tramoTDA: A trajectory monitoring system using Topological Data Analysis

被引:0
|
作者
Esteve, Miriam [1 ]
Falco, Antonio [1 ]
机构
[1] CEU Univ, Univ Cardenal Herrera CEU, Dept Matemat Fis & Ciencias Tecnol, Valencia, Spain
关键词
Topological Data Analysis; Trajectory classification; Spatial data visualization; Urban planning;
D O I
10.1016/j.softx.2024.101953
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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 userfriendly 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.
引用
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页数:8
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