tramoTDA: A trajectory monitoring system using Topological Data Analysis

Abstract

Due to the rapid proliferation of mobile devices and advanced tracking sensors, there is a significant increase in data production daily. In response, we have created tramoTDA, a Python library that uses Topological Data Analysis (TDA) to enable intuitive and visually-oriented classification of trajectory data. This tool offers a unique approach by focusing on the data’s topological properties, which enables the identification of subtle and critical patterns often missed by conventional methods. tramoTDA combines scientific rigor with user-friendly design, making it suitable for both technical and non-technical users in diverse applications such as urban planning and maritime navigation. Through its innovative use of TDA, tramoTDA not only enhances data interpretation but also facilitates new research opportunities in complex system analysis, positioning it as a pivotal resource in data science and analytics.

Keywords

• Topological Data Analysis
• Trajectory classification
• Spatial data visualization
• Urban planning