@Article{cmc.2021.018128,
AUTHOR = {Isha Puthige, Kartikay Bansal, Chahat Bindra, Mahekk Kapur, Dilbag Singh, Vipul Kumar Mishra, Apeksha Aggarwal, Jinhee Lee, Byeong-Gwon Kang, Yunyoung Nam, Reham R. Mostafa},
TITLE = {Safest Route Detection <i>via</i> Danger Index Calculation and K-Means Clustering},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {69},
YEAR = {2021},
NUMBER = {2},
PAGES = {2761--2777},
URL = {http://www.techscience.com/cmc/v69n2/43879},
ISSN = {1546-2226},
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.},
DOI = {10.32604/cmc.2021.018128}
}