SafeRoute-A Comprehensive Travel Solution

Travel safety is a critical concern for individuals navigating urban environments, especially in areas prone to crime or high-risk incidents. Traditional navigation systems primarily focus on the shortest or fastest routes, often neglecting security considerations. This research explores the integration of safety-based routing mechanisms to enhance secure travel experiences. By analyzing existing safe route guidance systems, crime data integration, and predictive modelling for high-risk areas, this study aims to develop an intelligent travel safety framework. The research examines multiple factors influencing safe navigation, including crime hotspots, real-time traffic conditions, environmental factors, and user-generated data. The findings suggest that a hybrid approach combining real-time data analyzis, historical crime trends, and AI-driven route optimization can significantly improve travel security. This study contributes to the development of a comprehensive Safe Route Navigation System, enhancing personal security and informed decision-making for travellers. Keywords— Safe route, crime data, Safe Route Navigation System, Safe Route Guidance System (SRGS), Crowd-sourcing, Intelligent Transportation Systems (ITS), Safe Path Algorithm using Feedback and Environment (SPaFE), MultiAttribute Decision Making (MADM)

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-23
DOI
https://doi.org/10.5281/zenodo.15531003
Primary Topic
Medical Image Segmentation Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

SafeRoute-A Comprehensive Travel Solution

Zenodo (CERN European Organization for Nuclear Research)
Medical Image Segmentation Techniques
article

SafeRoute-A Comprehensive Travel Solution

article en

Abstract

Travel safety is a critical concern for individuals navigating urban environments, especially in areas prone to crime or high-risk incidents. Traditional navigation systems primarily focus on the shortest or fastest routes, often neglecting security considerations. This research explores the integration of safety-based routing mechanisms to enhance secure travel experiences. By analyzing existing safe route guidance systems, crime data integration, and predictive modelling for high-risk areas, this study aims to develop an intelligent travel safety framework. The research examines multiple factors influencing safe navigation, including crime hotspots, real-time traffic conditions, environmental factors, and user-generated data. The findings suggest that a hybrid approach combining real-time data analyzis, historical crime trends, and AI-driven route optimization can significantly improve travel security. This study contributes to the development of a comprehensive Safe Route Navigation System, enhancing personal security and informed decision-making for travellers. Keywords— Safe route, crime data, Safe Route Navigation System, Safe Route Guidance System (SRGS), Crowd-sourcing, Intelligent Transportation Systems (ITS), Safe Path Algorithm using Feedback and Environment (SPaFE), MultiAttribute Decision Making (MADM)

Zenodo (CERN European Organization for Nuclear Research)
Amal Jyothi College of Engineering
Sustainable cities and communities
Openalex Percentile: Top 54%
Medical Image Segmentation Techniques
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SafeRoute-A Comprehensive Travel Solution · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS