A Comparative Study of Rule-Based and Data-Driven Approaches in Industrial Monitoring

ArXi:2509.15848v2 Announce Type: replace Industrial monitoring systems, especially when deployed in Industry 4.0 environments, are experiencing a shift in paradigm from traditional rule-based architectures to data-driven approaches leveraging machine learning and artificial intelligence. This study presents a comparison between these two methodologies, analyzing their respective strengths, limitations, and application scenarios, and proposes a basic framework to evaluate their key properties.