Abstract: This study systematically summarizes the key characteristics, core functionalities, paradigm shifts, significance, and implementation strategies of smart infectious disease surveillance and early warning systems. The research identifies four key characteristics of smart construction: systemic optimization, data-driven approaches, deep integration of next-generation information technologies, and city-based implementation as the fundamental unit. The system is designed to perform six critical functions: intelligent multi-source data collection, multimodal data governance, multi-trigger early warning, epidemic trend forecasting, intelligent decision support, and visualization platform display. These features drive comprehensive transformations, including shifts from single to multi-source data, passive to active surveillance, early signal detection to risk-based assessment, and experience-driven to precision-based approaches. The study further proposes implementation strategies such as embedding the system into smart city governance frameworks, promoting cross-departmental data standardization, cultivating interdisciplinary talent, and strengthening data security and ethical safeguards. These insights provide theoretical guidance for developing smart, efficient, resilient, and sustainable infectious disease surveillance and early warning systems.