TY - GEN
T1 - Story line
T2 - 2nd IEEE/ACM International Conference on Internet-of-Things Design and Implementation, IoTDI 2017
AU - Wang, Shiguang
AU - Giridhar, Prasanna
AU - Wang, Hongwei
AU - Kaplan, Lance
AU - Pham, Tien
AU - Yener, Aylin
AU - Abdelzaher, Tarek
N1 - Funding Information:
We sincerely thank Dr. Octav Chipara for shepherding this paper and the anonymous reviewers for their valuable comments that significantly enhanced the final manuscript. Research reported in this paper was sponsored in part by the Army Research Laboratory under Cooperative Agreement W911NF-09-2-0053 and in part by NSF under grants CNS 16-18627 and CNS 13-20209. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory, NSF, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.
Publisher Copyright:
© 2017 ACM.
PY - 2017/4/18
Y1 - 2017/4/18
N2 - Some of the most widely deployed IoT devices in urban areas are smartphones in the possession of urban individuals. Their proliferation has led to the emergence of crowdsensing/crowdsourcing services, where humans collect data about their environment (using phones), and servers aggregate the data for various application purposes of interest. With the emergence of social media, a common alternative form of human data entry has become media posts (e.g., on Twitter). This leads to the prospect of building crowdsensing services on top of social media content, exploiting humans as "sensors". In this paper, we develop one such service, called StoryLine. the service detects and tracks physical urban events of interest to the user, such as car accidents, infrastructure damage (in the aftermath of a natural disaster), or instances of civil unrest. It others an interface to client-side software that allows browsing such events in real time, as well as an interface for software applications to a structured representation of the events and their related statistics. the service embodies novel algorithms for real-time detection, demultiplexing, and tracking of physical events using social media data. In our evaluation with Twitter feeds, we show that our service outperforms two state-of-the-art baselines in event detection and demultiplexing. We also conduct two case-studies to show the effectiveness of the real-time event detection capability and event tracking performance of our system.
AB - Some of the most widely deployed IoT devices in urban areas are smartphones in the possession of urban individuals. Their proliferation has led to the emergence of crowdsensing/crowdsourcing services, where humans collect data about their environment (using phones), and servers aggregate the data for various application purposes of interest. With the emergence of social media, a common alternative form of human data entry has become media posts (e.g., on Twitter). This leads to the prospect of building crowdsensing services on top of social media content, exploiting humans as "sensors". In this paper, we develop one such service, called StoryLine. the service detects and tracks physical urban events of interest to the user, such as car accidents, infrastructure damage (in the aftermath of a natural disaster), or instances of civil unrest. It others an interface to client-side software that allows browsing such events in real time, as well as an interface for software applications to a structured representation of the events and their related statistics. the service embodies novel algorithms for real-time detection, demultiplexing, and tracking of physical events using social media data. In our evaluation with Twitter feeds, we show that our service outperforms two state-of-the-art baselines in event detection and demultiplexing. We also conduct two case-studies to show the effectiveness of the real-time event detection capability and event tracking performance of our system.
UR - http://www.scopus.com/inward/record.url?scp=85019036878&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019036878&partnerID=8YFLogxK
U2 - 10.1145/3054977.3054992
DO - 10.1145/3054977.3054992
M3 - Conference contribution
AN - SCOPUS:85019036878
T3 - Proceedings - 2017 IEEE/ACM 2nd International Conference on Internet-of-Things Design and Implementation, IoTDI 2017 (part of CPS Week)
SP - 83
EP - 93
BT - Proceedings - 2017 IEEE/ACM 2nd International Conference on Internet-of-Things Design and Implementation, IoTDI 2017 (part of CPS Week)
PB - Association for Computing Machinery, Inc
Y2 - 18 April 2017 through 20 April 2017
ER -
