AI 中文总结
针对物联网中异构设备语义和数据格式不同导致通信难的问题，提出中间件解决方案，含消息句法翻译、语义互操作性框架及特征提取算法，经评估，MLP确定消息属性标准含义的总体分类准确率达95.78%。
AI 中文摘要
随着物联网需求增长，异构物联网设备与网络间需无缝可靠通信。本文提出物联网网络发布-订阅框架中统一语义和句法互操作性的中间件解决方案。先提出消息句法翻译新方法解决用户与设备句法差异，再提出基于多层感知器的语义互操作性框架及提取特征算法。通过评估不同参数验证其有效性，MLP确定消息属性标准含义的总体分类准确率达95.78%。
英文摘要
With the growing demand of Internet of Things (IoT), there is a need for seamless and reliable communication between heterogeneous IoT devices and the cyber-world to ensure autonomous control over any application process. More specifically, seamless communication requires interoperability between heterogeneous devices (actors) having different semantics and data formats (syntaxes), while making it more challenging. In this paper, we propose a middleware solution for unified semantic and syntactic interoperability in the publisher-subscriber framework of IoT network. The proposed framework automatically translates the subscribers (users) compatible syntax and semantics of the receiver message from the publishers (IoT devices). First, we propose a novel method of syntax translation of messages, to solve the syntactic disparities between users and devices, while providing the information in the user requested syntax. Thereafter, a multilayer perceptron (MLP)-based semantic interoperability framework is proposed to translate the device information to the user requested semantics. Additionally, a novel algorithm is proposed for extracting raw and discriminative features, which are to be fitted to the MLP model as inputs. To show the effectiveness of the proposed middleware, we evaluate different parameters, while considering various publicly used data formats and semantic annotations of attributes to ensure the versatility of the proposed middleware in the practical scenario. The overall classification accuracy using MLP is $95.78$\% for determining the standard meaning of each attribute of the incoming message from the publisher to address the semantic interoperability problem in IoT.
