Abstract:
Safe Paths is a mobile-based application in which users can find the safest and the
shortest possible route. Safe Paths is a recommendation system that suggests users to
use the safest and the shortest path where the crime ratio low as compared to other
routes. A very large number of methods are used to provide the easiest and safest route
like google maps and other applications. However, not all the applications consider the
safest paths. The proposed project analyses information to enhance the security of the
people.
In the proposed application, we are using various techniques of Data Mining
and Machine Learning (ML) to analyse crime data and suggest the safest path. The
application is developed with the help of Android Java Native Framework and ML
Libraries. We have applied different ML techniques such as Linear Regression, K
Nearest Neighbour (KNN), Decision Tree, Naive Bayes and, Random Forest algorithm
on the dataset. Among all the algorithms, KNN has achieved the maximum accuracy
of 92%. The proposed application provides an efficient time-saving solution and
suggest the best route by predicting the crime rate for the safest and shortest path.
