What if digital interfaces could assess our daily screen time by analyzing the impacts of HEV light on our facial features?

(Prototype in development), Python, OpenCV
Image Credits: Thomas Leveritt UV series

Original image by Thomas Leveritt UV series, (Number of UV marks on face undetermined).

The skin is “a border that feels, providing an effective opening to the bodies of others.” Its dual capacity as both protector and mediator positions it as a living record of our interactions with the environment.

This project translates that narrative into a digital context, exploring the relationship between the skin’s physical barrier and the digital realm. Using a UV-sensitised photograph as a base, the prototype employs Python and OpenCV libraries to detect and visualise UV marks—traces of the skin’s defence against environmental exposure.

By applying edge detection, thresholding, and contour detection, the model uncovers previously invisible markers, demonstrating the potential for machine learning to encode and reveal these interactions. As a prototype in development, this work positions the skin as a site of encryption—decoding the impact of screen time and UV exposure while provoking conversation about how physical and digital systems converge. It invites reflection on the skin’s ability to serve as both a boundary and a bridge, translating lived experiences into tangible, visual data.

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