Rule Conflict Classification and Detection for Smart Building Systems: A Case Study

With the rapid development of rule engine-based smart building systems, it is urgent to address the potential conflicts between different control rules to ensure system usability and reliability. For this end, this paper proposed a rule conflict detection approach based on the statistical model checking technique. Firstly, it presented a conflict taxonomy for smart building rules, systematically considering conflicts between different rules, and rule conflicts against system invariant constraints. Then, it proposed depicting smart building control rules, dynamic trigger sources and actuators with the NPTA (Network of Priced Timed Automata for short) model, and specifying rule conflicts with temporal logic. Finally, it proposed carrying out conflict detection with the statistical model checking technique based on the above formal model and formal specification. To validate the effectiveness of this approach, we carried out a case study on a superstore ventilation and air conditioning system, and demonstrated the rule conflict detection processes of 8 types of rule conflicts. The results demonstrate that the proposed approach can explicitly depict smart building rule interactions, and can effectively diagnose and detect rule conflicts, ensuring usability and reliability of the rule-based smart building control rules.