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OT數據治理是指針對工業現場產生的各類資料進行有系統的管理、標準化與品質控管，使之能夠有效支援企業決策與AI應用。它涵蓋從數據取得、格式轉換、品質檢查、權限控管、存取機制到後續的儲存與應用等整體流程。與IT數據治理不同，OT數據治理需考量設備通訊協議多樣性、數據型態複雜性、即時性要求、資料安全與邊緣運算能力等挑戰。

This white paper helps readers evaluate AIoT platforms from four key security perspectives, covering design and deployment requirements. It explains how to build a secure edge AIoT architecture using international standards (e.g., ISO 27017, IEC 62443), encrypted communication, secure hardware modules, and remote access control. The goal is to select a platform capable of prevention, defense, monitoring, and traceability—empowering businesses to digitally transform while mitigating growing cybersecurity threats.

In the era of rapid IoT and AI growth, many devices are underutilized. Edge orchestration platforms solve this challenge by enabling centralized edge device management and local data processing. Real-time analytics improve operational efficiency, reduce cloud transmission costs, and enhance data security—ultimately improving user experience. Download our white paper to explore the limitless potential!