Context-Aware Algorithm for Enhancing Quality of on-the-go Media Streaming in no Signal Areas

Author(s):  
Mihajlo Milotic ◽  
Jelena Vlaovic ◽  
Milos Mozetic ◽  
Nikola Teslic
2020 ◽  
Author(s):  
Diandre de Paula ◽  
Daniel Saraiva ◽  
Romeiro Natália ◽  
Nuno Garcia ◽  
Valderi Leithardt

With the growth of ubiquitous computing, context-aware computing-based applications are increasingly emerging, and these applications demonstrate the impact that context has on the adaptation process. From the context, it will be possible to adapt the application according to the requirements and needs of its users. Therefore, the quality of the context information must be guaranteed so that the application does not have an incorrect or unexpected adaptation process. But like any given data, there is the possibility of inaccuracy and/or uncertainty and so Quality of Context (QoC) plays a key role in ensuring the quality of context information and optimizing the adaptation process. To guarantee the Quality of Context it is necessary to study a quality model to be created, which will have the important function of evaluating the context information. Thus, it is necessary to ensure that the parameters and quality indicators to be used and evaluated are the most appropriate for a given type of application. This paper aims to study a context quality model for the UbiPri middleware, defining its quality indicators to ensure its proper functioning in the process of adaptation in granting access to ubiquitous environments. Keywords: QoC, Model, Context-Aware, Data, Privacy


Author(s):  
José Bringel Filho ◽  
Nazim Agoulmine

Ubiquitous Health (U-Health) smart homes are intelligent spaces capable of observing and correctly recognizing the activities and health statuses of their inhabitants (context) to provide the appropriate support to achieve an overall sense of health and well-being in their inhabitants’ daily lives. With the intrinsic heterogeneity and large number of sources of context information, aggregating and reasoning on low-quality raw sensed data may result in conflicting and erroneous evaluations of situations, affecting directly the reliability of the U-Health systems. In this environment, the evaluation and verification of Quality of Context (QoC) information plays a central role in improving the consistency and correctness of context-aware U-Health applications. Therefore, the objective of this chapter is to highlight the impact of QoC on the correct behavior of U-Health systems, and introduce and analyze the existing approaches of modeling, evaluating, and using QoC to improve its context-aware decision-making support.


Using sensors in healthcare can greatly improve the quality of life, especially for elderly patients. The data from the sensors of the patients is constantly monitored for abnormalities at a server. Whenever this data crosses a threshold value, the information is notified to the corresponding doctor. The doctor can then take the necessary action. However an inspection of historical data has shown that some conditions of patients have cyclic patterns and the medications are often repeated. The proposed system is designed to assist the doctor in diagnosis by retrieving those patterns. We have compared the times taken for receiving responses from the two different systems and a significant amount of improvement was noticed. We have introduced a Dynamic Context Aware Technique (DCAT) which can improve the quality of 24 hour monitoring patient. This paper presents the design and implementation of a system based on DCAT using SAMSUNG GEAR S (Heart rate monitor sensor.The backend remote centralized computation and data storage can decreases the workload of the remote health care provider by avoiding of sending the identical and similar cases data to the doctors. This improves the processing speed and also gives solutions in case of the unavailability of doctors in some cases. Experimental results based on real datasets show that our system is highly efficient and scalable to a long time monitoring patients.


2020 ◽  
Vol 19 (s) ◽  
pp. 1-1
Author(s):  
S. Casaccia ◽  
G.M. Revel ◽  
L. Scalise ◽  
R. Bevilacqua ◽  
L. Rossi ◽  
...  

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