Sensor fusion

A formal definition of Information Fusion, according to International Society of Information Fusion (ISIF), is

“Information fusion is the synergistic integration of information from different sources about the behavior of a particular system, to support decisions and actions relating to the system. Information fusion includes theory, techniques and tools for exploiting the synergy in the information acquired from multiple sources, for example sensors observing system behavior, databases storing knowledge about previous behavior, simulations predicting future behavior and information gathered by humans.”

Instead, the problem of Information Fusion, from a practical point of view, is explained as follows:
“We are drowning in information but starved for knowledge. This level of information is clearly impossible to be handled by present means. Uncontrolled and unorganized information is no longer a resource in an information society, instead it becomes the enemy.”
Information Fusion has recently gained attention as a widespread tool for a systematic analysis/design of several practical systems, such as:

  • Wireless Sensor Networks systems for surveillance tasks;
  • Cognitive Radio Networks for spectrum holes exploitation;
  • Multi-Sensor Multi-target tracking systems, through the use of several and multi-modalities sensors;
  • Enhanced Bio-medical systems, for effective healthcare assurance.

The classical models and algorithms derived in the single-source of information case need a re-thinking in the case of multi-dimensional (and possibly) heterogeneous observations coming from different sensors, typically distributed in a wide geographical area. In fact, this undefinite growth of available information poses the serious problem of the “curse of dimensionality“, thus affecting the scaling property of such complex systems. Therefore Information Fusion represents a cross-layer (w.r.t. the specific application and/or discipline) framework for enhancing, through an equal-balance between theoretical results and ready-to-implement practical (fusion) algorithms, the performance of such systems, while keeping the complexity under control.

Relevant Publications:

[J-3], [J-4], [J-7], [J-8], [J-9];

[C-8], [C-14], [C-15];


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