Integration of type-2 fuzzy logic and Dempster-Shafer Theory for accurate inference of IoT-based health-care system

Abstract The patient’s heterogeneous data in IoT-based healthcare system are gathered using various sensor nodes. the existing healthcare and monitoring systems are mostly based on ontology or type-1 fuzzy logic which is insufficient due to inconsistency and uncertainty in the sensed data. in this paper a novel data fusion scheme is proposed which is based on type-2 fuzzy logic (T2FL) incorporated with Dempster–Shafer theory (DST) to extract precise information and correctly infer the result. in the proposed scheme the membership values of the patient data are effectively decided by type-2 fuzzy logic, and the evidence obtained from the membership values are properly fused and processed by the DST in the decision-making system. extensive computer simulation with heart disease and diabetes dataset reveals that the proposed scheme considerably outperforms the existing schemes based on ontology and type-1 fuzzy logic with respect to the decision accuracy.

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