On Exploiting Structured Human Interactions to Enhance Sensing Accuracy in Cyber-physical Systems

Abstract

In this article, we describe a general methodology for enhancing sensing accuracy in cyber-physical systems that involve structured human interactions in noisy physical environment. We define structured human interactions as domain-specific workflow. A novel workflow-aware sensing model is proposed to jointly correct unreliable sensor data and keep track of states in a workflow. We also propose a new inference algorithm to handle cases with partially known states and objects as supervision. Our model is evaluated with extensive simulations. As a concrete application, we develop a novel log service called Emergency Transcriber , which can automatically document operational procedures followed by teams of first responders in emergency response scenarios. Evaluation shows that our system has significant improvement over commercial off-the-shelf (COTS) sensors and keeps track of workflow states with high accuracy in noisy physical environment.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 24, 2017
Source ID
10.1145/3064006

Entities

People

  • Hongwei Wang
  • Lu Su
  • Lui R. Sha
  • Minje Kim
  • Poliang Wu
  • Renato Mancuso
  • Shaohan Hu
  • Shiguang Wang
  • Tarek Abdelzaher
  • Yunlong Gao

Organizations

  • Defense Threat Reduction Agency
  • IBM Research
  • Indiana University
  • National Science Foundation
  • University at Buffalo
  • University of Illinois Urbana–Champaign

Tags

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Emergency Management and Homeland Security.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Cyber