Isha Otero*
Anaerobic reactors play a crucial role in various industrial and environmental applications, such as wastewater treatment and biogas production. To ensure their efficient and uninterrupted operation, condition-based maintenance is essential. This paper presents an AI-enhanced predictive maintenance approach for anaerobic reactors, which leverages artificial intelligence and machine learning techniques to monitor and optimize reactor performance. By analysing real-time sensor data and historical operational information, the proposed system can predict potential issues, schedule maintenance activities and enhance the overall reliability and performance of anaerobic reactors. This research contributes to the sustainability of anaerobic processes and offers a cost-effective solution for ensuring optimal operation.
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