Building on the first part of this work in the area of smart home monitoring, this second part presents a case study of the comprehensive architecture designed to identify anomalous events and issue alerts in smart home environments. Leveraging advances in artificial intelligence and heterogeneous data sources, the architecture addresses the critical need for real-time monitoring and response systems, particularly for vulnerable individuals such as the elderly living alone. The architecture includes various components, including data input handlers, event recognizers, analyzers, and communication channels, to provide a holistic home monitoring solution. To validate the adaptability and robustness of the architecture, the actions of an elderly person in their daily home life and potential events requiring attention when living alone are considered, focusing on scenarios involving potential health emergencies and unusual activities. The evaluation of the architecture spans different hardware configurations, demonstrating its scalability, stability, and efficient response times in different environments.