Detection and Analysis of Anomalies in People Density and Mobility Through Wireless Smartphone Tracking

被引：4

作者：

Fernandez-Ares, A. ^{[1
]}

Garcia-Sanchez, P. ^{[2
]}

Arenas, M. G. ^{[3
]}

Mora, A. M. ^{[1
]}

Castillo-Valdivieso, P. A. ^{[3
]}

机构：

[1] Univ Granada, ETSIIT, Dept Signal Theory Telemat & Commun, Granada 18010, Spain

[2] Univ Cadiz, Dept Comp Sci & Engn, Cadiz 11519, Spain

[3] Univ Granada, Dept Comp Architecture & Comp Technol, Granada 18010, Spain

来源：

IEEE ACCESS | 2020年 / 8卷

关键词：

Anomaly detection; device tracking; crowd analysis; smart cities; smart devices; people monitoring; wireless communications; TIME-SERIES; OUTLIER DETECTION; UNIT-ROOT; SYSTEM;

D O I：

10.1109/ACCESS.2020.2979367

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

One of the challenges of this century is to use the data that a smart-city provides to make life easier for its inhabitants. Specifically, within the area of urban mobility, the possibility of detecting anomalies in the movement of pedestrians and vehicles is an issue of vital importance for the planning and administration of a city. The aim of this paper is to propose a methodology to detect the movement of people from the information transmitted by their smart mobile devices, analyze these data, and be able to detect or recognize anomalies in their behavior. In order to validate this methodology, different experiments have been carried out based on real data aiming to extract knowledge, as well as obtaining a characterisation of the anomalies detected. The use of this methodology might help the city policy makers to better manage their mobility and transport resources.

引用

页码：54237 / 54253

页数：17