Unconventional Public Transport Anonymous Data Collection employing Artificial Intelligence

被引：3

作者：

Minea, Marius ^{[1
]}

Dumitrescu, Catalin ^{[1
]}

Chiva, Ionut-Cosmin ^{[1
]}

机构：

[1] Univ Politehn Bucuresti, Transports Fac, Bucharest, Romania

来源：

PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTERS AND ARTIFICIAL INTELLIGENCE (ECAI-2019) | 2019年

关键词：

Bluetooth; anonymous data collection; machine learning; filtering algorithms; Delaunay trilateration;

D O I：

10.1109/ecai46879.2019.9041957

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents results of a research concerning the possibility of collecting anonymous data regarding public transport level of service, employing wireless technologies (Bluetooth and Wi-Fi), big data and statistical filtering. Machine learning algorithms are used to detect, locate, create a map and record presence of travelers in public transport vehicles and stations, along with regular traffic data. The solution could also serve as back-up system for locating vehicles on their path.

引用

页数：6

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