@inproceedings{364,
  keywords = {activity patterns, computational engineering, decision support systems, ergonomics, geographic information systems, geographic position, health and safety, human protection, individual decision support, individual human context, quick forecasting, situational awareness, state patterns},
  author = {Justyna Zander and Piter Mosterman and John Kinnebrew and Gautam Biswas},
  title = {Computation of things for human protection and fulfillment},
  abstract = {Computer science and computational engineering have enabled great advances in modeling and simulation to analyze various scenarios. Still, facilitating and enhancing situational awareness for a single human is rarely considered. Poor decisions by an individual encountering everyday challenges or public threat situations can have dramatic effects, both for the individual and others. In the presented research, a Computation of Things (CoTh) framework is proposed to provide individual decision support during crises and prevent long-term deviations from safe and secure conditions. The target of CoTh is to enable a profound understanding of the situation from the viewpoint of individual persons in order to permanently reduce their fear, while simultaneously increasing awareness of appropriate responses. CoTh allows for a quick forecasting of action (or non-action) alternatives based on an individual human context, including geographic position (e.g., pollution level and energy usage), activity patterns (e.g., personal nutrition habits, lifestyle, traveling load, family status, circle of friends, social network, and virtual life), and state patterns (e.g., the DNA, current health conditions, and musculature of a human), depending on the considered situation. Insights into CoTh's motivation, requirements, and challenges are provided and the architecture proposal is depicted.},
  year = {2010},
  journal = {Technologies for Homeland Security (HST), 2010 IEEE International Conference on},
  pages = {153 -159},
  month = {11/2010},
  address = {Waltham, MA},
}