Paper Info
Title
Large-Scale Situation Awareness With Camera Networks and Multimodal Sensing
Abstract
Sensors of various modalities and capabilities, especially cameras, have become ubiquitous in our environment. Their intended use is wide ranging and encompasses surveillance, transportation, entertainment, education, healthcare, emergency response, disaster recovery, and the like. Technological advances and the low cost of such sensors enable deployment of large-scale camera networks in large metropolises such as London and New York. Multimedia algorithms for analyzing and drawing inferences from video and audio have also matured tremendously in recent times. Despite all these advances, large-scale reliable systems for media-rich sensor-based applications, often classified as situation-awareness applications, are yet to become commonplace. Why is that? There are several forces at work here. First, the system abstractions are just not at the right level for quickly prototyping such applications on a large scale. Second, while Moore's law has held true for predicting the growth of processing power, the volume of data that applications are called upon to handle is growing similarly, if not faster. Enormous amount of sensing data is continually generated for real-time analysis in such applications. Further, due to the very nature of the application domain, there are dynamic and demanding resource requirements for such analyses. The lack of right set of abstractions for programing such applications coupled with their data-intensive nature have hitherto made realizing reliable large-scale situation-awareness applications difficult. Incidentally, situation awareness is a very popular but ill-defined research area that has attracted researchers from many different fields. In this paper, we adopt a strong systems perspective and consider the components that are essential in realizing a fully functional situation-awareness system.
Year
DOI
Venue
2012
10.1109/JPROC.2011.2182093
Proceedings of the IEEE
Keywords
Field
DocType
large-scale situation awareness,health care,multimodal sensing,real-time analysis,large-scale camera network deployment,situation awareness,functional situation awareness system,video-based surveillance,sensing data,scalability,resource management,image sensors,ubiquitous computing,emergency response,ill-defined research area,cameras,programing model,large-scale reliable system,media-rich sensor-based application,resource requirement,moore law,data-intensive nature,multimedia communication,multimedia algorithm,disaster recovery,video surveillance,large-scale distributed systems,computer vision,intelligent sensors,real time,resource manager,intelligent sensor,programming model,real time systems
Resource management,Data science,Intelligent sensor,Computer science,Situation awareness,Computer security,Application domain,Ubiquitous computing,Disaster recovery,Moore's law,Scalability
Journal
Volume
Issue
ISSN
100
4
0018-9219
Citations 
PageRank 
References 
10
0.72
31
Authors
8
Name
Order
Citations
PageRank
Umakishore Ramachandran11071103.27
Kirak Hong221813.15
Liviu Iftode32112148.14
Ramesh Jain476301861.65
Rajnish Kumar522922.32
Kurt Rothermel62806450.84
JunSuk Shin71388.07
Raghupathy Sivakumar82679340.00