This project is part of our course STMO and focuses on optimizing algorithms to design running routes in the city of Ghent. The goal is to create a tool that leverages geographical and algorithmic data to provide runners with customized routes that cater to their preferences and needs.
The project incorporates advanced graph algorithms, geographical data processing using the OSMNX library, and network analysis using NetworkX. The primary objective is to ensure that runners can find a good running route that is tailored to their specific distance training needs, whilst also taking into account specified points of interest.
Optimal Route Design: Develop and refine algorithms that compute the best running routes within Ghent.
User-Focused Features: Allow customization based on user preferences such as total distance and specific scenic values.
Data-Driven Decisions: Utilize real-world geographical data to inform and optimize route calculations.
We chose to focus on this project because running is a universally loved activity that promotes health and well-being. However, finding the right running route can often be a challenge for individuals who prioritize safety, distance accuracy, or aesthetics. By using Ghent as our pilot city, we aim to address this problem with a scalable solution that can later be expanded to other locations.
Our project not only combines our passion for running but also integrates our interest in leveraging technology to solve practical, real-world problems. The intersection of data science, geographical analysis, and user-focused design is what drives our enthusiasm for this initiative.
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Clone the repository from GitHub.
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Install the required dependencies listed in the requirements.txt file.
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Run the notebook with your own inputs like starting address and locations you are interested in, to generate a running route in Ghent.
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Visualize the suggested route and enjoy your run!