  This research proposes a method to detect alcohol consumption from
Near-Infra-Red (NIR) periocular eye images. The study focuses on determining
the effect of external factors such as alcohol on the Central Nervous System
(CNS). The goal is to analyse how this impacts on iris and pupil movements and
if it is possible to capture these changes with a standard iris NIR camera.
This paper proposes a novel Fused Capsule Network (F-CapsNet) to classify iris
NIR images taken under alcohol consumption subjects. The results show the
F-CapsNet algorithm can detect alcohol consumption in iris NIR images with an
accuracy of 92.3% using half of the parameters as the standard Capsule Network
algorithm. This work is a step forward in developing an automatic system to
estimate "Fitness for Duty" and prevent accidents due to alcohol consumption.
