Human Behaviour Detection Using GSM Location Patterns and Bluetooth Proximity Data

被引：0

作者：

Azam, Muhammad Awais ^{[1
]}

Tokarchuk, Laurissa ^{[1
]}

Adeel, Muhammad ^{[1
]}

机构：

[1] Queen Mary Univ London, Dept Comp Sci & Elect Engn, London E1 4NS, England

来源：

UBICOMM 2010: THE FOURTH INTERNATIONAL CONFERENCE ON MOBILE UBIQUITOUS COMPUTING, SYSTEMS, SERVICES AND TECHNOLOGIES | 2010年

关键词：

Behaviour; Cell tower ID; Bluetooth proximity; Neural Network; Jaccard Index;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Human behaviours are multifarious in nature and it is a challenging task to predict and learn from daily life activities. The profusion of Bluetooth enabled devices used in daily life has created new ways to analyze and model the behaviour of individuals. Bluetooth integrated into mobile handsets can be used as an efficient short range sensor. The aim of this research work is the detection of unusual human behaviours from cell tower and Bluetooth proximity data using neural networks. The primary purpose is to find anomalies in individual's daily life routines that will further help us to detect and predict unusual behaviour of elderly people and patients such as dementia patients.

引用

页码：428 / 433

页数：6

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