Crowd-Sourced Sensing and Collaboration Using Twitter

Problem: Despite the availability of the sensor and smartphone devices to fulfill the ubiquitous computing vision, the state-of-the-art has gap due to lack of infrastructure to task/utilize these devices for collaboration and coordination. We propose that Twitter can provide an “open” publish-subscribe infrastructure for sensors and smartphones, and pave the way for ubiquitous crowd-sourced sensing and collaboration applications.

Approach: We design and implement a crowd-sourced sensing and collaboration over Twitter, and showcase our system in the context of two applications: a crowd-sourced weather radar, and a participatory noise-mapping application. Our system is composed of three components namely Askweet, Sensweet and Twitter clients. Sensweet is a smartphone application that publishes real-time readings from the integrated-sensors to Twitter. Askweet is a program that listens to its Twitter account for questions and processes the questions and aggregates the replies it receives to these questions from Sensweet and the Twitter clients.

Contributions: We present an analysis of our real-world Twitter experiments to give insights for the feasibility of our approach. We find that although we do not offer the user any incentives to reply, our queries receive at least 15% reply ratios. Surprisingly, 50% of the total replies arrive within the first 10 minutes of our query, and 80% of the replies arrives within the first 2 hours, enabling low latency operations for crowd-sourcing applications. Our experiments also found that consistently the majority of replies come from users that access Twitter from their mobile phones.

Publications:

Murat Demirbas, Murat Ali Bayir, Cuneyt Gurcan Akcora, Yavuz Selim Yilmaz, Hakan Ferhatosmanoglu, "Crowd-Sourced Sensing and Collaboration Using Twitter". (accepted to WOWMOM 2010) pdf