Multiple Information Agents for Real-Time, ISHM: Architectures for Real-Time Warfighter Support
James A. Crowder · AIAA Infotech@Aerospace 2010 · 2010
In the real-time battlefield arena, situational awareness becomes critical to making the right decisions and achieving the overall goals for the system. The key to Situational Awareness is not simply collecting and disseminating data, but it is actually getting the right information to the right users at the right time. In ground processing systems, various sensors, spacecraft, and other data sources gather and generate data different relevant contexts. What is required is an Integrated System Health Management (ISHM) processing architecture that allows users to turn the data into meaningful information, and to reason about that information in a context relative to the user at that time, and to update the information real-time as the situation changes. In short, it is imperative that the information processing environment be efficient, timely, and accurate. Described will be an Intelligent Information Agent processing environment which allows data to be processes into relevant, actionable knowledge. Based on the technologies described above, situational management is one of the most innovative components this processing systems. Utilizing the Artificial Cognitive Neural Framework (ACNF) (Crowder, 2005), it can provide real-time processing and display of dynamic, situational awareness information. I. Introduction Even in Service Oriented Architectures, true ISHM situational awareness is difficult because the enterprise has to become more aware, more flexible, and more agile than ever before. Information gathering, processing, and analyzing must be done continually to keep track of current trends in the context of the current situations, both local and overall, and provide timely and accurate knowledge to allow the users to anticipate and respond to what is happening in a changing environment. To achieve the combination of awareness, flexibility, and agility means supporting dynamic and flexible processes that adapt as situations change. This is possible with learning, evolving, Intelligent Information Agents, like those in the described here. The Data Steward Agents will support growing volumes of data and allow Reasoner Agents to produce accurate and relevant metrics about past, current, and future situations (prognostics). Through inter-agent communication, they provide control and visibility into the entire ground processing enterprise. This is made possible by integrating the processing environment into the flexible, distributed, Service Oriented Architecture (SOA) that enables secure collaboration, advanced information management, dynamic system updated, and customer, rule-based processes (Advisor Agents). The inter-agent communication allows shared awareness which, in turn, enables faster operations and more effective information analysis and transfer, providing users with an enhanced visualization of overall constellation and situational awareness across the ground processing system’s Enterprise Infrastructure. This Intelligent Agent-based system can deal with massive amounts of information to levels of accuracy, timeliness, and quality never before possible. Even applications that deal with object-oriented technologies fail to achieve the goals of awareness, flexibility, and agility because their processes are hard coded into the applications. The flexible, learning, adapting Intelligent Software Agents of the ACNF processing framework can adapt, collaborate, and provide the increased flexibility required in a growing, changing signal/source environment (Crowder, 2006).