Soter

Abstract

In recent years, crimes against children and cases of missing children have increased at a high rate. Therefore, there is an urgent need for safety support systems to prevent crimes against children or for antiloss, especially when parents are not with their children, such as to and from school. However, existing children’s tracking systems are not smart enough to provide the safety supports, as they simply locate the children’s positions without offering any notification to parents that their children may be in danger. In addition, there is limited research on children’s tracking and their antiloss. In this article, based on location histories, we introduce novel notions of children’s life patterns that capture their general lifestyles and regularities, and develop an intelligent data mining framework to learn the safe regions and safe routes of children on the cloud side. When the children may be in danger, their parents will receive automatic notifications from the cloud. We also propose an effective energy-efficient positioning scheme that leverages the location tracking accuracy of the children while keeping energy overhead low by using a hybrid global positioning system and a global system for mobile communications. To the best of our knowledge, this is the first attempt in applying data mining techniques to applications designed for children’s safety. Our proposed techniques have been incorporated into Soter , a children’s safeguard system that is used to provide cloud service for smart bracelets produced by Qihoo. The case studies on real smart bracelet users of Qihoo demonstrate the effectiveness of our proposed methods and Soter for children’s safety.