Towards Continuous Monitoring of Environment under Uncertainty: A Fuzzy Granular Decision Tree Approach

Smart monitoring of environment has been an essential area of research where decision-making process is inevitable. Reliability of the whole system depends on the stability and consistency of its decision-making unit. Real-time decision making is another challenge in the field on which the research community has been focusing on improving the performance of the underlying models. The underlying models are usually the learning models, that act as a smart engine after being sufficiently trained for the process. In this paper, we propose to use a decision tree model that has the capability of handling uncertainty in the acquired data from the environment. The resulting model is called as Fuzzy Granular Decision Tree (FGDT). Series of evaluation of FGDT shows that the model is stable and powerful for the presently considered problem.