Adaptive awareness for personal and small group decision making.
Many situations call for the use of sensors monitoring physiological and environmental data. In order to use the large amounts of sensor data to affect decision making, we are coupling heterogeneous sensors with small, light-weight processors, other powerful computers, wireless communications, and embedded intelligent software. The result is an adaptive awareness and warning tool, which provides both situation awareness and personal awareness to individuals and teams. Central to this tool is a sensor-independent architecture, which combines both software agents and a reusable core software framework that manages the available hardware resources and provides services to the agents. Agents can recognize cues from the data, warn humans about situations, and act as decision-making aids. Within the agents, self-organizing maps (SOMs) are used to process physiological data in order to provide personal awareness. We have employed a novel clustering algorithm to train the SOM to discern individual body states and activities. This awareness tool has broad applicability to emergency teams, military squads, military medics, individual exercise and fitness monitoring, health monitoring for sick and elderly persons, and environmental monitoring in public places. This report discusses our hardware decisions, software framework, and a pilot awareness tool, which has been developed at Sandia National Laboratories.
- Research Organization:
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 918265
- Report Number(s):
- SAND2003-8701; TRN: US200818%%180
- Country of Publication:
- United States
- Language:
- English
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