Pervasive symbiotic advertising

Narayanaswami, Chandra; Coffman, D. M.; Lee, M. C.; Moon, Yong-Eun; Han, Jeongsoo; Jang, Haeseong; McFaddin, Scott; Paik, Y. S.; Kim, J. H.; Lee, J. K; Park, J. W.; Soroker, Danny

doi:10.1145/1411759.1411781

Cited by 10 publications

(3 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The displays are then able to tailor ads depending on the preferences of who is passing by. Narayanaswami and colleagues built a similar system and drew preliminary conclusions about the opportunities and challenges of pervasive advertising [14]. There has been little work on measuring the effectiveness of advertising on bigger displays such as electronic billboards.…”

Section: Existing Techniques For Audience Measurementsmentioning

confidence: 99%

Mobile Phones and Outdoor Advertising: Measurable Advertising

Quercia

Lorenzo

Calabrese

et al. 2011

IEEE Pervasive Comput.

View full text Add to dashboard Cite

Television and newspapers sit at the top of many agency marketing plans, while outdoor advertising stays at the bottom. The reason for this is that it's difficult to account for who views a billboard, so there is no way of consistently determining the effectiveness of outdoor advertising. As a result, agencies do not consider the medium and allocate their money elsewhere. To change this situation, one needs to create new credible audience measurements for the outdoor marketing industry. Here we propose a new way of performing audience measurements that combines mobile phone location estimations with information freely available on the Internet. We show that it is possible to estimate the number of people who drive or walk by a given area in Greater Boston from location estimations of a large fraction of mobile phone users in the region. We also infer the preferences for social events of the users by combing their location estimations with Internet listings of social events. This makes it possible to profile areas based on their residents' interests and dynamically change displayed advertising based on those assessments.

show abstract

Section: Existing Techniques For Audience Measurementsmentioning

confidence: 99%

Mobile Phones and Outdoor Advertising: Measurable Advertising

Quercia

Lorenzo

Calabrese

et al. 2011

IEEE Pervasive Comput.

View full text Add to dashboard Cite

show abstract

“…Our approach, in contrast, builds upon standard devices and platforms, leveraging facility displays for a rich experience. Symbiotic advertising on large displays by utilizing user preferences from users' mobile devices is explored in [20]. The use of multiple devices for display and control is advocated in [18].…”

Section: Related Workmentioning

confidence: 99%

User-driven visual mashups in interactive public spaces

Soroker¹,

Paik²,

Moon³

et al. 2008

Proceedings of the 5th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

Self Cite

View full text Add to dashboard Cite

Searching and presenting rich data using mobile devices is hard given their inherent I/O limitations. One approach for alleviating these limitations is device symbiosis, whereby the interaction with one's personal mobile device is augmented by additionally engaging with more capable infrastructure devices, such as kiosks and displays. The Celadon framework, previously developed by our team, builds upon device symbiosis for delivering zone-based services through mobile and infrastructure devices in public spaces such as shopping malls, train stations and theme parks.An approach for rich data visualization that is gaining wide popularity is mashups. In this paper we describe User-Defined Mashups -a general methodology that combines device symbiosis and automated creation of mashups. We have applied this methodology to build a system that enables Celadon users to flexibly interact with rich zone information through their mobile devices, leveraging large public displays. Our system bridges public and personal devices, data and services.

show abstract

“…Context-based mobile advertising matches advertisement and e-coupons with potential customers according to their locations, activities, or interests [20,21,25]. Symbolic location of a user, such as a store name, is important since a user can get exclusive coupons based on their frequent visits, or receive product recommendations from similar shops.…”

Section: Introductionmentioning

confidence: 99%

SensOrchestra: Collaborative Sensing for Symbolic Location Recognition

Cheng

Sun

Buthpitiya

et al. 2012

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

View full text Add to dashboard Cite

Symbolic location of a user, like a store name in a mall, is essential for context-based mobile advertising. Existing fingerprintbased localization using only a single phone is susceptible to noise, and has a major limitation in that the phone has to be held in the hand at all times. In this paper, we present SensOrchestra, a collaborative sensing framework for symbolic location recognition that groups nearby phones to recognize ambient sounds and images of a location collaboratively. We investigated audio and image features, and designed a classifier fusion model to integrate estimates from different phones. We also evaluated the energy consumption, bandwidth, and response time of the system. Experimental results show that SensOrchestra achieved 87.7% recognition accuracy, which reduces the error rate of single-phone approach by 2X, and eliminates the limitations on how users carry their phones. We believe general location or activity recognition systems can all benefit from this collaborative framework.

show abstract

Pervasive symbiotic advertising

Cited by 10 publications

References 7 publications

Mobile Phones and Outdoor Advertising: Measurable Advertising

Mobile Phones and Outdoor Advertising: Measurable Advertising

User-driven visual mashups in interactive public spaces

SensOrchestra: Collaborative Sensing for Symbolic Location Recognition

Contact Info

Product

Resources

About