We propose the hierarchical behavior suggestion system and recovery mechanism for the smart home management platform, including location layer, action layer, and home appliance layer. The smart home management system uses the hierarchical structure to take regional management action and home appliance management action. This study also provides a hierarchical human behavior suggestion algorithm (HHBSA), which suggests the behavior pattern. HHBSA includes a location–learning suggestion algorithm (LLSA) and an action–behavior suggestion algorithm (ABSA). LLSA suggests the user's location with the concepts of Q-learning and fuzzy-state Q-learning (FSQL). ABSA provides advices on regional behaviors according to the suggested regional sequence updated by users' location. The home appliances included in the behaviors can be switched on in advance when the behaviors have been suggested. A hierarchical recovery mechanism may be used to correct the errors occurring when starting the home appliances. The home appliances can be re-started when errors occur if the action layer is set as a recovery point that can be changed according to the usage sequence. A dynamic recovery point makes it possible to unlimitedly add behaviors to the system, and to maintain the efficiency of a recovery mechanism.
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