  The share of online video traffic in global carbon dioxide emissions is
growing steadily. To comply with the demand for video media, dedicated
compression techniques are continuously optimized, but at the expense of
increasingly higher computational demands and thus rising energy consumption at
the video encoder side. In order to find the best trade-off between compression
and energy consumption, modeling encoding energy for a wide range of encoding
parameters is crucial. We propose an encoding time and energy model for SVT-AV1
based on empirical relations between the encoding time and video parameters as
well as encoder configurations. Furthermore, we model the influence of video
content by established content descriptors such as spatial and temporal
information. We then use the predicted encoding time to estimate the required
energy demand and achieve a prediction error of 19.6 % for encoding time and
20.9 % for encoding energy.
