Stream Data Classification in the Age of 5G Networks

该项目旨在开发一种新的流数据分类模型，以应对5G网络时代的挑战，例如流数据的范围，它们之间关系的复杂性，包含信息的多样性以及众多传感器的错误读数。该项目通过探索和建模流中数据实例之间更强的相关性来解决重大的知识差距。其结果是一个系统，是高效，准确和损坏的数据容忍分类解决方案，为个人流数据以及多个流数据。预期的好处将是广泛的，适用于许多领域，如智能家居，医疗保健，交通和制造业。

This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a system that is highly efficient, accurate and corrupted-data-tolerant classification solutions for individual stream data as well as multiple stream data. The expected benefits will be far-ranging and adaptable to many domains, such as smart home, medical and healthcare, transportation and manufacturing.