Multimedia consumption has become a significant part of our everyday life due to the ability to view various types of content on many devices, such as mobile phones and computers. The rapid evolution of multimedia, such as 8K videos, presents new opportunities in various fields and applications, such as medical videos, security surveillance, and educational content. However, this development is accompanied by an increased demand for resources required to maintain satisfactory quality of service (QoS), thus increasing the power consumption required to process multimedia. The increased demands for resources and power required for multimedia streaming cause sustainability and economic challenges, which are crucial for the environment and many industries that rely on multimedia.

Our objective is to research and implement methods to empower sustainable multimedia. This is done by developing state-of-the-art AI-based methods to dynamically predict and allocate resources required in various multimedia streaming scenarios based on the application and the required quality of service, as well as developing algorithms designed using sustainable computing principles to lower the amount of resources required with minimal impact on the desired quality of service.