DocumentCode
2950255
Title
TRUSS: Tracking Risk with Ubiquitous Smart Sensing
Author
Mayton, Brian ; Dublon, G. ; Palacios, S. ; Paradiso, Joseph A.
Author_Institution
Responsive Environments Group, MIT Media Lab., Cambridge, MA, USA
fYear
2012
fDate
28-31 Oct. 2012
Firstpage
1
Lastpage
4
Abstract
We present TRUSS, or Tracking Risk with Ubiquitous Smart Sensing, a novel system that infers and renders safety context on construction sites by fusing data from wearable devices, distributed sensing infrastructure, and video. Wearables stream real-time levels of dangerous gases, dust, noise, light quality, altitude, and motion to base stations that synchronize the mobile devices, monitor the environment, and capture video. At the same time, low-power video collection and processing nodes track the workers as they move through the view of the cameras, identifying the tracks using information from the sensors. These processes together connect the context-mining wearable sensors to the video; information derived from the sensor data is used to highlight salient elements in the video stream. The augmented stream in turn provides users with better understanding of real-time risks, and supports informed decision-making. We tested our system in an initial deployment on an active construction site.
Keywords
computerised instrumentation; construction industry; data mining; safety systems; sensor fusion; sensors; video signal processing; TRUSS; altitude information; base stations; construction sites; context mining wearable sensor; dangerous gas; data fusion; distributed sensing infrastructure; dust information; light quality; motion information; noise information; risk tracking; ubiquitous smart sensing; video signal processing; wearable device; Base stations; Cameras; Safety; Sensor fusion; Streaming media; Tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Sensors, 2012 IEEE
Conference_Location
Taipei
ISSN
1930-0395
Print_ISBN
978-1-4577-1766-6
Electronic_ISBN
1930-0395
Type
conf
DOI
10.1109/ICSENS.2012.6411393
Filename
6411393
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