Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems 2015
DOI: 10.1145/2702613.2732858
|View full text |Cite
|
Sign up to set email alerts
|

Design of a Smart TV Logging System Using Beacons and Smartphones

Abstract: In this paper, a smart TV logging system comprising a beacon system and smartphones is proposed. To investigate the feasibility of our strategy, we designed and implemented a prototype system and conducted a trial study. The study results show that the prototype can unobtrusively capture viewers' various events embedded in TV viewing behavior. The results of the study also suggest that the proposed method allows more robust and accurate data to be collected than do the TV viewing behavior analysis approaches u… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
2
1
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(2 citation statements)
references
References 4 publications
0
2
0
Order By: Relevance
“…In addition to these users' data, smartphone app-use information was used to figure out what users did while watching TV. Another smart TV logging system has been proposed [58] consisting of a Beacon system, a smartphone, and a camera. This system's main purpose is to precisely determine the user viewing activities and viewer behavior in a household.…”
Section: Smart Tv-based Lifelogging Systemsmentioning
confidence: 99%
See 1 more Smart Citation
“…In addition to these users' data, smartphone app-use information was used to figure out what users did while watching TV. Another smart TV logging system has been proposed [58] consisting of a Beacon system, a smartphone, and a camera. This system's main purpose is to precisely determine the user viewing activities and viewer behavior in a household.…”
Section: Smart Tv-based Lifelogging Systemsmentioning
confidence: 99%
“…Different approaches such as computer vision, machine learning, recording and observing in the lab environment, human interaction, surveys, and content analysis have been used to measure the viewers' behavior patterns [63][64][65][66][67][68]. The data collected through the logging system is more robust and authentic than the qualitative research studies such as surveys and interviews [58]. Therefore, the development and use of smart TV-based lifelogging systems (smart-log) are one of the best choices to analyze and identify household family members' various watching behavior patterns.…”
Section: Viewers Watching Behaviorsmentioning
confidence: 99%