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Proceedings Paper

Context-aware event detection smartphone application for first responders
Author(s): Sanjay K. Boddhu; Rakesh P. Dave; Matt McCartney; James A. West; Robert L. Williams
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Paper Abstract

The rise of social networking platforms like Twitter, Facebook, etc…, have provided seamless sharing of information (as chat, video and other media) among its user community on a global scale. Further, the proliferation of the smartphones and their connectivity networks has powered the ordinary individuals to share and acquire information regarding the events happening in his/her immediate vicinity in a real-time fashion. This human-centric sensed data being generated in “human-as-sensor” approach is tremendously valuable as it delivered mostly with apt annotations and ground truth that would be missing in traditional machine-centric sensors, besides high redundancy factor (same data thru multiple users). Further, when appropriately employed this real-time data can support in detecting localized events like fire, accidents, shooting, etc…, as they unfold and pin-point individuals being affected by those events. This spatiotemporal information, when made available for first responders in the event vicinity (or approaching it) can greatly assist them to make effective decisions to protect property and life in a timely fashion. In this vein, under SATE and YATE programs, the research team at AFRL Tec^Edge Discovery labs had demonstrated the feasibility of developing Smartphone applications, that can provide a augmented reality view of the appropriate detected events in a given geographical location (localized) and also provide an event search capability over a large geographic extent. In its current state, the application thru its backend connectivity utilizes a data (Text & Image) processing framework, which deals with data challenges like; identifying and aggregating important events, analyzing and correlating the events temporally and spatially and building a search enabled event database. Further, the smartphone application with its backend data processing workflow has been successfully field tested with live user generated feeds.

Paper Details

Date Published: 22 May 2013
PDF: 9 pages
Proc. SPIE 8742, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV, 874213 (22 May 2013); doi: 10.1117/12.2016352
Show Author Affiliations
Sanjay K. Boddhu, Qbase (United States)
Rakesh P. Dave, Qbase (United States)
Matt McCartney, Wright State Univ. (United States)
James A. West, Wright State Univ. (United States)
Robert L. Williams, Tec^Edge Innovation and Collaboration Ctr. (United States)
Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 8742:
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV
Tien Pham; Michael A. Kolodny; Kevin L. Priddy, Editor(s)

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