Home sleep care with video analysis and its application in smart TV

Fan, Ching-Tang; Wang, Yuan-Kai; Chen, Jian-Ru

doi:10.1109/gcce.2014.7031232

Cited by 6 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Compared to traditional TV, besides the possibility to personalize their user environment [4], users appreciate variety of applications that can be installed in the smart TV set, spanning from various games, media and infotainment applications to various services, including employment of smart TV sets in various home IoT solutions. Especially this field is a subject of recent research and development, for instance controlling of smart home appliances [5], [6], smart light management system [7] or the whole smart home solution [8], [9] using a smart TV set, various personal healthcare application employing smart TV, for instance [10] or personal sleep management employing a video analysis using a smart TV application [11]. As another example, smart home security system using cameras and smart TV set can be given [12].…”

Section: Introductionmentioning

confidence: 99%

Testing the Usability and Accessibility of Smart TV Applications Using an Automated Model-Based Approach

Bureš

Macík

Ahmed

et al. 2020

IEEE Trans. Consumer Electron.

View full text Add to dashboard Cite

As the popularity of Smart Televisions (TVs) and interactive Smart TV applications (apps) has recently grown, the usability of these apps has become an important quality characteristic. Previous studies examined Smart TV apps from a usability perspective. However, these methods are mainly manual, and the potential of automated model-based testing methods for usability testing purposes has not yet been fully explored. In this paper, we propose an approach to test the usability of Smart TV apps based on the automated generation of a Smart TV user interaction model from an existing app by a specialized automated crawler. By means of this model, defined user tasks in the Smart TV app can be evaluated automatically in terms of their feasibility and estimated user effort, which reflects the usability of the analyzed app. This analysis can be applied in the context of regular users and users with various specific needs. The findings from this model-based automated analysis approach can be used to optimize the user interface of a Smart TV app to increase its usability, accessibility, and quality.

show abstract

Section: Introductionmentioning

confidence: 99%

Testing the Usability and Accessibility of Smart TV Applications Using an Automated Model-Based Approach

Bureš

Macík

Ahmed

et al. 2020

IEEE Trans. Consumer Electron.

View full text Add to dashboard Cite

show abstract

“…Nowadays, smart TV devices are actively involved in other technologies like smart home, Internet of things (IoT), and controlling other consumer electronics. For example, smart security camera system [13], home sleep care with video analysis using smart TV app [14], controlling the smart home from smart TV [15], Smart Lighting Control [16], healthcare app of smart home [17], home appliances control through Smart TVs [18], [19], and many other apps. It is strongly become difficult to ignore the testing of the smart TV app.…”

Section: Motivation and Related Workmentioning

confidence: 99%

An Automated Testing Framework For Smart TV apps Based on Model Separation

Ahmed¹,

Gargantini²,

Bureš³

2020

Preprint

View full text Add to dashboard Cite

Smart TV application (app) is a new technological software app that can deal with smart TV devices to add more functionality and features. Despite its importance nowadays, far too little attention has been paid to present a systematic approach to test this kind of app so far. In this paper, we present a systematic model-based testing approach for smart TV app. We used our new notion of model separation to use sub-models based on the user preference instead of the exhaustive testing to generate the test cases. Based on the constructed model, we generated a set of test cases to assess the selected paths to the chosen destination in the app. We also defined new mutation operators for smart TV app to assess our testing approach. The evaluation results showed that our approach can generate more comprehensive models of smart TV apps with less time as compared to manual exploratory testing. The results also showed that our approach can generate effective test cases in term of fault detection.

show abstract

“…As another class of smart devices, smart TVs are currently becoming increasingly popular due to the rapid development of apps that can be installed on these devices and the ability to control other consumer electronics and connect with them in the IoT context. Some examples of the possible applications of such technology include controlling home appliances through smart TVs [21], [22], home sleep care with video analysis using a smart TV app [23], controlling smart homes from smart TVs [24], healthcare applications for smart homes [25], smart lighting control [26], and smart security camera systems [27]. With the increasing prevalence of these applications, it is becoming increasingly difficult to ignore the unique requirements of quality assessment for smart TV apps and assume that the same quality assessment procedures can be used as for mobile apps.…”

Section: Background and Related Workmentioning

confidence: 99%

EvoCreeper: Automated Black-Box Model Generation for Smart TV Applications

Ahmed

Bureš

2019

IEEE Trans. Consumer Electron.

View full text Add to dashboard Cite

Smart TVs are coming to dominate the television market. This accompanied by an increase in the use of the smart TV applications (apps). Due to the increasing demand, developers need modeling techniques to analyze these apps and assess their comprehensiveness, completeness, and quality. In this paper, we present an automated strategy for generating models of smart TV apps based on a black-box reverse engineering. The strategy can be used to cumulatively construct a model for a given app by exploring the user interface in a manner consistent with the use of a remote control device and extracting the runtime information. The strategy is based on capturing the states of the user interface to create a model during runtime without any knowledge of the internal structure of the app. We have implemented our strategy in a tool called EvoCreeper. The evaluation results show that our strategy can automatically generate unique states and a comprehensive model that represents the real user interactions with an app using a remote control device. The models thus generated can be used to assess the quality and completeness of smart TV apps in various contexts, such as the control of other consumer electronics in smart houses.

show abstract

Home sleep care with video analysis and its application in smart TV

Cited by 6 publications

References 5 publications

Testing the Usability and Accessibility of Smart TV Applications Using an Automated Model-Based Approach

Testing the Usability and Accessibility of Smart TV Applications Using an Automated Model-Based Approach

An Automated Testing Framework For Smart TV apps Based on Model Separation

EvoCreeper: Automated Black-Box Model Generation for Smart TV Applications

Contact Info

Product

Resources

About