Cost effective localization in distributed sensory networks

Engineering Applications of Artificial Intelligence

24

2

2010

10.1016/j.engappai.2010.10.006

Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 4.0) https://creativecommons.org/licenses/by-nc-nd/4.0/ Permission granted to the University of West Florida Libraries to digitize and/or display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires the permission of the copyright holder.

The most important mechanism to occur in biological distributed sensory networks (DSNs) is called lateral inhibition, (LI). LI relies on one simple principle. Each sensor strives to suppress its neighbors in proportion to its own excitation. In this study, LI mechanism is exploited to localize the unknown position of a light source that illuminated the photosensitive sensory network containing high and low quality sensors. Each photosensitive sensor was then calibrated to accurately read the distance to the light source. A series of experiments were conducted employing both quality sensors. Low quality array was allowed to take advantage of LI, whereas the high quality one was not. Results showed that the lateral inhibition mechanism increased the sensitivity of inferior quality sensors, giving the ability to make the localization as sensitive as high quality sensors do. This suggests that the networks with multitude of sensors could be made cost-effective, were these sensory networks equipped with LI.

Artificial intelligence
Localization
Distributed sensory networks
Lateral inhibition

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