  This paper focuses on Crime zone Identification. Then, it clarifies how we
conducted the Belief Rule Base algorithm to produce interesting frequent
patterns for crime hotspots. The paper also shows how we used an expert system
to forecast potential types of crime. In order to further analyze the crime
datasets, the paper introduces an analysis study by combining our findings of
the Chittagong crime dataset with demographic information to capture factors
that could affect neighborhood safety. The results of this solution could be
used to raise awareness of the dangerous locations and to help agencies predict
future crimes at a specific location in a given time.
