Summary

The benefits of using JIGSAW include:

Simple integration with other systems
Long life reliability (devices such as robots maintain themselves)
Self-calibration
Lower development and maintenance costs
Flexibility – works with a variety of data types

Uniqueness
Several years of search through scientific, commercial and patent literature has revealed that previous researchers have not realised the possibility of using signal content to derive spatial, adaptive mappings.

Scalability
JIGSAW is fully scalable in parallel configurations. It is linear in computational complexity, a rare and desirable property for any algorithm.

Assumptions
JIGSAW assumes only that there is a useful relationship between the similarity of two signals and the proximity of the two sensors that produce them. This is true for many phenomena: visual information, weather patterns, etc.

Limitations
The results of JIGSAW are determined by data signals. Data that does not contain sufficiently useful spatial clues will not produce clear results.