A System Designed to Collect Users' TV-Watching Data Using a Smart TV, Smartphones, and Smart Watches

Seo, Jehwan; Lim, Hyunchul; Oh, Changhoon; Yun, Hyun-Kyu; Suh, Bongwon; Lee, Joongseek

doi:10.1145/2932206.2933562

Cited by 6 publications

(4 citation statements)

References 5 publications

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Section: Related Workmentioning

confidence: 99%

“…In addition, several methods that record user's viewing behavior have been developed [5,6]. [5] proposed a logging system, which included a smart TV, phone and watch, and could effectively determine the user's TV viewing behavior. [6] confirmed that the proposed system could estimate the time spent on TV viewing behavior at home by combining the infrared signal logs of the TV, IP packet data, Bluetooth signal sensor and brightness sensor data.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, there is no control by the user over the viewing history. In contrast, [5] and [6] proposed a method for recording viewing history data on the user side, but they did not aim to record a viewing history indicating what was viewed and when. Here, our aim is to combine the user-centric collection of viewing history data and the acquisition of the viewing history data that can identify what content was viewed through online video services.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Personal Viewing History Collection Method for Video Streaming Services in User-Centric Model

Sekine

Matsumura

Fujii

2021

ACM International Conference on Interactive Media Experiences

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The personal viewing history of broadcast and internet content can be used to improve the quality of online services for the user; consequently, enhancing a person's experience in their daily life. This study proposes a collection method of the personal viewing history of online video streaming services in a user-centric model, where the user owns and controls their data. By obtaining event data from a video element of HTML5 in a video streaming player on a web browser, users can store their viewing history separately from the service provider's system. Because this method employs standardized web technologies, it can be applied to multiple viewing devices and player implementations. Additionally, a prototype of a video streaming player extension is developed. Implementation of the proposed method and verification tests are conducted on the prototype. The results obtained suggest that the proposed method is applicable to existing HTML5 compliant web browsers.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Personal Viewing History Collection Method for Video Streaming Services in User-Centric Model

Sekine

Matsumura

Fujii

2021

ACM International Conference on Interactive Media Experiences

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“…They claimed that we could create a new service that is much more useful than existing services by aggregating lifelog data from multiple sources. A smart TV logging system [57] consisting of a smart TV, a smartphone, and a smartwatch has been proposed that received signal strength indication (RSSI), an accelerometer, and a gyroscope data from smartwatches be used to track user activities and determine whether the user is located in the smart TV watch area. In addition to these users' data, smartphone app-use information was used to figure out what users did while watching TV.…”

Section: Smart Tv-based Lifelogging Systemsmentioning

confidence: 99%

Smart TV-Based Lifelogging Systems: Current Trends, Challenges, and the Road Ahead

Khan

Khusro

Alam

2021

Information and Knowledge in Internet of Things

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The phenomena of lifelogging can be described as "to digitally record the people's daily-life activities and events in varying amounts of detail" [1]. The lifelogging systems use various tools, applications, and devices, such as desktop computers, laptops, smartphones, wearable smart devices, biometric devices, and process the data for explaining the individual's daily-life activities [2]. This recorded information can offer the potential to mine or infer knowledge about life experiences and used for a variety of purposes including contextual recommendation, e-commerce, monitoring, memory augmentation, linking, summarization, contextual retrieval, browsing, the judicial system, searching, adaptive user interface, and analyzing user profiles [3]. Usually, these personalized devices captured a single user's events to help predict and find out different patterns, such as healthcare services, social network services, intelligent mirror services, and recommendation services. Moreover, a user must be actively involved during the lifelogging [4].Lifelogging is a form of pervasive computing. Users can digitally record, capture, store, archive, and process the individuals' complete life experiences in the form of multimodal through different sensors [5]. The main idea of lifelogging to enhance the way people record and exchange their data, information, communication with others, and log into tools or devices [6]. Besides, the concept of lifelogging, to gain knowledge and data about someone, is just like automated biography. However, the lifelogging applications/tools of these devices have been used for single-user life experiences. For example, lifelogging applications and computer tools, such as Latent [7], have their own perspective of live experiences. However, these

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Deep Learning Approach of Raw Human Activity Data

Amroun¹,

Temkit²,

Ammi³

2018

Challenges of the Internet of Things

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A System Designed to Collect Users' TV-Watching Data Using a Smart TV, Smartphones, and Smart Watches

Cited by 6 publications

References 5 publications

Personal Viewing History Collection Method for Video Streaming Services in User-Centric Model

Personal Viewing History Collection Method for Video Streaming Services in User-Centric Model

Smart TV-Based Lifelogging Systems: Current Trends, Challenges, and the Road Ahead

Deep Learning Approach of Raw Human Activity Data

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