Implications for Asset Management in the Broadcasting Industry arising from Industrial Revolution 4.0
Ponnan R.1, Supramaniam M2, Abdullah A3

1Ramachandran Ponnan, School of Media and Communication, Taylors University.
2Mahadevan Subramaniam, Institute of Graduate Studies, SEGi University.
3Azween Abdullah, School of Computing and IT, Taylors University.
Manuscript received on 27 September 2019 | Revised Manuscript received on 06 October 2019 | Manuscript Published on 22 October 2019 | PP: 170-175 | Volume-8 Issue-3S October 2019 | Retrieval Number: C10301083S19/2019©BEIESP | DOI: 10.35940/ijrte.C1030.1083S19
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: The Industrial Revolution 4.0 and the Internet of Things pose numerous challenges for broadcasters in Malaysia. Archiving content and production workflow are critical in the transition to the digital environment. Issue of resource expansion and loss of opportunity among small and medium-sized broadcasters are a result of technological disruption at the advent of IR 4.0. Large amount of content requires digitisation following new quality control (QC) standards in the transition to digitalisation. In this exploratory study, a scalable media asset management (MAM) solution especially for small-scale content providers is proposed. The aim is to establish: (1) the challenges experienced by audio-visual archives, (2) metadata features for effective MAM processes and (3) efficiency among talents to facilitate large volume of transactions in the MAM workflow. In this qualitative research, face-to-face in-depth interviews with broadcasters, content providers and vendors at their respective premises and participant observation and content analysis were conducted at production operation centres and production houses to understand their issues. A compliance criteria model compatible to their workflow is proposed.
Keywords: Broadcasting Archives, Metadata, Machine Learning, and Media Asset Management.
Scope of the Article: Data Management