Using evolutionary techniques to improve the multisensor fusion of environmental measurements

Within the environmental sciences, the ability to accurately collate, combine and present data from various sensors is important to validate research. Whilst measuring data from a single sensor is a standard practice, fusing the output of more than one sensor can be a complicated and computationally intensive process. Outlined is a brief introduction to the art of multisensor fusion and a suggestion that fusion optimisation and analysis could be improved with the use of evolutionary techniques common within the field of artificial intelligence. Evolutionary techniques are used in a wide array of research areas, but their application and initial parameter settings are often unique to the specific task at hand.