Bulletin of Emerging AI and Media Broadcasting (BEAM)

The Bulletin of Emerging AI and Media Broadcasting (BEAM) is an international, peer-reviewed journal dedicated to navigating the seismic shifts within the global media landscape. As the boundaries between terrestrial digital content, generative AI, and decentralized streaming architectures converge, BEAM serves as a high-impact scholarly platform for the dissemination of transformative scientific discoveries.

The mission of BEAM is to illuminate the trajectory of digital transmission through rigorous empirical research and methodological excellence. We posit that contemporary broadcasting has transcended unidirectional dissemination, evolving into an interactive, AI-enhanced dialogue between creators and global consumers.

By championing Orange Technologies' innovations that harmonize human creativity with emotional resonance, BEAM ensures that the future of media remains authentic, culturally vibrant, and ethically grounded. Our vision is to facilitate the technical and creative synchronization requisite for a resilient and innovative media ecosystem.

Important Information for Authors

Authors are strictly advised to utilize the Official BEAM Submission System for all manuscript uploads; submissions via email, telephone, or unauthorized third-party intermediaries will be summarily rejected. Neither BEAM nor its publisher, Pandawan Sejahtera Indonesia, assumes liability for papers submitted through unofficial channels. Before submission, authors must meticulously align their manuscripts with the Publication Ethics and Duties of Authors guidelines to ensure compliance with the rigorous standards of the international environment. All accepted research will be published under an open-access model, ensuring immediate global visibility and seamless integration into abstracting and indexing databases.

Call for Contributions: V2N2 November 2026

As we approach the V2N2 November 2026 issue, BEAM invites scholars, engineers, and media theorists to join the broadcast. We solicit bold, interdisciplinary manuscripts that challenge conventional boundaries, ranging from the optimization of signal processing algorithms to the socio-technical impacts of AI-driven storytelling.

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