The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing.
One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security,
battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3
requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to:
computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g.,
centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and
global data/information fusion scheme for situational awareness. Although, many models have been proposed to address
one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information
fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks.
In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for
LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared
to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different
levels of fusion and different applications.