| Situation Management is a rapidly developing science combining new techniques for data collection with advanced methods of data fusion to facilitate the process of situation awareness leading to correct decisions prescribing action. Current research focuses on reducing increasing amounts of diverse data to knowledge used by decision makers and on reducing time between observations, decisions and actions.
No new technology is more promising for increasing the diversity and fidelity of observations than sensor networks. New techniques are rapidly reducing size and cost of sensor motes that sense (or act), compute, and communicate under their own power. Low cost allows massive deployment, increasing the diversity and fidelity of observation. Small size enables unintrusive, inconspicuous deployment required for many situation management applications. However, current research focuses on centralized approaches modeled after conventional computer network architectures. We believe this trend will not realize the full potential of Situation Management.
We propose a new architecture modeled after biological ecosystems where motes are autonomous and intelligent, yet cooperate with local neighborhoods. Providing a layered approach, they sense and act independently when possible, cooperate with neighborhoods when necessary. The combination of their local actions results in global effects. We measure the success of our architecture by metrics of costs in time between observation and action, power consumption, and communication and in the mitigation of single point of failure compared with a more centralized approach.
While Situation Management research is currently dominated by military applications, advances envisioned for industrial and business applications have similar requirements. NASA has requirements for intelligent and autonomous systems in future missions that can benefit from advances in Situation Management. We describe requirements for the Integrated Vehicle Health Management program where our biology-inspired architecture provides a layered approach and decisions can be made at the proper level to reduce costs and improve efficiency in making diagnostic and prognostic assessments of the structural integrity, aerodynamic characteristics, and operation of aircraft. |