Supporting ordinary home users to diagnose and resolve potential problems in their home wireless networks presents a significant opportunity to reduce support costs and increase user satisfaction. However the raw data necessary to identify even simple issues, such as a device being out of wireless range, require specific expertise to interpret. This paper introduces an approach for expert-derived semantic annotation of this raw data in order to allow end users to understand and resolve common network-related problems in real time. This approach demonstrates how semantic web technologies and visualization may be combined to satisfy high-level network monitoring requirements. This semantic approach, with causal reasoning, coupled with semantically-derived visualizations was implemented in a prototype home network monitoring system (HANMS). This paper describes the design decisions, implementation details and evaluation approach of HANMS.