OLED-EQ: A Dataset for Assessing Video Quality and Energy Consumption in OLED TVs Across Varying Brightness Levels

The climate crisis has highlighted the environmental impact of information and communication technologies (ICT), underscoring the need for sustainable solutions to reduce carbon emissions from ICT. As video streaming continues to dominate Internet traffic, research in this field has become increasingly important. The energy consumption of OLED TVs relies on the video brightness. Thus, an approach to optimized the energy consumption is reducing the video brightness. In this work, we provide an open dataset for energy consumption in OLED TVs while playing videos with various brightness levels. The dataset comprises the energy data of four OLED TVs with different screen sizes and manufacturers in playing 176 videos in a range of dark and bright content. As results, 704 data traces of energy consumption are collected.We also conduct a subjective test to assess the quality of videos displayed in OLED TVs when they are reduced the brightness. Ten levels of brightness reduction are investigated four different video bitrates and video characteristics. The rating scores are attached to our dataset so that they can be used to develop QoE prediction models in the context of the tradeoff between energy consumption and video brightness. We collected opinion scores from 28 participants, resulting in 2240 responses in total. The dataset is available at https://github.com/minhkstn/OLED-EQ.