A Framework for Automated Digital Media Asset Acquisition using Cloud

This paper presents a cloud-based automated media asset acquisition framework designed to enhance the efficiency and speed of media ingest workflows in broadcast environments. Traditional media ingestion, particularly in news production, often involves manual processes such as physical file transfers, operator intervention, and transcoding delays, which can slow down content availability. Our proposed framework leverages cloud storage, mobile journalism technology, and automation scripts to eliminate these inefficiencies. By developing a dedicated mobile application, integrating cloud storage with automated monitoring and downloading mechanisms, and employing a local watchfolder-based transcoding system, the workflow minimizes human intervention and significantly reduces media ingest time. We conducted a series of comparative real-world experiments evaluating the new framework against conventional workflows in a news television station, measuring ingest time and resource utilization. The results demonstrate that our automated solution outperforms traditional and alternative cloud-based methods, reducing ingest time by up to fifteen times while eliminating the need for additional personnel. These findings highlight the potential of automation and cloud computing to optimize media workflows, ultimately improving production speed and operational efficiency which can also lead to potential economic benefits.