Next Generation TV Ratings Systems

TV ratings conventionally depend on focus groups and/or set top devices that keep track of the channels and shows viewed. This approach has been the main source of information for rating TV shows, sports, news, etc and it has been an integral part of the economics of the TV industry. But with the growing sources of viewing TV programmes either live (using TV sets or online streaming) or later (using video on demand either through set top devices or online portals) and with the growing number of TV viewers posting their opinions about what they are viewing, TV programmes rating is become a more challenging task that requires innovative solutions.

On the other hand, recently booming terms like "Connected Viewers" and "Two Screen Viewing" describe TV viewers that use their smart phones or tablets while watching TV. These smart devices forms a rich source of information on the TV viewing habits of the device's owners. This information can help both the TV industry and the TV viewers. On one side, the TV industry can definitely use information regarding the TV viewing habits streaming in live from millions of mobile devices. In addition to normal ratings information, this new source of information comes with detailed preferences list and characterization of each programme viewer. This new information can help make better ads and make more informed airtime assignments. Moreover, web-based and mobile based advertisers (e.g. Google) can have more information about the mobile device's owner which means more information for their ads engines. On the other hand, the mobile devices' owners can make use of social applications and recommendations that are based on their TV viewing habits.

At the Wireless Research Center @ E-JUST we realized the potential of building such an application. The application enables tracking a mobile device's owner TV habits need to work passively collecting information about each programme and any online activity made while watching that programme (similar to tracking web-browsing history). While the detection of the programme playing on a TV is a well addressed problem and available for free by applications like IntoNow. The problem at hand here is more complex as we cannot assume that the user will activate the application each time he/she is watching a TV.

In our work (accepted at Ubicomm'13) we aim at analyzing the acoustic fingerprint and visual fingerprints of a TV set in order to determine whether a device's owner is viewing a TV or not. Our preliminary results showed a huge potential in using these two sensors (i.e. microphone and camera) to perform the passive detection functionality, allowing applications like IntoNow to identify the programme playing afterwards. 

Our novel stack of applications presents a new generation of audience measurement systems that can provide larger sets of more accurate and higher dimensional data about TV viewing. Also linking the TV viewing habits of a user to her viewing habits of online portals like youtube will give a clearer image of the popularity of TV programmes.

For more details check our technical report on arXiv: Mohamed Ibrahim, Ahmed Saeed, Moustafa Youssef, and Khaled A. Harras, "Unconventional TV Detection using Mobile Devices", arXiv:1306.0478.


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