Foundations of Data Fusion for Automation*
Data fusion is a paradigm for integrating data from multiple sources to synthesize new information such that the whole is greater than the sum of its parts. This is a critical task in contemporary and future systems that are distributed networks of low-cost, resource-constrained sensors [1,2]. Current techniques for data fusion are based on general principles of distributed systems and rely on cohesive data representations to integrate multiple sources of data. Such methods do not extend easily to systems in which real-time data must be gathered periodically, by cooperative sensors, where some decisions become more critical than other decisions episodically.