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
Link To Document :
بازگشت