Ubiquitous learning environments move learners out of a classroom and into the real world where learners engage in experiential and tangible learning involving instrumented physical things. Learners use peer-to-peer networks connecting learners, teachers, and a host of learning “things,” such as instrumented pieces of art, flower pots, and even buildings. A key component of such systems is wireless-enabled edge devices augmented with various types of sensors to represent the state of physical things and their context. This article presents a novel generic architecture for context-aware ubiquitous learning systems based on the Internet of Things (IoT) computing paradigm. A commonly used IoT edge device was used to implement four variants of the proposed architecture. The variants were based on advanced message queuing protocol, constrained application protocol (CoAP), message queue telemetry transport, and extensible messaging and presence protocol. All variants provided more than adequate performance for implementing ubiquitous learning scenarios. As expected, CoAP was generally more resource-efficient. However, practical differences in performance were so small that the choice of which architectural variant to use may depend on nonfunctional requirements such as reliability, security, maximum payload size, and ease of implementation.

中文翻译：

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用于无处不在上下文感知学习的通用物联网架构

无所不在的学习环境将学习者带出教室，进入现实世界，在这里，学习者可以进行涉及仪器物理事物的体验式和有形的学习。学习者使用点对点网络连接学习者，老师和许多学习“事物”，例如艺术品，花盆甚至建筑物。这种系统的关键组件是启用无线功能的边缘设备，该设备增加了各种类型的传感器以表示物理事物的状态及其上下文。本文提出了一种基于物联网（IoT）计算范例的，上下文相关的普适学习系统的通用架构。常用的物联网边缘设备用于实现所提议架构的四个变体。这些变体基于高级消息队列协议，约束应用程序协议（CoAP），消息队列遥测传输以及可扩展的消息传递和状态协议。所有变体都为实施无所不在的学习场景提供了足够的性能。不出所料，CoAP通常更节省资源。但是，性能上的实际差异很小，以致于选择使用哪种体系结构变体可能取决于非功能性要求，例如可靠性，安全性，最大有效负载大小和易于实现。