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OT data governance refers to the systematic management, standardization, and quality control of data generated from industrial operations, ensuring it can effectively support enterprise decision-making and AI applications. It covers the end-to-end process—from data acquisition, format transformation, quality validation, and access control to storage and downstream usage. Unlike IT data governance, OT data governance must account for diverse equipment communication protocols, complex data types, real-time operational requirements, data security, and the constraints of edge computing environments.

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!