Open Access

ARTICLE

Safest Route Detection via Danger Index Calculation and K-Means Clustering

Isha Puthige¹, Kartikay Bansal¹, Chahat Bindra¹, Mahekk Kapur¹, Dilbag Singh¹, Vipul Kumar Mishra¹, Apeksha Aggarwal¹, Jinhee Lee², Byeong-Gwon Kang², Yunyoung Nam^2,*, Reham R. Mostafa³

1 School of Engineering and Applied Sciences, Bennett University, Greater Noida, India
2 Department of ICT Convergence, Soonchunhyang University, Asan, Korea
3 Department of Information Systems, Faculty of Computers and Information Sciences, Mansoura University, Mansoura, Egypt

* Corresponding Author: Yunyoung Nam. Email:

(This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)

Computers, Materials & Continua 2021, 69(2), 2761-2777. https://doi.org/10.32604/cmc.2021.018128

Received 26 February 2021; Accepted 24 April 2021; Issue published 21 July 2021

Abstract

The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations. Using the New York City dataset, which provides us with location tagged crime statistics; we are implementing different clustering algorithms and analysed the results comparatively to discover the best-suited one. The results unveil the fact that the K-Means algorithm best suits for our needs and delivered the best results. Moreover, a comparative analysis has been performed among various clustering techniques to obtain best results. we compared all the achieved results and using the conclusions we have developed a user-friendly application to provide safe route to users. The successful implementation would hopefully aid us to curb the ever-increasing crime rates; as it aims to provide the user with a before-hand knowledge of the route they are about to take. A warning that the path is marked high on danger index would convey the basic hint for the user to decide which path to prefer. Thus, addressing a social problem which needs to be eradicated from our modern era.

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Keywords

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