TRUSS: Tracking Risk with Ubiquitous Smart Sensing
Name
Paradiso_TRUSS tracking.pdf
Size
400.07 KB
Format
Adobe PDF
Checksum (MD5)
33fdba648db5d78e87c6258f3d360aec
Author(s)
Dublon, Gershon
Paradiso, Joseph A.
Mayton, Brian Dean
Palacios, Sebastian Ricardo
Date Issued
October 2012
Journal
2012 IEEE Sensors
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Mayton, Brian, Gershon Dublon, Sebastian Palacios, and Joseph A. Paradiso. “TRUSS: Tracking Risk with Ubiquitous Smart Sensing.” In 2012 IEEE Sensors, 1-4. Institute of Electrical and Electronics Engineers, 2012.
Version
Author's final manuscript
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.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Media Laboratory
Massachusetts Institute of Technology. Responsive Environments Group
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICSENS.2012.6411393
