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Principal Investigators:

• Moises Sudit (UB)
• Andrew Feldman (JHU-APL)

Investigators:

• Jacqueline Cattani (USF)
• Michael Moskal (CUBRC)

Project Objectives:

The high level objective of the proposed research is to investigate and provide a proof-of-concept demonstration of how to approach the Biosensor Fusion process as a Systems Optimization. Recent work on Biosensor Fusion is disjointed and compartmentalize at each technical challenge of a very complex problem. For example the Biosensor designers might not consider the communication bandwidth issues and fusion algorithms might not take into account the human decision-makers processing limitations.

Utilize a systems approach to analyze the following questions:

• Where to locate sensors?
• What sensors to locate?
• How to configure sensors?
• When to locate the sensors or extract the data?

The answer to each of these questions will be done by trying to consider all aspects of the Fusion process.

Project Summary & Planned Activities:

Planned activities will focus on the following two areas:

Biosensor Ontology:

To study the overall performance of a Biosensor system we will study in depth capabilities of the sensor suite, which will enable us to develop more meaningful and useful fusion algorithms to aid the decision makers.

Mathematical Model:

We will develop a mathematical model that will maximize the different dynamic variables of sensors (i.e. where to locate, how to configure, when to extract) subject to a number of constraints. This process will take into account a number of conflicting system requirements that need to work together to attain a solution that will satisfy a multi-criteria decision-making process.

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