Cities function as interconnected ecosystems where various systems like transportation and energy are dynamically linked. Understanding Local Digital Twins (LDTs) requires a structured approach to encapsulate this complexity. The challenge lies in moving beyond viewing LDTs as singular entities to appreciating their architecture composed of interoperable, distributed systems. The solution is the fi ve-layer architecture framework that deconstructs LDTs into Physical, Data Sensing, Data Transmission, Virtual, and Application layers. This model clarifi es LDT complexity while highlighting how these layers interact to create dynamic digital systems capable of real-time simulation, adaptation, and optimization. This microlearning unit, TEC-102, teaches the fi ve-layer architecture through an examination of each layer’s function and interconnectivity. Learners discover how layers collaborate to maintain accurate digital simulations, enabling decision-support and refl ecting physical systems. This structured insight empowers learners to design and improve LDTs effectively within their own contexts.