Trafile monitoring is a challenging task that has been addressed by various research studies in recent years, especially for large networks. However, fewer studies have been conducted on home networks. In this paper, we tackle trafile monitoring issue in home networks focusing on anomaly detection use case. In fact, home networks are observing a continuous increase of complexity lead by the introduction of multiple devices, connectivity technologies and services. Therefore, efficient tools allowing to improve the troubleshooting process are needed. Moreover, security and anomaly detection are of high importance in this context. From an ISP point of view, it allows to reduce help-desk costs and to have a better insight on home network performance. On the other hand, for customers, it improves QoE while mitigating attacks risks. Within Acemind European research project, we propose a flow monitoring solution enriched with an anomaly detection system based on FlowMon components. We show its feasibility and efficiency on an experimental testbed using real home network devices.