A Smart Electronic Tagging System Based on Context Awareness and Machine-to-Machine Interworking

The existing electronic tagging system traces the location of a sex offender using triangulation by communicating with Global Positioning System (GPS) satellites and mobile phone base stations. The acquired location information is used to prevent the offenders from perpetrating repeat crimes. However, the battery resources of such a system are inadequate as it has to trace the location of the moving target in real time and consumes a large amount of battery power while communicating with GPS satellites and mobile phone base stations. In addition, the systems cannot infer the mental state of the targets or detect their alcohol consumption levels, which may be necessary for the prevention of a repeat crime. The purpose of this study is to connect the Ubiquitous System Network (USN), which consumes little electricity, and Android mobile platforms, which are commonly used for machine-to-machine communication. Thus, this system will legally facilitate the protection of minors by providing information only about the target's approach to certain facilities. In addition, the system uses an Android platform to process data measured by the USN's sensors, which can also detect alcohol intake and infer the mental state of the target, and then initiates the corresponding real-time context-awareness services.