenous regions in order to achieve image segmentation. The Adaptive fuzzy c-means (AFcM) is a guide to cluster image data. A second stage coding is applied using entropy coding to remove the whole image entropy redundancy. In the decompression phase, the reverse process is applied in which the decoded image suffers from missing details due to the coarse segmentation. For this reason, we suggest the application of total variation (TV) regularization, such as the Rudin-Osher-Fatemi (ROF) model, to enhance the quality of the coded image. Our experimental results had shown that ROF may increase the PSNR and hence offer better quality for a set of benchmark grayscale images.

Context Reasoning for Predicting Gestational Diabetes Mellitus Using CA-RETE Algorithm

2021 ◽  
Vol 17 (4) ◽  
pp. 41-59
Author(s):  
Deeba K. ◽  
Saravanaguru R. A. K.
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Smart Devices ◽  
Context Aware ◽  
Healthcare Applications ◽  
Context Aware Computing ◽  
Context Reasoning ◽  
Reasoning System ◽  
High Level

Today, IoT-related applications play an important role in scientific world development. Context reasoning emphasizes the perception of various contexts by means of collection of IoT data which includes context-aware decision making. Context-aware computing is used to improve the abilities of smart devices and is increased by smart applications. In this paper, context-aware for the internet of things middleware (CAIM) architecture is used for developing a rule-based system using CA-RETE algorithm. The objective of context-aware systems are concentrated on 1) context reasoning methodologies and analyzing how the technologies will involve enhancing the high-level context data, 2) framework of context reasoning system, 3) implementation of CA-RETE algorithm for predicting gestational diabetes mellitus in healthcare applications.

A Context-Aware Smart TV System with Body-Gesture Control and Personalized Recommendation

2013 ◽  
pp. 115-130
Author(s):  
Wei-Po Lee ◽  
Che KaoLi
Keyword(s):  
Control System ◽  
Personalized Recommendation ◽  
Multimedia Content ◽  
Context Aware ◽  
Social Tag ◽  
Gesture Control ◽  
Human Gestures ◽  
Smart Tv ◽  
Interactive Services

Smart TV enables viewers to conveniently access different multimedia content and interactive services in a single platform. This chapter addresses three important issues to enhance the performance of smart TV. The first is to design a body control system that recognizes and interprets human gestures as machine commands to control TV. The second is to develop a new social tag-based method to recommend most suitable multimedia content to users. Finally, a context-aware platform is implemented that takes into account different environmental situations in order to make the best recommendations.

Realizing IoE for Smart Service Delivery

2020 ◽  
pp. 186-215
Author(s):  
Umar Mahmud ◽  
Shariq Hussain ◽  
Arif Jamal Malik ◽  
Sherjeel Farooqui ◽  
Nazir Ahmed Malik
Keyword(s):  
Industrial Revolution ◽  
Detailed Comparison ◽  
Smart Devices ◽  
Smart Device ◽  
Context Aware ◽  
Museum Guide ◽  
Guide System ◽  
Smart Service ◽  
Comparison Table

Widespread use of numerous hand-held smart devices has opened new avenues in computing. Internet of things (IoT) is the next big thing resulting in the 4th industrial revolution. Coupling IoT with data collection, storage, and processing leads to Internet of everything (IoE). This work outlines the concept of smart device and presents an IoE ecosystem. Characteristics of IoE ecosystem with a review of contemporary research is also presented. A comparison table contains the research finding. To realize IoE, an object-oriented context aware model is presented. This model is based on Unified Modelling Language (UML). A case study of a museum guide system is outlined that discusses how IoE can be implemented. The contribution of this chapter includes review of contemporary IoE systems, a detailed comparison, a context aware IoE model, and a case study to review the concepts.

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