Data-Driven Intelligent Monitoring and Evaluation: A Multi-Industry Application Study

Abstract

 The growing complexity of modern engineering and management systems has made traditional monitoring and evaluation approaches increasingly inadequate. This chapter establishes a theoretical framework for data-driven intelligent monitoring and evaluation by examining how online monitoring, degradation assessment, and efficiency evaluation have evolved across industrial, transportation, healthcare, and management contexts. Rather than assuming a linear progression from diagnosis to prediction, the discussion acknowledges that methodological transfer across domains remains uneven and context-dependent. Existing studies often emphasize algorithmic performance while paying limited attention to data quality, sensor reliability, and institutional constraints. Considering these limitations, the chapter proposes a four-layer framework, monitoring, evaluation, prediction, and optimization, as a tentative organizing logic rather than a fixed prescription. Further research is needed to test whether such a framework can be generalized without losing sensitivity to domain-specific conditions.