HumSafar: An Android app enabling a safer way to travel

Arora, Moni; Kaushik, Nisha; Jain, Tanya; Kaur, Baljeet; Vashisth, Pooja; Khosla, Kamakshi; Bhatia, Sangeeta

doi:10.1109/pdgc.2016.7913204

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…A solution totally based on sexual-crime assault [28], which marked the hotspots [29] in the regions, seemed effective but extremely constrained. HumSafar [30], instead of countering the problem, suggested the pooling system in the transport system for more security which at some scope, further increases the crime possibilities. Thus, these models gave us some benchmarks but no workable solution to counter the problem.…”

Section: Related Workmentioning

confidence: 99%

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

Puthige¹,

Bansal²,

Bindra³

et al. 2021

Computers, Materials &Amp; Continua

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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 beforehand 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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Section: Related Workmentioning

confidence: 99%

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

Puthige¹,

Bansal²,

Bindra³

et al. 2021

Computers, Materials &Amp; Continua

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“…al. [11] have studied about the development of an open street map based safe zone routing system. This system recommends the optimal route to the safest zone using a map interface.…”

Section: Literaturementioning

confidence: 99%

Geographical Information System Based Safe Path Recommender

Jain¹,

Kumar²,

Parashar³

et al. 2019

IJITEE

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The threat to women safety, especially on road, has become a major concern these days and the problem is increasing dramatically. Women are unsafe not just in the night but also in the day, they fear getting assaulted not only in public transport but also while travelling in cars and two-wheelers. People are harassed on road in various ways like robberies, killings, etc., but women go through even bigger traumas. Cases like, rape in moving cars, sexual assault and robberies by forcefully stopping the vehicle, teasing women on two-wheelers, etc. have increased to an alarming level. This study is an initiative to safe-guard the self-esteem of our women and prevent them from any ugly experience, while on road. It aims to find and suggest the safest path for women and tells the level of crime of the locations in that path, while travelling from one place to another. The system determines the various paths from source to destination, as entered by the user on the map interface, by calculating the danger index. This index is found on the basis of the crime rate of the grouped locations. These locations are grouped by clustering them on the basis of the crime history of that location. The app as a result suggests the best three paths in different colours (Green, Red, Yellow).

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