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Title: Modelling and simulation of AI-driven operation and maintenance processes: a case study in broadcasting systems

Authors: Ling Niu

Addresses: Wuwei Broadcasting Relay Station, Gansu Provincial Radio and Television Bureau, Wuwei 733000, China

Abstract: The conventional manual operation and maintenance mode has been challenging to satisfy the modern operation and maintenance needs in the radio and television sector as demand for equipment operation and maintenance efficiency and stability rises. This research thus suggests an intelligent operations and maintenance (O&M) system based on artificial intelligence (AI), hoping to increase the O&M efficiency and fault response capacity of broadcasting and television transmitters via four components. The method is based on discrete event simulation and LSTM data-driven modelling. The anomaly detection loop is implemented through isolation forest, and the large application possibility of the intelligent O&M system in terms of response timeliness and task scheduling efficiency is revealed by the trial findings. The experimental verification framework reduces response time by 38% and improves task scheduling efficiency by 42%, reflecting the value of cross domain simulation optimisation.

Keywords: AI-driven; intelligent operations and maintenance; broadcasting and television transmitters.

DOI: 10.1504/IJSPM.2025.150543

International Journal of Simulation and Process Modelling, 2025 Vol.22 No.3/4, pp.147 - 159

Received: 04 Jul 2025
Accepted: 15 Sep 2025
Published online: 16 Dec 2025 *