Multiple conformance to hybrid-automata-modelled requirements for detecting indoor temperature anomalies

Abstract

Detections of different thermal problems resort to approaches that utilize different indices, respectively. From an engineering viewpoint, they are neither flexible in detecting multiple thermal problems nor flexible in dealing with new concerned thermal problems. This article proposes a multiple-conformance approach to requirements that modelled by hybrid automata for flexibly detecting temperature anomalies. Temperature anomalies could lead to thermal problems, i.e., thermal discomfort as well as serious health problems. This approach extended a conventional conformance approach. The flexibility of the proposal is reflected in two aspects. First, it is an integrated approach that can deal with multiple thermal problems at different states of hybrid automata. Second, we can devise conformance relations concerning new thermal problems, and add them to the multiple-conformance approach. Experimental results show the feasibility and high performance of our proposal in detecting indoor temperature anomalies comprehensively.